Software#
The Vera C. Rubin Observatory In-Kind Program includes contributed software: directable and non-directable software-development effort that international partners contribute to Rubin teams and LSST Science Collaborations. This page lists all current software-development contributions. General pool contributions – directable effort offered without a recipient defined ahead of time – are listed on the General Pool page instead.
Use the filters or the table below to browse by category, science keyword, or recipient group. Each entry starts with the basics from the original proposal; cards marked Delivered have a full team-submitted record on file, and cards marked In Progress are still awaiting that submission. Some software contributions also produce a dataset – where that’s the case, the card links to the matching entry on the Datasets page.
Please email the in-kind helpdesk rubin-inkind at noirlab dot edu if you have any questions about contributed software.
| Software | Category | Primary recipient | Status | Updated |
|---|---|---|---|---|
| Directable SW dev | LSST AGN Science Collaboration | Delivered | 2026-07-29 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | Delivered | 2026-07-29 | |
| TBD | TBD | Delivered | 2026-07-29 | |
| Non-directable SW dev | LSST Transients and Variable Stars Science Collaboration | Delivered | 2026-07-29 | |
| Directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | Rubin Photo-z Coordination Group | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST AGN Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Solar System Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST AGN Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST AGN Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST AGN Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | Rubin Prompt Processing Group | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Solar System Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Stars Milky Way and Local Volume Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | Rubin Algorithms & Pipelines Team | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST AGN Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | Rubin Commissioning Team | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Stars Milky Way and Local Volume Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Stars Milky Way and Local Volume Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | Rubin SQuaRE Team | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Strong Lensing Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Stars Milky Way and Local Volume Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | Rubin Crowded Field Coordination Group | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST AGN Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | Rubin Prompt Processing Group | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Transients and Variable Stars Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Strong Lensing Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Galaxies Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Strong Lensing Science Collaboration | In Progress | 2026-07-22 | |
| Non-directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | Rubin International Program Coordinator (Software Development) | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Solar System Science Collaboration | In Progress | 2026-07-22 | |
| Directable SW dev | Rubin Algorithms & Pipelines Team | In Progress | 2026-07-22 | |
| Directable SW dev | LSST Dark Energy Science Collaboration | In Progress | 2026-07-22 |
SER-SAG-S1
Science Pipeline Development for analysis of variability of celestial sources in the LSST AGN and TVS Science Collaboration
Astronomy software Astrophysics Exoplanet astronomy Stellar astronomy Planetary science Solar system
Primary recipient: LSST AGN Science Collaboration
Additional recipients: LSST Transients and Variable Stars Science Collaboration, Rubin Commissioning Team, Rubin Telescope & Site Team
Software: QhX v0.2.1 (main inkind derivable), additional delierable QNPy-Latte 0.1.0
Start (approx.): FY22
Links: main inkind deliverable software QhX source repository, SER-SAG-S1 GitHub organisation, additional software QNPy-Latte source repository, QNPy-Latte package page, LSST-SER-SAG-S1/QNPy_Latte
Documentation: main software deliverable QhX documentation, QhX closeout software archive, additional software QNPy-Latte
The SER-SAG staff will contribute directable software development in the general area of LSST AGN and TVS variability of celestial sources analysis, including, but not limited to, the detection of AGN and TVS periodicity and reverberation mapping from the LSST data products (primarily the Object catalogs and time series, and potentially images).SER-SAG staff will work with the recipients of the AGN and TVS SC to define needed software development tasks, and then carry out those tasks as an integral part of these collaborations, reporting regularly on progress, taking input from the rest of the collaboration, and supporting and training the collaboration’s members in the use of the code. We intend to work flexibly with the recipients following their direction in developing and delivering software products as required. Following the advice of AGN SC point of contact, the exact shape of the directable contribution and a final decision on its endorsement would be pending AGN SC consultation that could not be finished before the 25 September deadline. The TVS SC values SER-SAG directable software efforts, and intends to offer endorsement of SER-SAG proposal to the US agencies.We predict moderate amounts of local computing resources for this work, which are already available at SER-SAG, and we will obtain additional local resources if needed by application to the Institute of physics Belgrade high performance computing center. Additionally we will use opportunities provided by Serbian Ministry of Education Science and Technological development to apply for funds through their recurrent triennial calls IDEJE (e.g. we will submit a proposal ExtraUniverse at the first call with deadline Oct8,2020).Our directable-software contribution to the TVS and AGN SC may move towards the development of an iterative modular classification system for variable stars and transients based on machine learning algorithms. This idea is supported by Croatian, Hungarian, Serbian and Slovenian institutions sharing joint interests and expertise in time-domain astronomy and astrophysics and willing to commit resources towards its development. We concentrate on using Rubin-provided user computing resources upon their availability to optimize and fortify the code functions at the needed scale. The primary risk in this work is in obtaining the needed skills in the Rubin tools and data products. To overcome this, the SER-SAG staff will train early with any Rubin tutorials provided, and be active participants in events associated with the Rubin “Data Previews”, all within the context of the AGN and TVS SC.
Also see: dataset (SER-SAG-S1) →Updated: 2026-07-29
UKD-UKD-S17
Galaxy Clustering Infrastructure
Galactic and extragalactic astronomy
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: LSST Galaxies Science Collaboration
Software: TXPipe v0
Links: LSSTDESC/TXPipe
Documentation: https://txpipe.readthedocs.io/en/latest/
This directable staff effort contribution has been developed jointly with DESC and GSC. This contribution will focus on providing infrastructure for the treatment of one of the biggest sources of systematic uncertainty for galaxy clustering: the non-cosmological modulation of galaxy density caused by Galactic and observational sky contaminants (e.g., dust extinction, stars, PSF fluctuations). The proposed work is timely and impactful: it will be developed in conjunction with other lensing/clustering infrastructure work as part of the LSST:UK in-kind contribution, and validated on early Rubin data, addressing multiple deliverables in the GSC and DESC Science Roadmaps. It will result in long term, accumulating gains, affecting multiple science cases as systematics mitigation methods will be needed throughout Rubin.The work will be carried out in four stages:Stage 1 (FY24-25): Standard contaminant mapping and cleaning methods. LSST:UK will make a full implementation of standard contaminant mapping and cleaning methods in the existing DESC analysis pipeline (TXPipe). This includes mapping of survey depth and contaminant moments, linear deprojection, random catalog generation.Stage 2 (FY25-26): Source injection infrastructure. LSST:UK will implement Source Injection (SI) methods, adding mock objects to images and reprocessing them to characterise system responses. LSST:UK will implement the significant software infrastructure to inject and process fake sources, and to process the resulting catalogs with TXPipe.Stage 3 (FY26-27): Optimal data cuts and robust clustering measurements. LSST:UK will develop software to produce robust GC measurements using SI, in order to recommend optimal quality and sky cuts, produce catalog weights and cleaned overdensity maps, and compute diagnostics (e.g. signal-systematic correlations).Stage 4 (FY27): Clustering data products from DR1 and DR2. LSST:UK will apply the new infrastructure to DR1 and DR2 data, to test and compare standard SI decontamination methods. LSST:UK will generate vital products for any clustering measurements made by the DESC and the GSC: random catalogs, masks, systematic maps.
Updated: 2026-07-29
UKD-UKD-S5
LSST–VISTA Fusion Pipeline including two public repositories: lsst-ir-fusion (version: v1.0.0) and obs_vista (version: v1.2.0)
Galactic and extragalactic astronomy Interdisciplinary astronomy Observational astronomy
Primary recipient: TBD
Additional recipients: None
Software: LSST–VISTA Fusion Pipeline including two public repositories: lsst-ir-fusion (version: v1.0.0) and obs_vista (version: v1.2.0)
Links: lsst-uk/obs_vista
Documentation: lsst-ir-fusion documentation
TBD
Also see: dataset (UKD-UKD-S5) →Updated: 2026-07-29
UKD-UKD-S9
Science Software development: Cross-matching
Cosmology Galactic and extragalactic astronomy Interstellar medium Observational astronomy Stellar astronomy
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: LSST Stars Milky Way and Local Volume Science Collaboration
Software: macauff
Start (approx.): FY20
Links: macauff/macauff
Documentation: https://macauff.readthedocs.io/
The depth of the LSST survey represents an almost unique challenge to attempts to cross-match the catalogues to other surveys, because of the combination of depth and point-spread function. The LSST is deeper than any ground-based survey to date, yet the Rubin observatory is still limited by ground-based seeing. As a result the number of stars per point-spread function is very large. At the most basic level this means that traditional matching by (say) a 2” proximity match will get confused. As an example, roughly half the galactic plane within -90 < l < 90 and |b|< 10 reaches a density of sources such that in a single visit that there will (on average) be one random match per 2” circle. Hence as the survey becomes deeper this problem will spread out of the plane until by full depth it is even having a small effect on high latitude fields. This problem can be overcome by using the uncertainties in the astrometry to show whether sources are truly co-incident, but requires a fully Bayesian approach which takes into account the local stellar density (see Sutherland & Saunders 1992MNRAS.259..413S). However, there is also a second more subtle problem which affects the astrometric uncertainties and means one cannot simply use the uncertainties from image centroiding. This is that the stellar densities at magnitudes below the survey detection limit are so high that undetected stars affect the centroids. These effects are significant, but can be modelled (Wilson & Naylor 2017MNRAS.468.2517W). Finally, photometric information can also be used to assess whether a match is likely (Wilson & Naylor 2018MNRAS.473.5570W). This proposal is to make cross-matches between the LSST and the VISTA, VPHAS, WISE and Spitzer surveys using these up-to-date techniques available to astronomers both as a software package and tables of matches. The work is endorsed by the TVS SC, hence we are proposing this as non-directable effort. An endorsement has been requested from SMWLV, and we have engaged with the Rubin Crowded Field Coordination Group.We have LSST:UK funding in place to write the software, validate it against Hyper Suprime-Cam data and integrate it into the UK IDAC. During operations the software could be run either on the UK IDAC, or be part of the standard release pipeline, producing cross-match tables between the entirety of the LSST and the other surveys. The compute time required to build the tables will be provided through the UK IDAC computing resource as described in S3.
Also see: dataset (UKD-UKD-S9) →Updated: 2026-07-29
AUS-AAL-S2
Dedicated Software Development Effort
Astronomy software Galaxies
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: None
Start (approx.): FY21
ADACS-Maquarie will contribute directable software development effort in the general area of Rubin Low Surface Brightness science analysis, including establishing the optimal sky subtraction method for retaining this light. As sky estimation affects source detection, de-blending, and photometry, and requires access to all the pixels, it is best done early in the processing steps rather than as level-3 post-processing. ADACS-Maquarie staff will work with the Galaxies SC and Low Surface Brightness WG to define the optimal method, as an integral part of the collaboration taking input from the rest of the WG and SC, and supporting the integration of that code into the Stack taking input from the Rubin DM team and reporting regularly on progress.We have developed this contribution in coordination with the Galaxies Science Collaboration which supports our proposed approach.We anticipate needing modest amounts of local computing to support this work and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at ADACS-Maquarie and UNSW (where Prof Brough is located), and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the ADACS-Maquarie staff will engage early with the Rubin DM team, and would be expected to work through the “stack club” tutorial notebooks as well as to be active participants in the current Low Surface Brightness Working Group Challenges, within the context of the Galaxies SC. Should travel become possible, travel to meet with the Rubin DM team will be supported.
Updated: 2026-07-22
BRA-LIN-S3
Contributions to Science Pipeline Development in the LSST-DESC TJP Working Group
Astronomy software Cosmology
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY21
LIneA will contribute with directable software development effort in the general area of cosmological calculations (Theory, Covariances, and Joint Probes). The direct software development efforts include the development and validation of CCL, firecrown, and development of TJP Covariance pipeline (TJPCov) for multiprobe analysis. Since development will take place inside DESC projects, most of it will be done locally and tested inside Rubin-provided computer resources (NERSC). When it comes to this proposal, the main challenge is acquiring the needed expertise in the LSST-DESC. In order to mitigate this risk, the members are engaged with the Pipeline Scientist group and interacting within the DESC TJP working group. If necessary LIneA also provides computing infrastructure that can be used to run and test the developed codes.
Updated: 2026-07-22
BRA-LIN-S4
Infrastructure and data sets to support photo-z generation
Astroinformatics Astronomy software Galaxy clusters Machine learning Photometric redshift Spectroscopy
Primary recipient: Rubin Photo-z Coordination Group
Additional recipients: Rubin Algorithms & Pipelines Team, LSST Galaxies Science Collaboration
Start (approx.): FY21
LIneA will contribute directable software development effort in the general area of data preparation for science analysis in LSST. The contribution consists of adding value to the LSST Data Release Objects catalog providing standardized training and validation sets, photometric redshifts and galaxy properties estimates. LIneA staff is already participating in the Photo-z Virtual Forum and will work with LSST Project to define needed software development tasks and deliverable data products, carry out those tasks as an integral part of the contribution, take input from the rest of the Science Community/users, regularly reporting the progress.The planned activities include: (i) Maintain a spectroscopic redshifts (spec-z) repository with data from public releases of spec-z surveys, monitor the literature to keep the spec-z repository up to date, produce standardized training and validation samples regularly before each DR, work together with the Project to make these data products available to the community via RSP. (ii) Develop a photo-z server to support the 'Photo-z Validation Cooperative' including the implementation of a photo-z validation pipeline and administrative tools. Write documentation and provide office hours to support authors for integrating new photo-z codes into the pipeline. Work collaboratively with the Project to make this service available to the community on RSP. (iii) Support to the 'Photo-z Validation Cooperative' in organizing the results from different groups and making it available in a single document. (iv) Run the photo-z(s) algorithm(s) chosen by the community, produce photo-z (single estimates and posterior PDFs) and galaxy properties catalogs for all objects in the Object catalog and export the results to the RSP as federated datasets before each DR. The proposed activities include the upgrade of photo-z related pipelines of the DES Science Portal to scale to the data volume of LSST (the photo-z related input and output columns) and improve some of the short-comings identified in the earlier DES version. To this end new software solutions are already being investigated by the LIneA IT team to improve the orchestration code to make it more flexible and portable, and the handling of the input data taking advantage of the new Lustre storage system, which is being installed and tested by Adean. In recent preliminary tests done by Singulani using Parsl (http://parsl-project.org, Babuji et al., 2019) to orchestrate a workflow for running the template-fitting code LePHARE (Arnouts et al. 1999, Ilbert et al. 2006), LIneA achieved a benchmark of 0.2 milliseconds per object, which can be interpreted as an upper limit estimate considering that machine learning codes are, on average, faster than the template-fitting ones. That benchmark includes the whole process of transforming data from parquet files into ascii inputs required by LePHARE, running all steps of the photo-z code, and saving the outputs also in parquet format. Such activities are part of the ongoing revision of the codebase which is being carried out to improve performance and include in-line documentation. In parallel, a considerable effort is being carried out to document the code and write technical notes describing the products to the users. LIneA agrees to share the software created to serve LSST as open-source in any code sharing platform adopted by the recipient groups. The precursor DES Science Portal codes are already in public domain in GIT (http://git.linea.gov.br), except for the private scientific codes which are wrapped into the Portal and used as 'blackboxes'. All LIneA's public codes are in the process of migration to LIneA's organization on Github (https://github.com/linea-it). LIneA anticipates that a considerable amount of local computing will be required to support this work, with seasonal peaks of usage before each data release. LIneA will provide local computing resources and storage space for the products which will be federated with other DACs and the IDAC network via the Brazilian Lite-IDAC, pending its final approval. The processing will be carried out using the computer clusters already available in LIneA's datacenter. The remaining resources are dependent on the approval and subsequent implementation of the Brazilian IDAC, so the risk associated with this work is coupled with the IDAC project's success.
Updated: 2026-07-22
CAN-CAN-S3
Science Pipeline Development in the LSST Dark Energy Science Collaboration
Astronomy software Cosmology Gravitational lensing Photometric redshift Spectroscopy Supernovae
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: Rubin Photo-Z Coordination Group
Start (approx.): FY23
The Canadian LSST consortium will contribute directable software development effort in the general area of LSST DESC science analysis, which may include, but is not limited to:the development of Alert/broker support/difference image analysis support;the development of spectroscopic follow-up targeting software;the integration of the supernova pipeline and adaptation to the real science verification data;contributions to weak lensing image simulations;developing cross-correlation pipelines with wide-field surveys such as Euclid for galaxy shapes and photo-z estimation, should a collaborative agreement be reached between Euclid and Rubin; support of the DESC computational infrastructure pipeline.The dedicated staff will work with the DESC leadership to define needed software development tasks, and will be embedded in the DESC. They will carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. In addition to DESC resources, the staff will use the CLASP computing resources if needed to complete these tasks.
Updated: 2026-07-22
CAN-CAN-S4
Science Pipeline Development in the LSST Transient and Variable Star Science Collaboration
Astronomy software Spectroscopy Time domain astronomy Transient detection Variable stars
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY22
The Canadian LSST consortium will contribute directable software development effort through CLASP Infrastructure Fellows (CIF) who will work in the general area of LSST TVS science analysis, including but not limited to the development of Alert/broker support/difference image analysis support, and the development of spectroscopic follow-up targeting software.The dedicated staff will work with the TVS leadership to define needed software development tasks, and will be embedded in the TVS. They will carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. The staff will use the CLASP computing resources if needed to complete these tasks, no additional computing support will be required from TVS resources.
Updated: 2026-07-22
CAN-CAN-S5
Science Pipeline Development in the LSST Galaxies Science Collaboration
Astronomy software Galaxies Photometric redshift Spectroscopy
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: None
Start (approx.): FY23
The Canadian LSST consortium will contribute directable software development effort in the general area of LSST Galaxies science analysis, including but not limited to building pipelines for galaxy classification and morphology studies and developing spectroscopic training pipelines of photometric redshift estimates, however the CIF will work on the specific tasks needed by the Galaxies collaboration as a directable contribution.The dedicated CIF will work with the leadership of the Galaxies collaboration to define needed software development tasks, and will be embedded in the LSST Galaxies collaboration. They will carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. The staff will use the CLASP computing resources if needed to complete these tasks.
Updated: 2026-07-22
CAN-CAN-S6
Science Pipeline Development in the LSST AGN Science Collaboration
Active galactic nuclei Astronomy software Time domain astronomy Transient detection
Primary recipient: LSST AGN Science Collaboration
Additional recipients: None
Start (approx.): FY23
The Canadian LSST consortium will contribute directable software development effort for LSST AGN science analysis, in two general areas:Developing image stacking, image differencing, and variable-source detection software components of the LSST Software Stack that are optimized for detecting variability on longer timescales of weeks to months. This software will be distinct from LSST’s transient detection pipeline, which is optimized for detection of transients and variability on shorter timescales of days. This distinction is crucial because AGN characteristically exhibit observed-frame optical continuum variability on longer timescales than transients. For example, slow stochastic variability on timescales of weeks from a faint AGN in a spatially-extended dwarf galaxy would be missed by the standard transient detection pipeline in the LSST Software Stack, and its detection would require stacking and subtraction of images taken over several weeks. Developing an AGN alerts pipeline for detection and rapid notification of peculiar AGN variability activity, such as outbursting or fading ‘changing-look AGN’. These objects puzzlingly exhibit a wide variety of variability properties that do not seem to follow the well-known red-noise variability of most AGN. The origin of these peculiar variability phenomena in both emission and absorption and their relation to other types of nuclear variability (such as Tidal Disruption Event flares) are unknown. The AGN alerts pipeline would use light curves from the image differencing software described above to detect any peculiar variability in real-time, based on modeling the temporal and spectral properties of the non-simultaneous multi-band light curves that are updated as the data are obtained.This proposal has been endorsed by the LSST AGN Science Collaboration. The dedicated staff will work with the leadership of the AGN Science Collaboration to define needed software development tasks, and will be embedded in the AGN collaboration. They will carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. The staff will use the CLASP computing resources if needed to complete these tasks.
Updated: 2026-07-22
CAN-CAN-S7
Science Pipeline Development in the LSST Solar System Science Collaboration
Astronomy software Solar system astronomy
Primary recipient: LSST Solar System Science Collaboration
Additional recipients: None
Start (approx.): FY23
The Canadian LSST consortium will contribute directable software development effort in the general area of LSST Solar System science analysis, to meet some of the requirements laid out in the SSSC software roadmap[2]. Possible contributions that match well with the anticipated expertise of the PDF include:Developing hooks between the Canadian LSST public archive and the CADC’s Solar System Object Image Search archival tools to enable pre-covery of newly discovered moving bodies, for use by the SSSC, as encouraged through the CEC’s feedback of the CLASP LOI.An ephemeris driven cutout service.A forced photometry package with techniques appropriate for moving objects like those implemented in Trailed Imaging in Python[3]The dedicated staff will work with the SSSC leadership and the SSSC’s Community Software and Infrastructure Development Working Group, to define needed software development tasks, and will be embedded in the SSSC. They will carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. The staff will use the CLASP computing resources if needed to complete these tasks.
Updated: 2026-07-22
CRO-RBI-S1
Science Analysis Infrastructure Effort
Astronomy software Time domain astronomy Transient detection
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: Rubin International Program Coordinator (Software Development)
Start (approx.): FY21
Software development effort would be provided by the two of the institutions participating in CPG: RBI and HO. In both cases a postdoctoral researcher would be hired, in order to provide directable software development effort. Whether the contribution will be in the terms of general pooled effort or directable software effort embedded in the TVS SC will depend on the outcome of the selection procedure. In either case the selected candidates will provide no less than 0.5 FTE/year. This approach is motivated by a risk that we have identified and its mitigation strategy: we do not expect that many software engineers with PhDs (ideally working full time on LSST software development) or astronomy postdocs (working part time on software development) will be applying to the positions that we will be advertising. By advertising a more flexible scheme, we hope to attract a larger talent pool and ultimately select better candidates. We have already requested TVS SC Justice, Equity, Diversity, and Inclusion (JEDI) group to act as advisors in order to help us select the best candidates and ensure fairness throughout the hiring procedure. We would like to extend the same invitation to any relevant group or committee at the LSST-wide level.As the efforts are directable, we would work with the relevant LSST groups to define the exact kind of the needed software development tasks, carry out those tasks, report regularly on the progress, take input from the rest of the collaboration and support collaboration members in the use of the code. Presently it is difficult to assess the local hardware requirements, but we do note that significant computing resources are offered as the second part of our contributions (CRO-RBI-2) and that it would be logical to make use of these resources. TVS SC endorsement has been received for these contributions.In case of the general pooled software development effort to either the LSST science collaborations or Rubin Observatory teams, CPG staff will work with the Rubin International Program Coordinators (and through them, the CEC) to identify a suitable recipient group, work with that group to define needed software development tasks, and then carry out those tasks as an integral part of the group, reporting regularly on progress, taking input from the rest of the group, and supporting the group’s members in the use of the code.
Updated: 2026-07-22
ESP-BCM-S1
Contribution of Directable Software Development Effort to DESC Computing Infrastructure Operations team
Astronomy software Cosmology
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY21
BCN-MAD will contribute directable effort to the Dark Energy Science Collaboration in the form of focused planning, development and deployment of test cases and procedures for ongoing and planned Data Challenges of DESC, adapting to, reinforcing or repurposing current efforts in this area from scattered groups and researchers. Long term planning will start in October 2020 so that these tests can eventually be reworked into tests for Data Management products within the context of DESC, as commissioning data becomes available, even feeding back into this process where applicable. The fact that the Contribution Lead is applying also for some effort in the Project’s commissioning team can be of great value for both contributions and synergistic.The proposed contribution lead would adapt to any other tasks within the context of Computing Infrastructure for DESC. The detailed work plan will be developed in consultation with the relevant members of the DESC leadership. Regular reporting would be made as planned by DESC. The Contribution’s Lead group at CIEMAT has direct access to moderate computing resources, which are considered sufficient, as in principle most of the development and execution will be done in the NERSC environment. The Contribution Lead has already access and experience working with the DESC environment at NERSC.
Updated: 2026-07-22
ESP-BCM-S3
Contribution of Directable Software Development Effort to DESC Large Scale Structure and/or photo-z WG
Astronomy software Cosmology Photometric redshift
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY23
BCN-MAD will contribute directable software development effort to the Dark Energy Science Collaboration in the general area of Large Scale Structure and photometric redshifts. BCN-MAD will work with the DESC SC to define the needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration members in the use of the code. The detailed work plan will be developed in consultation with the relevant members of the DESC leadership. BCN-MAD anticipates a modest amount of computing for development, especially given that full deployment will require the use of official Rubin computing resources and NERSC. In any case, the Group counts with substantial local resources as well which should be more than enough for the scale of these focused developments, as well as potentially direct access to one of LSST’s Lite IDACs. The BCN-MAD team has engaged the Rubin data environment already through one of its team members (see Contribution 1), which would transfer the needed knowledge to members of this new team locally.
Updated: 2026-07-22
GER-ARI-S1
Target and Observations Management (TOM) system Development in the LSST TVS Science Collaboration
Astronomy software Time domain astronomy Transient detection
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY22
ARI will contribute directable software development effort in the general area of LSST TVS science analysis focused primarily in the development of a Target and Observation Management (TOM) system to serve the specific science goals of TVS. ARI staff will work with the TVS SC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. We anticipate needing modest amounts of cloud computing to support this work, and will focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned cloud computing resources will be secured by ARI on a well established commercial cloud server, such as Amazon AWS, and we will work with TVS to arrange additional resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the ARI staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the TVS SC.
Updated: 2026-07-22
GER-CCL-S1
Science Pipeline Development in the Dark Energy Science Collaboration
Astronomy software Cosmology Galaxy clusters Gravitational lensing Photometric redshift Spectroscopy
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY22
The GCCL will contribute directable software development efforts in the general area of Dark Energy Consortium science analysis, working with DESC to define needed software development tasks. We will carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. Our preference is for the GCCL directable effort to be mainly embedded within the DESC Photometric Redshift working group, for example making a significant contribution to photometric redshift calibration and quantifying and mitigating spectroscopic incompleteness. Given the wide range of expertise at the GCCL, the group could also, however, contribute to the LSST optical cluster detection algorithm and the quantification of the resulting selection function, both key deliverables for the Cluster working group, in addition to contributing to a wide range of different deliverables required for the weak lensing working group and the theory-joint probes working group. We will work with DESC leadership to narrow down this wide range of activities into a defined list of tasks based on their needs and the skill profile of the postdocs and/or software engineers that will be recruited for the start of FY22. With mutual agreement, the DESC may request a change of direction in the future if the goals and resources available to the DESC require it. We have significant funding to support the local computing that will be required to support this work. Based on the requirements from the final defined list of tasks, a procurement exercise will be undertaken to ensure that we have appropriate computing resources, in addition to our already existing compute cluster. We will also use NERSC resources to ensure the code we contribute runs well at NERSC such that DESC members outside the GCCL can easily collaborate with the GCCL team.The primary risk associated with this work is in the recruitment and retention of staff with relevant expertise and skills. This risk will be mitigated somewhat by offering each new GCCL member hired for this role, the opportunity to use up to 50% of their time to pursue their own research interests, over a full three-year position. In addition we have a significant number of existing experienced GCCL fellows with strong interests in DESC, whose efforts could be diverted to directable software development effort, if the task is already in line with their scientific interests.
Updated: 2026-07-22
GER-CCL-S2
Science Pipeline Development in the Dark Energy Science Collaboration
Astronomy software Cosmology Galaxy clusters
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY25
As part of the GCCL contribution, Robert Reischke and Andrina Nicola will contribute directable software development efforts to LSST DESC. After consultation with the WLSS, MCP and CL WGs in DESC as well as the analysis coordination team, we have settled on the following proposed development effort: The primary goal of this contribution is to implement the covariance tools needed to perform cluster cosmology analyses using TJPCov and CCL. We will implement theoretical predictions for cluster overdensity cross-correlations into CCL. In addition, we will implement cluster cross 2pt-function covariances into TJPCov and validate them using independent implementations. We will do this both for optical clusters as well as tSZ-selected clusters to allow for joint analyses with CMB surveys. In particular, we will coordinate development of the analysis pipeline with the Simons Observatory to facilitate future combined analyses (examples are: consistent theory predictions and likelihoods/samplers). In a first step, we will focus on Fourier space. If needed, we could also extend to real space correlations.In a second part of this in-kind contribution, we will support the development of the augur forecasting tool and help with implementing cluster cosmology forecasts. However, with mutual agreement, the DESC may request a change of direction in the future if the goals and resources available to the DESC require it.We have secured funding to cover the position of Robert Reischke, who has joined the AIfA in October 2023. He will be able to dedicate 0.5 FTE for 2 years starting at any time convenient for Rubin and DESC. In addition, we have access to local computing resources to support this work. We will also work on NERSC to ensure that the developed tools run there as well and to facilitate collaboration with other DESC researchers. Given that a person with very relevant expertise has already been hired, the risk associated with this contribution is minor.
Updated: 2026-07-22
GER-LMU-S1
Calibration pipeline development for Weak Gravitational Lensing analyses in the LSST Dark Energy Science Collaboration [near-term directable software development]
Astronomy software Cosmology Gravitational lensing Photometric redshift
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY22
Prof. Dr. Gruen’s team will contribute directable software development effort in the general area of LSST Dark Energy science weak lensing analysis. Depending on the candidate hired with the transition of the group to LMU, an on coordination with the relevant DESC working groups, this could e.g. be in the area of image simulations for weak lensing shear and photometric redshift calibration or other pipelines for photometric redshift calibration purposes, or the correction of other weak lensing related systematics in DESC observables. Team members will work with the DESC, particularly the WL, PZ, and BL working groups, to define needed software development tasks. They will then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, supporting the collaboration’s members in the use of the code, and running the code at scale to produce the required calibrations for DESC weak lensing science. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at Munich, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products and connect and extend them for the needs of weak lensing calibration: to mitigate this, staff will engage early with DESC working groups, the DESC Spokespersons and Analysis Coordinators, any tutorials and codes provided, and look to be active participants in the WL, PZ and BL working groups.
Updated: 2026-07-22
GER-LMU-S2
Galaxy Cluster Analysis Infrastructure [near-term directable software development, developed in consultation with LSST-DESC]
Astroinformatics Astronomy software Cosmology Galaxy clusters Gravitational lensing
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY22
We will contribute directable software development effort to DESC in the general area of enabling cluster cosmology analyses. Under the direction of the relevant members of the DESC leadership, and depending on the candidates hired for these tasks, we propose to contribute to i) the development and testing of the multi-observable cluster cosmology pipeline, ii) the simulation-based calibration of the relationship between halo mass and the weak-lensing shear signal, accounting for all relevant sources of systematic uncertainties, iii) the tools required for the construction of multi-wavelength cluster catalogs, and iv) the development and implementation of emulators, with particular focus on the cosmological emulators as defined in the DESC science roadmap. In consultation with the relevant members of the DESC leadership--- presumably including the coordinators of the Clusters, Weak Lensing, and Cosmology Simulations working groups--- we will work to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, supporting the collaboration members in the use of the code, and running the codes at scale to produce the required data products and results.We expect the computational needs associated with our contributions to be provided at NERSC, DESC’s primary computing center, but to also draw upon local resources owned by our group and major computing resources in the Munich area to which we have guaranteed access (e.g., C2PAP at LRZ). This range of computing resources will support efficient development and testing while allowing more extensive testing to ensure the codes function at the needed scale.The primary risk associated with this work is in gaining the needed expertise in the Rubin and DESC tools and data products and in understanding how best to apply them in the context of cluster cosmology. To mitigate this, our group members will engage early with the appropriate DESC working groups, analysis coordinators, and any available tutorial and instruction resources. We wish to be active participants in the clusters, weak lensing, and computing working groups and to establish fruitful scientific and technical exchange.
Updated: 2026-07-22
GER-LMU-S3
Cluster Line of Sight Simulation Software (near-term directable software development)
Astroinformatics Astronomy software Cosmology Galaxy clusters Gravitational lensing
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY21
Stella Seitz’s group will contribute directible software development which aims to support LSST cluster weak lensing analyses and derived cosmological constraints. Since we have expertise in generating realistic cluster lines of sights and rendering the according photometric-morphological catalogues into image simulations we find it likely that our effort is directed by the Survey Simulations and the Clusters WGs. To specify our contribution, we will consult the relevant members of DESC leadership regarding the WG priorities and we will then develop a work plan via mutual agreement. Since cluster weak lensing analyses are interconnected to the BL, the PZ, the WL, the SSim, and TJP WGs we expect that our team members will interact with all the aforementioned WGs to optimally fulfill the software development tasks.In case our group is directed in a way that involves producing image simulations, we would like to ensure that they are processible with Rubin's LSST Science Pipelines. For that reason we would like to (where appropriate and beneficial to the success of the work) use and may be update existing collaboration tools, like imsim, which produces galaxy images adapted to the LSST telescope and survey conditions.We will carry out the software development as an integral part of the collaboration, reporting regularly on progress, taking input from our colleagues and supporting the collaboration’s members in the use of the code. We have secured the needed amounts of local computing for this work, but will be keen on using DESC computing resources (at NERSC) as they become available to us, to ensure that the code functions at the needed scale. In addition, to ensure that DESC members have read access during all stages of code development we plan to host any code development on DESC GitHub.The primary risk associated with this work is to find high level experts familiar with the complex subject. Since we have such a skilled person in our group now (until summer 2023) we would like to contribute our FTE at the earliest time possible (see below).
Updated: 2026-07-22
GER-LMU-S4
Cluster Finding and Likelihood: development and validation [near-term directable software development]
Astroinformatics Astronomy software Cosmology Galaxy clusters
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY35
Prof. Dr. Weller’s team will contribute directable software development effort in the general area of LSST Dark Energy science cluster cosmology analysis. Depending on the candidates hired and on coordination with the relevant DESC working group, this could e.g. be in the area of defining the likelihood and cluster selection function or validating the cluster finder with additional data and complementary finders or implementing cluster clustering as a probe under consideration of the full covariance. To specify our contribution, we will consult the relevant members of DESC leadership regarding the WG priorities and we will then develop a work plan via mutual agreement. Team members will work with the DESC, particularly the CL, LSS and TJP working groups, to define needed software development tasks. They will then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration and supporting the collaboration’s members in the use of the code. The Postdocs will make use of standard DESC software tools/tutorials to help them to get engaged with the DESC activities and procedures.We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at Munich, also by preferential access to the local computing centers like for example the Leibniz Supercomputing Centre via the Excellence Cluster Origins structure. However, the primary platform for the development and implementation of the software tools will be NERSC as DESC's primary computing center. The primary risk associated with this work is the availability of realistic galaxy cluster catalogs to calibrate the cluster selection function. This can be mitigated with the staff to closely collaborate with the simulations group of LSST-DESC to ensure the useful development of simulations.
Updated: 2026-07-22
GER-MPE-S1
Photometric redshift tuned for AGN
Active galactic nuclei Astroinformatics Astronomy software Photometric redshift Radio astronomy
Primary recipient: LSST AGN Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY22
MPE will contribute directable software development efforts in the area of photo-z computation for AGN identified by the AGN SC using LSST data (via e.g. colors, time variability), or other means (X-rays, radio, MIR etc) combined with LSST. A non negligible fraction of sources that LSST will detect are AGN and a dedicated effort to compute their photo-z will be needed. MPE staff will work with the AGN SC to define the required software development tasks, and then carry out the development. The software to be developed will not be part of any existing infrastructure, but rather a tool made available to the LSST SC and possibly to the entire community. It will be possible to use the tool also on catalogs of galaxies not known to host an AGN. The comparison between the traditional photo-z for galaxies and photo-z for AGN will ensure that peculiar sources are flagged, which may help the scientific output of other SCs. We have reached out to the primary contacts for GAL and DE SCs, who are interested in exploring how this work could benefit their collaborations. We will also contact the SLSC and the TVS SC as they may also be interested in the work. We will liaise with Rubin’s photo-z Coordination Group as needed.MPE will provide regular progress reports on this work to the AGN SC as primary recipients. The software will be fully documented and initial support will be provided for collaboration members in its use. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the required scale. The primary risk associated with this work is in gaining the needed expertise in the VRO tools and data products. To mitigate this, the MPE staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the AGN SC, of which the Proposal Lead is already an active member.
Updated: 2026-07-22
GER-MPE-S2
MPE efforts to assure reliable photo-z for AGN
Active galactic nuclei Astronomy software Photometric redshift
Primary recipient: LSST AGN Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY22
MPE will contribute directable software development effort in the specific area of LSST AGN photometric redshifts. In general this contribution will comprise studies aimed at determining the best way to compute photo-z for AGN enhanced by LSST photometry. Together with the AGN SC and the AGN photo-z group at least two distinct areas that need development have already been identified and for which the expertise of MPE would be valuable. First, the construction and improvement of AGN templates (e.g. templates for obscured AGN). Second, a “recipe” that allows the merging of photometry from different surveys at different wavelengths, depending on e.g., whether the sources are extended or point-like. The latter development should allow reliable photo-z for AGN to be determined as soon as LSST data become available, to enable science while waiting for homogenised photometry (e.g., like that currently offered by Legacy Survey) to become available. These areas have been highlighted from a range of other related efforts towards realising reliable AGN photo-z’s. We will respond flexibly under the guidance of the SC to assist with effort towards the high priority development needed with mutual agreement. The studies will be in synergy and coordinated together with the experts of the AGN SC, to which the MPE group will report periodically.The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, MPE staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the AGN SC. The AGN SC and in particular the AGN photo-z group within the SC has endorsed this proposed contribution.
Updated: 2026-07-22
HUN-KON-S2
Directable Effort in the General Area of Machine Learning Classification and Associated Infrastructure Software
Astronomy software Machine learning Time domain astronomy Transient detection Variable stars
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY21
The Hungarian LSST Collaboration proposes to allocate directable software development efforts to support the activities within the TVS Science Collaboration. Our staff will work with the TVS SC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code(s). One such contribution might be the development of a machine-learning based classification pipeline to incrementally improve classification of variable point-sources with LSST multicolor light curves as more and more data are coming in during the 10-yr main survey. Since a monolithic classifier would not be able to meet the output purity requirements we propose an iterative modular system with different modules tuned for classification of specific transients and variable stars. We would take advantage of the fact that some of the modules may already be in development in other LSST Science Collaborations and incorporate these when possible in the proposed pipeline. The pipeline would be primarily based on LSST multicolor lightcurves, but would also take advantage of other LSST data products where possible (e.g. real/bogus brokers) as well as data from other surveys. Therefore, we will also work closely with the developers of LSST broker systems. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at Konkoly Observatory, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the our staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the TVS SC. Also, as Róbert Szabó has been a named PI for more than 3 years, has been an active member of the TVS SC, and participated in the annual Consortium meetings in Tucson (and virtually), he and his small team are already involved in Rubin Obs. activities.Recipient: LSST Transients and Variable Stars Science Collaboration (TVS) This contribution has been endorsed by the TVS Science Collaboration. This idea is supported by Croatian, Hungarian, Serbian and Slovenian institutions sharing similar interests and expertise in time-domain astronomy and astrophysics and willing to commit resources towards its development.
Updated: 2026-07-22
IND-ISR-S1
Science Pipeline Development in the LSST Transients and Variable stars Science Collaboration
Astronomy software Galaxy clusters Time domain astronomy Transient detection Variable stars
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY24
IISER Pune will contribute directable software development in the general area of astrophysical transients, focussing primarily on software development for follow up of host galaxies of transients. We will work with the Transient and Variable Stars (TVS) SC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. We anticipate needing significant amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. We expect sufficient our needs will be fulfilled by the local computing resources available at IISER Pune. IISER Pune hosts the PARAMBRAHMA cluster as part of the national supercomputer mission, additionally the PIs have access to appended data storage facilities. Our staff will engage early with any Rubin tutorials provided to gain expertise in handling Rubin specific challenges , and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the TVS SC. S1.
Updated: 2026-07-22
IND-ITI-S1
Science Pipeline Development in the LSST AGN Science Collaboration
Active galactic nuclei Astronomy software
Primary recipient: LSST AGN Science Collaboration
Additional recipients: None
Start (approx.): FY23
IIT Indore will contribute directable software development effort in the general area of LSST Active Galactic Nuclei science analysis, with contributions directed to the two working groups in AGN SC, viz., AGN Variability and Follow-up. IIT Indore staff will work with the AGN SC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code.We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at IIT Indore, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the IIT staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the AGN SC.
Updated: 2026-07-22
IND-ITI-S2
Science Pipeline Development in the LSST Galaxies Science Collaboration
Astronomy software Galaxies Galaxy clusters
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: None
Start (approx.): FY23
IIT Indore will contribute directable software development effort in the general area of LSST Galaxies science analysis, with contributions directed to the science areas involving Active Galactic Nuclei, high redshift galaxies and QSOs, clusters of galaxies (AGN feedback, multiwavelength data, Bayesian forward modeling), deep fields and large scale structures, as mentioned in the Galaxies SC roadmap. IIT Indore staff will work with the Galaxies SC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code.The development work will be embedded in the Galaxies SC. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at IIT Indore, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the IIT Indore staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the Galaxies SC.
Updated: 2026-07-22
IND-IUC-S1
Science Pipeline Development in the LSST Dark Energy Science Collaboration
Astronomy software Cosmology Galaxy clusters Gravitational lensing
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: LSST Strong Lensing Science Collaboration
Start (approx.): FY23
IUCAA will contribute directable software development effort in the general area of LSST Dark Energy science analysis, with contributions directed to the weak gravitational lensing working group (WG), optical galaxy clusters WG, and the strong gravitational lensing WG. IUCAA staff will work with the Dark Energy SC leadership to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. For work related to strong gravitational lensing, we will also consult the Strong Lensing SC to find synergy with Dark Energy SC.The development work will be embedded in the Dark Energy SC. The development will be carried out at DESC computing resources at NERSC to ensure that other Dark Energy SC members can engage effectively with the work while it is in progress. The primary risk associated with this work is in gaining the needed expertise in the Dark Energy SC tools and data products: to mitigate this, the IUCAA staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, as well as the Dark Energy SC “Data Challenges”.
Updated: 2026-07-22
IND-IUC-S2
Science Pipeline Development in the LSST Galaxies Science Collaboration
Astronomy software Galaxies
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: None
Start (approx.): FY23
IUCAA will contribute directable software development effort in the general area of LSST Galaxies science analysis, with contributions directed in the area of low surface brightness (as identified in the Galaxies science roadmap). IUCAA staff will work with the Galaxies SC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at IUCAA, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the IUCAA staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the Galaxies SC.
Updated: 2026-07-22
IND-IUC-S3
Science Pipeline Development in the LSST Transients and Variable stars Science Collaboration
Astronomy software Time domain astronomy Transient detection Variable stars
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY23
IUCAA will contribute directable software development effort in the general area of LSST Transient and Variable Stars science analysis, with contributions directed in the area of Galactic and Local Universe transients (as identified in the TVS science roadmap). IUCAA staff will work with the TVS SC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at IUCAA, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the IUCAA staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the Galaxies SC.
Updated: 2026-07-22
IND-NCR-S1
Science Pipeline Development in the LSST Galaxies Science Collaboration
Astronomy software Galaxies Photometric redshift
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY23
NCRA will contribute directable software development effort in the general area of LSST Galaxies science analysis, with contributions directed to the SED fitting and photometric redshift and Galaxy morphology working groups (WG) via well trained and supervised postdocs. NCRA staff will work with the Galaxies SC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code.The development work will be embedded in the Galaxies SC. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at NCRA and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the NCRA staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the Galaxies SC.
Updated: 2026-07-22
IND-TIF-S1
Science Pipeline Development in the LSST Dark Energy Science Collaboration
Active galactic nuclei Astronomy software Cosmology Galaxy clusters
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY23
TIFR will contribute directable software development effort in the general area of LSST Dark Energy science analysis, with contributions directed to the dark matter working group (WG), cosmological simulations WG, Theory and Joint Probes WG, and Clusters of Galaxies WG. TIFR staff will work with the Dark Energy SC leadership to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code.The development work will be embedded in the Dark Energy SC. The development will be carried out at DESC computing resources at NERSC to ensure that other Dark Energy SC members can engage effectively with the work while it is in progress. The primary risk associated with this work is in gaining the needed expertise in the Dark Energy SC tools and data products: to mitigate this, the TIFR staff will engage early with any Dark Energy SC/Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews” and the Dark Energy SC “Data Challenges”. Some of these contributions could also have relevance and synergy with the AGN SC and the Galaxies SC.
Updated: 2026-07-22
ISR-UST-S1
Joint ULTRASAT-LSST Transient Alerts
Time domain astronomy Transient detection
Primary recipient: Rubin Prompt Processing Group
Additional recipients: None
We propose a handshake mechanism whereby LSST alert brokers and the ULTRASAT alert generator ping a designated server on the collaborating side, providing coordinates and a time stamp, and receiving in return a formatted block that can be included or appended to an outgoing alert, with the information described above. Communication protocols will be set up between the relevant broker teams and the ULTRASAT Science Operations Center (SOC). The connection between ULTRASAT and the AMPEL broker (operated by ULTRASAT core team members at DESY) will be set up by the ULTRASAT team, ensuring at least one operational joint broker by resources included fully in this proposal. For other brokers, development effort needs to be undertaken on the broker side by the relevant broker teams, but the ULTRASAT team will assign additional resources to support development on the broker side with information and advice. As part of the periodic ULTRASAT data releases, ULTRASAT UV light curves will be connected with LSST events (either transients or static sources - e.g., for stellar flares). This will allow curators of LSST data to add the public ULTRASAT light curves to the aggregated information about these LSST sources.
Updated: 2026-07-22
ITA-INA-S10
Directable SW contribution for the SMWLV and TVS SCs: Software Tools for
Astronomy software Time domain astronomy Transient detection
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: LSST Stars Milky Way and Local Volume Science Collaboration, Rubin Crowded Field Coordination Group
Start (approx.): FY23
We propose to work within the Crowded Fields Working group, and in agreement with the SMWLV and TVS SCs, in the framework of Directable SW, to implement a series of tools focused to obtain accurate photometry in crowded fields. As a proposed example, we mention our experience in the P.B. Stetson’s ALLFRAME code, which simultaneously fits a master star list on a set of images, cross-correlating fluxes (in different passbands) and positions. This approach allows to enhance the accuracy of the photometry, especially at the faint end of the brightness range. We are available to test this approach and other approaches developed to deal with the LSST data, according to the directable nature of our proposed contribution. In general, we are keen to contribute with specific FTEs and our experience on this matter.The INAF proposers will work with the Rubin Team to define needed software development and tasks aimed at tailoring/integrating any existing product on the base of Rubin requirements or to implement specific tools from scratch, by following Rubin requests. They also carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the proposed tool. We anticipate needing modest amounts of local computing to support this work and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at INAF, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products, both for INAF team staff members and dedicated recruited personnel: to mitigate this, the INAF team will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the TVS and SMWLV SCs.
Updated: 2026-07-22
ITA-INA-S11
Directable SW contribution for the Solar System SC: Advanced active objects’ detection & characterization
Astronomy software Solar system astronomy
Primary recipient: LSST Solar System Science Collaboration
Additional recipients: None
Start (approx.): FY23
The INAF team will contribute directable software development effort in the general area of Rubin data reduction, focusing on the detection and advanced characterization of active objects. The INAF proposers will work within the context of the SSSC Community Software and Infrastructure Development working group and other relevant working groups, such as the Active Object working group, in order to define and develop the needed SW by tailoring/integrating any existing product on the base of Rubin requirements or by implementing new specific tools from scratch following Rubin requests. They will carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the entire collaboration, and supporting the collaboration’s members in the use of the proposed tool.We anticipate needing modest amounts of local computing to support this work and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at INAF and at Parthenope University, and we will work to secure additional local resources if needed.The primary risk associated with this work is in gaining the needed expertise to adapt the pipeline already at hand to LSST scale. As some of the proposers and the dedicated recruited personnel are not part of the SSSC yet, they will first need to be acquainted with the Rubin data products and build-in pipelines. In order to mitigate this problem, we plan to engage early with Rubin SW developers and look to be active participants in forthcoming Rubin “Data Previews” within the context of the SSSC.
Updated: 2026-07-22
ITA-INA-S12
Directable SW contribution for the SMWLV SC: Machine Learning tools for the characterization of stellar populations
Astronomy software Galaxy clusters Machine learning Spectroscopy Variable stars
Primary recipient: LSST Stars Milky Way and Local Volume Science Collaboration
Additional recipients: LSST Transients and Variable Stars Science Collaboration
Start (approx.): FY25
We propose to work closely with the SMWLV and TVS Science Collaborations, and in the framework of Directable software, to implement a series of tools focused at characterising stellar populations. Thanks to our extensive experience in the study of stellar populations through spectroscopy and photometry, we could in particular provide expertise in the development of tools aimed at at the derivation of photometric metallicities of field stars and of parameters of stellar clusters (e.g. age, metallicity, distance etc) from Rubin Observatory data. An endorsement request has been sent to the SMWLV and TVS SCs jointly with contribution S10. We have already obtained a positive response from both collaborations.The INAF proposers will work with the Rubin Team to define needed software development and tasks aimed at tailoring/integrating any existing product on the base of Rubin requirements or to implement specific tools from scratch, by following Rubin’s requests. The proposers intend to exploit their previous experience into the adaptation of the tool to specific Rubin project needs. They also carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the proposed tool. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at INAF, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products, both for INAF team staff members and dedicated recruited personnel: to mitigate this, the INAF team will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the SMWLV and TSV Science Collaboration.
Updated: 2026-07-22
ITA-INA-S13
Directable SW contribution for the [Galaxies] and [DE] SCs: Advanced tools for extragalactic photometry
Astronomy software
Primary recipient: Rubin Algorithms & Pipelines Team
Additional recipients: LSST Dark Energy Science Collaboration, LSST Galaxies Science Collaboration
Start (approx.): FY26
The INAF team will contribute directable software development effort in the general area of Rubin data science analysis and exploration, including advanced methods for photometric measurements of sky sources. The INAF proposers will work with the Rubin Team to define needed software development and tasks aimed at tailoring/integrating any existing product on the base of Rubin requirements or to implement specific tools from scratch, by following Rubin requests. They also carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the proposed tool. We anticipate needing modest amounts of local computing to support this work and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at INAF, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products, both for INAF team staff members and dedicated recruited personnel: to mitigate this, the INAF team will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the I&S SC.
Updated: 2026-07-22
ITA-INA-S14
Directable SW contribution for the
Astronomy software Cosmology Galaxy clusters
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY25
The INAF team will contribute directable software development effort in the general area of DESC Galaxy Clusters and Simulations working group, in Projects and areas that could also include the creation of an infrastructure to generate, store and make fully accessible to the LSST Collaboration simulations and mocks of the LSST survey, the characterization of optimal filter algorithms for the identification of galaxy clusters in LSST data, the development and validation of software for galaxy cluster mass modelling and scaling relations. The INAF proposers will work with the DESC Team to define needed software development and tasks aimed at tailoring/integrating any existing product on the base of DESC requirements or to implement specific tools from scratch, by following DESC requests and shared with the DESC in GitHub community repositories. They also carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the proposed tool. We anticipate needing local computing to support this work and focus on using DESC-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at INAF, and we will work to secure additional local resources if needed. The INAF proposers will actively work to ensure that all the developed software will also run smoothly at NERSC, DESC’s primary computing host.The primary risk associated with this work is in gaining the needed expertise in the DESC tools and data products, both for INAF team staff members and dedicated recruited personnel: to mitigate this, the INAF team will engage early with any DESC tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the DESC.
Updated: 2026-07-22
ITA-INA-S15
Tools for classification, full characterization and validation of variable sources
Astroinformatics Astronomy software Deep learning Machine learning Time domain astronomy Transient detection Variable stars
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY25
The INAF team will contribute directable software development effort, endorsed by Rubin Transients and Variable Stars (TVS), Science Collaboration (SC), in order to provide TVS with an architecture and specific tools for the identification, classification and validation of variable sources observed by the Rubin Observatory. This will include machine/deep learning methods for prediction/classification tasks, as well as tools for cross-matching with existing catalogues, analysis and validation of variable sources.Tools, pipelines and (python-written) procedures we developed in the context of the Variability Unit of the Gaia Data Processing and Analysis Consortium (DPAC) will be re-moduled and adapted for the analysis of the LSST multi-wavelength time series data and/or used to feed machine-learning (python-based) pipelines to validate the classification. The machine learning training set will be based on the vast and accurate training sets that we have developed along the years in the context of the Gaia mission, which will be progressively updated to account for the Rubin-LSST achievements. In parallel, the validation will take full advantage of the huge compilation of literature catalogues (including those produced by previous Gaia releases) which we have been building over the years and constantly update to validate the Gaia products. The proposers will collaborate with the Rubin Team to define needed software developments, to integrate/tailor existing software products or implement specific tools from scratch, based on the Rubin requirements and following Rubin requests. The activity will be carried out in strict collaboration with other members of the LSST TVS SC and taking into account the feedback from the rest of the collaboration. The tools will be developed in the same framework adopted by the Rubin TVS SC in order to ensure compatibility and ease of use and testing. To allow for an efficient development of the proposed software both the INAF team staff members and the dedicated recruited personnel will need to quickly become familiar with the Rubin tools and data products. To this end the INAF team will engage early with any tutorials provided by RO, and will actively participate in events of the TVS SC associated with the Rubin “Data Previews”.
Updated: 2026-07-22
ITA-INA-S2
Directable SW contribution for the AGN SC: Simulations of high-z AGNs and galaxies in the LSST survey
Active galactic nuclei Astroinformatics Astronomy software
Primary recipient: LSST AGN Science Collaboration
Additional recipients: None
Start (approx.): FY23
The INAF team will contribute to the AGN SC team with a directable software development effort. This contribution might also be relevant for the Galaxies SC. The aim is to help build an AGN mock catalog which will be used as input, together with the galaxy mock catalog, to simulate LSST images. The AGN mock catalog at the desired depth and with any chosen set of passbands, will be created using the state-of-the-art prescriptions that match observations of AGN in the deep fields. The goal is to create simulated LSST and Euclid FoVs by using GalSim (Rowe et al., 2015) or other tools defined by the SC. Photometric catalogues of sources (AGN and galaxies) will then be extracted from the simulated images in different bands and at different depths. We point out that fluxes will be measured on the simulated images using real photometric software tools, as opposed to being directly simulated in the mock catalog. The INAF proposers will work with the Rubin Team to define needed software development and tasks on the base of Rubin requirements or to implement specific tools, by following Rubin requests. They will also carry out those tasks as an integral part of the AGN science collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the proposed tool. This work has been weighed against the AGN SC Roadmap document and the criteria outlined in the proposer’s handbook and it has been accepted as a contribution by the AGN SC. Several AGN SC members (i.e. Niel Brandt, Gordon Richards, Jan-Torge Schindler and Franz Bauer) have declared interest and will be involved in the project.We anticipate needing modest amounts of local computing to support this work and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The local computing resources are already available at INAF, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products, both for INAF team staff members and dedicated recruited personnel: to mitigate this, the INAF team will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews” within the context of the AGN SC.
Updated: 2026-07-22
ITA-INA-S23
Staff effort in support of Rubin commissioning: ML tools for instrumental monitoring and analysis
Astronomy software Deep learning Machine learning
Primary recipient: Rubin Commissioning Team
Additional recipients: None
Start (approx.): FY22
The INAF-OACN team will contribute directable software development effort in the general area of LSST focal plane instrument HouseKeeping/telemetry and science analysis, including machine/deep learning methods for prediction/classification tasks, as well as trend analysis and statistical characterization of focal plane instrument and science data/images systems. By considering that a general-purpose version of the proposed system is already in place and a customized version was adopted by ESA Euclid Mission, the proposers intend to exploit their previous experience into the adaptation of the tool to specific LSST project needs. The INAF-OACN proposers will work with the LSST Commissioning Team to define needed software development and tasks aimed at tailoring/integrating the existing product on the base of LSST requirements. In fact, this activity can be activated in a very short time, due to the already available software system on which to work. They also carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration members in the use of the proposed tool. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at INAF-OACN, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products, both for INAF-OACN team staff members and dedicated recruited personnel: to mitigate this, the INAF-OACN team will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the I&S SC.More technical and functional information on the prototype system offered is available here: https://drive.google.com/drive/folders/1iXAoA8OS9G1Srl7erVu9zQ-EdWVm5Rkj?usp=sharing
Updated: 2026-07-22
ITA-INA-S25
Non-Directable SW contribution for the [MWLW] SC: Population models of the LSST stellar content
Astroinformatics Astronomy software Variable stars
Primary recipient: LSST Stars Milky Way and Local Volume Science Collaboration
Additional recipients: None
Start (approx.): FY18
We will perform large-scale simulations of the stellar content of LSST, based on the latest version of the TRILEGAL population synthesis code. Each simulation is a big catalog of stellar fundamental parameters (masses, ages, metallicities, radii, coordinates, distance, extinction, proper motions, etc), together with photometry in LSST and Gaia filters, for ~19e9 stars in the Milky Way and Magellanic Clouds, down to the r~27.5 mag limit of stacked LSST images.- A first version of these simulations was used to support two Cadence Optimization white papers and the case for developing static crowded field photometry in the context of the SMWLV Science Collaboration. It was partially made available in the NOAO/ASTRO Data Lab in 2019.- A second version of the simulation, significantly more complete and including more information about variability and binaries, is now being finalised. Its density maps were already incorporated in MAF (lsst_sims tag sims_w_2020_05) as an alternative to previous star count models derived from the Galfast code. - We will provide at least 3 other releases of the simulations, in the 2001-2026 period, with complete versions being uploaded to NOIR Data Lab, and 'summary maps' (e.g., stellar densities as a function of color-magnitude and for different sub-samples of stars) being added to MAF and to any other LSST software where it might become useful. Every new release will take into account improved calibrations of the model parameters coming from many ongoing surveys and later from LSST data itself.- We will keep a database of python notebooks and a helpdesk to help the LSST community to use these simulations for any other goals.- From 2021 on, releases will include additional, newly simulated data: light curves for variables such as Cepheids and RR Lyrae, long period variables (LPVs), and eclipsing binaries, more detailed treatment of interstellar+circumstellar dust, extended non-adiabatic pulsation models (linear and non-linear, in 5 modes) for LPVs and semiregulars.- Other ongoing/planned improvements and tools may be provided on a best-effort basis, like for instance stellar models with a detailed treatment of interstellar+circumstellar dust and fast rotation, tools to identify the best-fit parameters of Milky Way models (in collaboration with the Brazilian team at Linea, who is submitting a separated in-kind request), the space-resolved star-formation history of nearby galaxies, etc. This is a non-directable in-kind contribution endorsed by the SMWLV Collaboration. S25
Updated: 2026-07-22
ITA-INA-S26
Non-Directable SW contribution for the TVS SC: A Bridge from Gamma to Optical
Astroinformatics Astronomy software Time domain astronomy Transient detection
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: LSST Stars Milky Way and Local Volume Science Collaboration
Start (approx.): FY26
The Italian National Institute for Astrophysics (INAF) and the Space Science Data Center of the Italian Space Agency (SSDC-ASI) teams will contribute non-directable software development effort in the specific area of LSST TVS analysis in a multi-frequency and multi-messenger context to allow the maximum exploitation of the astrophysical information contained in the data in a high-energy and very-high- energy field. The INAF and SSDC-ASI team proposes to systematically analyze LSST data looking for time resolved optical counterparts of high energy and very high energy sources present in catalogue of, or triggered by, X-ray and gamma-ray satellites or Cherenkov telescopes, including low confidence alerts. Validated results, cross-matched with catalogues hosted and managed by SSDC, will be immediately available to the full LSST community, in a multiwavelength context and remotely accessible through SSDC, for the early scientific exploitation. This project is well in line with similar initiatives undertaken for space missions and for Cherenkov Telescopes already carried on at SSDC within the framework of the general agreement between ASI and INAF for carrying on scientific and technical activities in the center. The computing infrastructure to be dedicated to this project will be provided by both INAF (ASTRI Data Center) and SSDC. The service will be articulated in four different phases: 1) the selection of an input catalog of high energy sources of interest; 2) LSST data retrieving and processing; 3) Multiwavelength analysis of the data; 4) Publishing results. The project will be active during the whole LSST survey. Computing resources are already available at INAF/SSDC, and we will work to secure additional local resources if needed. INAF will also provide a dedicated postdoc grant to the project.The TVS SC and SWMLV SC have endorsed this proposed contribution.
Updated: 2026-07-22
ITA-INA-S3
Directable SW contribution for the TVS SC: Development of a software to classify variable stars
Astroinformatics Astronomy software Time domain astronomy Transient detection Variable stars
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY25
The INAF team will provide directable software development effort in the area of Rubin data science analysis and classification of stellar variability, contributing to user-support projects to benefit a diverse range of science of interest for the TVS SC. Software effort to help TVS members transfer their data reduction to the Science Platform, will be provided, particularly for TVS members studying variable stars.For example, a potential project could include large catalog queries on the annual data release products, comparing the classifications provided by different brokers in order to compile verified variable stars catalogs.The proposers will make available their expertise in young stellar object variability phenomena in the framework of classification of stellar variability, and the final project will be developed in collaboration with TVS.Details describing the TVS software requirements concerning this science have been discussed in several Sections of the TVS. In particular, Sect. 2.4.1 and Sect. 3.3.5 (Giannini, Bonito & Antoniucci) describe the software requirements and possible follow-up observations to study YSOs with erupting accretion bursts (e.g. EXOrs objects), while 5.2.7 (Bonito) is focused on the variability due to quiescent accretion in YSOs in general discussing the necessary software and synergy with different multi-band facilities to accomplish the characterisation of variability for young stars.The INAF proposers will work with the Rubin TVS SC, reporting regularly on progress, taking input from the SC, and supporting the collaboration’s members in the use of the proposed tool. We anticipate needing modest amounts of local computing to support this work and focus on using Rubin-provided user computing resources as they become. The aforementioned local computing resources are already available at INAF, and we will apply for additional international resources if needed, as made since more than a decade for numerical simulations. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products, both for INAF team staff members and dedicated recruited personnel: to mitigate this, the INAF team will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”.Both proposers are members of the Stack Club, (Bonito is the Chair of the TVS Task Force on the Rubin Science Platform Evaluation).
Updated: 2026-07-22
ITA-INA-S5
Directable SW contribution for the Stars, Milky Way & Local Volume SC: Software for the measure of the optical fluxes from galactic diffuse medium
Astronomy software Variable stars
Primary recipient: LSST Stars Milky Way and Local Volume Science Collaboration
Additional recipients: None
Start (approx.): FY26
The INAF team will contribute directable software development effort in the general area of Rubin data reduction, analysis and exploration, including diffuse nebulae photometry optimization, to be prioritized and planned via mutual agreement based on the needs of the Stars, Milky Way & Local Volume Science Collaboration. An endorsement has been obtained from the SMWLV Science Collaboration. The INAF proposers will work with the Rubin Team to define needed software development and tasks aimed at tailoring/integrating any existing product on the base of Rubin requirements or to implement specific tools from scratch, by following Rubin requests. They also carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the proposed tool. We anticipate needing modest amounts of local computing to support this work and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at INAF, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products, both for INAF team staff members and dedicated recruited personnel: to mitigate this, the INAF team will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the SMWLV SC.
Updated: 2026-07-22
ITA-INA-S6
Directable SW contribution for the Galaxies SC: Tools for the measurement of surface brightness fluctuations on LSST data
Astroinformatics Astronomy software Galaxies Galaxy clusters
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: None
Start (approx.): FY25
Our team will contribute directable software development effort in the general area of Rubin data science analysis and exploration, with a focus on the measurement of SBF. We will work with the Galaxies SC to better identify the needed software development tasks, and then carry out those tasks as an integral part of the collaboration. A key characteristic of any deliverable for our contribute will be the automation, because of the large number of potential targets (any relatively smooth galaxy within ~100Mpc), and of the lengthy and complex procedures to measure SBF.The software efforts will be oriented toward (some of) the following contributes: A detection filter for identifying suitable targets for SBF measurement; A fast and automated procedure to model the brightness profiles of extended galaxies; Tools for automated treating all sources contaminating the SBF signal: dust, foreground stars, background galaxies, globular clusters host in the target galaxy;Automated analysis of the power-spectrum residual frame for the final measure of SBF; Validating the SBF distance estimates on test data (real/simulations);Running the measurement on the data releases, delivery of catalogs to the collaboration, preparing data for the public release.The areas of interest delineated above cover most of the needs for SBF measurement assuming that the tools for deriving some of the other key quantities (e.g. galaxy colors, PSF models, etc.) will be available from Rubin's data management, or other science collaborations. However, if needed, our team could participate in validating or developing such tools. The primary risk associated with this work is in the quality of the SBF signal: any geometric correlation between pixels introduced during the data reduction stage might badly affect the SBF. Hence, we consider of key importance an early testing stage on data processed with a reduction pipeline similar to the one to be used for the LSST (e.g. HSC-SSP data), or on simulated images. A second risk is the automation of the procedures, which we foresee will require to choose where to place the compromise between quality and quantity (many unsupervised measurements vs less supervised ones). To mitigate these risks, the team will engage early with the DM team to include the SBF detection in the standard measurement pipeline (assuming it is fast enough).We anticipate needing modest amounts of local computing to support this work, during the first stages of the project, in part already available. Other resources will be acquired via national or local funding.
Updated: 2026-07-22
ITA-INA-S8
Tools for the simulation of Pulsating Stars
Astronomy software Machine learning Time domain astronomy Transient detection Variable stars
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY23
Our team will contribute directable software development effort (endorsed by TVS) in the general area of Rubin data science analysis and exploration, with a focus on the development of an infrastructure based on extended model sets along with software tools to interpolate among grids of theoretical templates (e.g. light and radial velocity curves, perios, mean magnitudes and colors etc..…) for pulsating variables. We will work with the TVS SC to better identify the needed software, the interconnectivity with other TVS tools and brokers and then carry out those tasks as an integral part of the collaboration in order to achieve these two fundamental aims:to train the developed tools and infrastructure on the extended and detailed model grids for several classes of pulsating stars built by our team;to extend the same tools and infrastructure to theoretical LSST pulsating stars templates developed by other teams and under the supervision of the TVS Scientific Collaboration.The development of general purpose modeling tools for variable star light-curves and the associated infrastructure will rely on our group’s acknowledged expertise in several classes of pulsating stars, but the work will be closely embedded in the TVS Scientific Collaboration to ensure the general applicability of the resulting software.Moreover, the simulation of LSST pulsating stars of various classes will be useful for classification and characterization purposes in the context of the TVS Scientific Collaboration, including training machine learning classification systems.The importance and the necessity of these types of models and software tools for the future analysis of the LSST data for pulsating stars in different Galactic and extragalactic environments are also described in the TVS Roadmap in the Section 'Transients and variables of the Galactic and Local Intrinsic Universe'.
Updated: 2026-07-22
ITA-INA-S9
Directable SW contribution for the Galaxy and Strong Lensing SC and Data management: Structural parameters with Machine learning
Astronomy software Galaxies Gravitational lensing Machine learning
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: LSST Strong Lensing Science Collaboration
Start (approx.): FY23
The INAF team, located at the Osservatorio Astronomico di Capodimonte in Napoli, proposes to develop a software to derive galaxy structural parameters and galaxy-subtracted images using CNN techniques from Rubin observations. This process aims at complementing the ongoing effort of the Data Management (DM) division of the Rubin Observatory to derive single Sérsic fitting of galaxies and expand this to multi-band and multi-component analyses in a fast and efficient way, contributing to the process of deblending sources and star/galaxy separation. The production of galaxy-subtracted images will be implemented within the LSST strong lensing pipeline.The INAF proposers will work with the Rubin Team to define needed software development and tasks aimed at tailoring/integrating any existing product on the base of Rubin requirements or to implement specific tools from scratch, by following Rubin requests. They also carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the proposed tool. We anticipate needing modest amounts of local computing to support this work and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at INAF, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products, both for INAF team staff members and dedicated recruited personnel: to mitigate this, the INAF team will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the Galaxy and Strong Lensing Science Collaboration (GSC an SLSC) and DM.
Updated: 2026-07-22
JAP-JPG-S3
Serving Rubin Science Platform (Development and Support)
Astronomy software Data visualization
Primary recipient: Rubin SQuaRE Team
Additional recipients: Rubin Community Science Team
Start (approx.): FY22
In this section, we describe human resources for operation and development of RSP. The hardware resources for RSP are proposed as part of the computing facility for the Lite IDAC, which is described in Section 4.If selected, NAOJ would secure 2 individuals at a 0.5 FTE level each to support RSP (one for 4 years, and the other for 13 years). One is a software engineer who is experienced with deployment of data analysis environments using a combination of a container technology and a Jupyter-based interface over a Kubernetes-based distributed computing system. This individual would contribute, for 4 years, some in development of tools for user support such as a web application with expertise obtained through the ongoing HSC-SSP, as well as deployment of the RSP software suite. The other one is a scientist who will serve throughout 13 years of the survey period as user support to bridge LSST users and NAOJ local support staff. As recommended in the Feedback letter, these two staff would be associated with the Rubin Community Engagement team, and taking functional direction from CE team leadership, while being able to interact well with the SPaRE team[i] that will be evolving and maintaining the Rubin Science Platform. In addition, efforts for software development by the above engineer is supposed to follow a collaborative framework of “General pool of fully directable effort” guided in the Handbook, so that his/her contribution time is fully considered for requesting LSST data rights. Those staff would cooperate with the local support staff under the supervision of the same leading person for the Lite IDAC. The computing system and software would be designed to serve moderate result set support (50 simultaneous access, visualization for 10 million objects and result sets of up to 0.1GB, or different requirements that would be suggested by CEC in the evaluation onwards) as defined in the guideline (https://ldm-554.lsst.io/). Since we will host public data products from HSC-SSP and the upcoming PFS survey in neighboring systems in NAOJ, we would discuss an efficient way to provide access to those products for synergistic work combining those data sets with LSST data.
Updated: 2026-07-22
JAP-JPG-S7
Software for calibrating the covariance matrix for large-scale structure probes
Astronomy software Cosmology Galaxy clusters Gravitational lensing
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY21
The JPG covariance team led by Masahiro Takada (Kavli IPMU) wants to contribute non-directable software development effort in the specific area of covariance work for large-scale structure probes (weak lensing and galaxy clustering) in the DESC science cases, in close collaboration with the Theory and Joint Probes (TJP) working group of DESC collaboration. The JPG team will run cosmological N-body simulations (especially the so-called separate universe simulations) and develop the emulator package/tools allowing for computation of the response functions for matter-matter, matter-galaxy and galaxy-galaxy correlation functions for an input set of parameters (cosmology, halo occupation distribution, separations and redshift), which can be used to calibrate the super-sample covariance contribution of LSS clustering observables. The JPG covariance developers will work closely with the DESC TJP working group in this software development task, carrying out the work as an integral part of the collaboration, reporting regularly on progress, taking inputs from the rest of the collaboration, and supporting the collaboration’s members in the use of the emulator code/tools. We will use in-house computer resources at Kavli IPMU ,and/or super-computing resources at National Astronomical Observatory of Japan to which the JPG covariance team members have access, to run needing cosmological N-body simulations and develop the code/emulator tools. The JPG covariance team will engage with the DESC TJP tasks/collaboration as soon as possible, once this proposal is approved. We will provide the emulator package/tools in the format specified by the DESC TJP collaboration. The representative of JPG covariance team, Masahiro Takada, has been discussing with DESC TJP co-chairs on this proposed contribution, and we will define specific tasks/work packages of the proposed contributions so that the contribution is smoothly integrated with the existing efforts and software. DESC endorses this contribution, 'Software for calibrating the covariance matrix for large-scale structure probes'.
Updated: 2026-07-22
JAP-JPG-S8
ML deblending algorithm with ground- and space-based images
Astroinformatics Astronomy software Cosmology Deep learning Gravitational lensing Machine learning
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY21
The JPG deblending team led by Hironao Miyatake will contribute non-directable software development effort in the object deblending of Rubin images primarily for reducing systematics in weak lensing measurement and in associated infrastructure works. Our team will develop a machine-learning (ML) based deblending algorithm, using pairs of ground-based and space-based telescope images as a training set, which enables to deblend objects observed by a ground-based telescope alone. We will develop the algorithm using the HSC and Hubble Space Telescope (HST) images and apply the algorithm to the HSC and early LSST data. This software development is a pathfinder for a longer-term joint processing effort when the Nancy Grace Roman Space Telescope comes online. We are currently at the initial stage of the algorithm development. Before obtaining proofs of concept, this development should be counted as research rather than a part of our in-kind contribution.Through this development, we will contribute to the infrastructure work on BTK, which will benefit other groups within the DESC BLWG. Our contribution includes adding capability to simulate pairs of high-resolution and low-resolution realistic galaxy images based on, e.g., real galaxy images from the COSMOS HST data and ML-based generative images (Lanusse et al., arXiv:2008.03833), which is used to validate our deblending algorithm. Through this process, we will validate the completeness of COSMOS input catalog and enhance the COSMOS catalog with the ML-based generative images, which should benefit other DESC projects relying on the COSMOS catalog. Once initial proofs of concept for the deblender are successful, later stages of the algorithm development could be part of this in-kind contribution pending agreement from DESC that this would be a valued infrastructure contribution. We already have GPU machines in Nagoya University used for training deep learning models and have enough funding to purchase additional GPU machines if necessary. We will make sure our deblending algorithm runs on NERSC computers and will run deblending on the HSC and early LSST data within NERSC. A possible major risk is to identify an appropriate ML algorithm for deblending. To lower this risk, we already identified expert consultants at Institute of Statistical Mathematics (ISM) and Nippon Telegraph and Telephone Corporation (NTT) in Japan. We will also consult with ML experts within DESC and the Informatics and Statistics Science Collaboration (ISSC), which ensures this work is well-embedded within DESC and Rubin Observatory.DESC endorses this contribution, with LOI code JAP-JAP-4.
Updated: 2026-07-22
JAP-JPG-S9
Directable effort in the SL working group
Astronomy software Cosmology Gravitational lensing
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: LSST Strong Lensing Science Collaboration
Start (approx.): FY22
The JPG strong lensing team led by Masamune Oguri will contribute directable software development effort in the general area of LSST Strong Lensing science analysis. The possible effort includes, but not limited to, contribution to the end-to-end simulations of various types of strong lens systems to characterize the selection function in observations and contribution to strong lens finding tools. The team will work closely with the leadership of DESC SL WG and SLSC to define needed software tasks, and then carry out those tasks as an integral part of the collaboration in the DESC GitHub organization, taking inputs from DESC SL WG and SLSC members and reporting the progress regularly. The work will be carried out within DESC Projects as per the DESC Publication Policy. The team will use DESC tools and tutorials in the initial learning phase to ensure that softwares developed by the team will be smoothly connected with other software efforts in DESC. We anticipate that the effort will require modest amounts of computing resources, which are already available at University of Tokyo and NAOJ, although the team will also use NERSC to ensure broader collaboration engagement. This proposed contribution was developed in consultation with DESC.
Updated: 2026-07-22
MEX-UNA-S1
Science Pipeline Development in the LSST SL AND DE Science Collaboration (Joint)
Astronomy software Gravitational lensing Strong gravitational lensing
Primary recipient: LSST Strong Lensing Science Collaboration
Additional recipients: LSST Dark Energy Science Collaboration
Start (approx.): FY22
MEX-UNA subgroup will contribute directable software development effort to SLSC-DESC jointly, with some focus on dark matter science cases whenever possible. Contributions towards the DESC External Synergies and Dark Matter Analysis WGs are also of our interest. The staff will work with SLSC-DESC to define needed software development tasks, and carry them conjointly with the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and so on. We anticipate the use of local computing resources, which are already available at the University of Guanajuato and UNAM, and we will work to increase local resources if needed. It is worth mentioning that the MEX-UNA group is also proposing a lite IDAC, which could also be hosting SL data if there is interest or need for it. In addition. for the DESC related work will make use of NERSC, DESC primary computing center, in order to efficiently work in a collaborative manner with other DESC members, and we make sure all developed code runs correctly. Regarding code/software development, we will involve at least two other staff members, one at UNAM and one at UG (to be identified), who are software engineers, that will provide support to the core group. The group will have to develop some of the needed expertise, with the time frame depending on the tasks assigned. To minimize the learning time process, the staff will be actively participating in the SLSC-SCSC activities as early as possible, and will take advantage of DESC and SCSL existing documentation, tools and tutorials. Also, the group will be providing the effort in a progresive way, being the least amount of effort in the first year and increasing it in subsequent years. Activities such as validating, documenting or optimizing existing pieces of software within a broader development team are suitable for the early stages, while well-defined software products could be envisioned for later stages. Finally to engage within DESC and SLSC the team will join the regular telecoms and activities of the SCs as well as to participate actively in all their activities, and make use of their communication tools as well.
Updated: 2026-07-22
MEX-UNA-S2
Science Pipeline Development in the DESC Science Collaboration
Astronomy software Cosmology Photometric redshift
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY22
This MEX-UNA subgroup will contribute directable effort to code/software development embedded in LSST DESC, with emphasis on the Photometric Redshifts (Photo-z) and Theory and Joint Probes (TJP) analysis groups. This group will work with the SC to define the needed software development tasks, and carry them out as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and so on.There is particular interest to contribute with tasks regarding covariance matrices, the development of CCL to compute observables in cosmology, the likelihood pipelines for joint analyses, the DESC single-probe LSS likelihood module, and the pipelines to test models beyond wCDM.This group has access to modest local computing resources already available at the researchers institutions, CINVESTAV and UNAM, which will support the majority of this work. The members of this group have also access to grants and funding to expand some of such resources as the project develops. In addition, we will make use of NERSC, DESC primary computing center, in order to efficiently work in a collaborative manner with other DESC members and verify that all developed codes run correctly. The main risk concerning this proposal is acquiring the expertise needed with the tools and products already in place. To mitigate this, the group will engage early with DESC, looking to be active participants in all the events, and will take advantage of DESC and SCSL existing documentation, tools and tutorials, as well as to join the regular telecoms and make use of their communication tools.
Updated: 2026-07-22
MEX-UNA-S3
Non-directable Science Pipeline Development in the LSST DE Science Collaboration
Astronomy software Cosmology
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY22
This MEX-UNA subgroup is seeking to contribute a non-directable software development effort to be embedded within DESC. The aim of this proposal is to develop a three point statistics pipeline, whose Software Development Priority will contain the following coding efforts: a) an algorithm to extract the signal from data, b) a prescription to estimate its associated error and c) the modelling of the signal. The first stage of the project is to choose and design an algorithm that would most benefit the LSST science, primarily steered by the TJP WG but also in close coordination with the LSS and WL WGs. At the moment, we envision two possibilities: either a configuration space three point correlation function, perhaps, using a multipole decomposition or its fourier space counterpart, the bispectrum, using spin-weighted spherical harmonics. Depending on the target space and other considerations, the error estimation may be done using semi-analytical approaches or re-sampling methods, and to model the signal, we can use our experience using recent developments in EFT-perturbation theory with a consistent biasing model. However, a more detailed study of the benefits, challenges and scientific goals of the two possibilities should be carried on and detailed in a document, which may also prove useful for further developments to the higher statistics pipeline. During this short design phase we will also assess the computational cost, integration into pre-existing codes and pipelines within DESC. Once the decision has been made in agreement with the relevant DESC Working Groups, we plan to spend most of the promised FTE time working in the three lines of software development described above until their completion, with the corresponding documentation in agreement with the collaboration guidelines. A further phase of enhancements can also take place where one may think of general improvements and model extensions. Long-term maintenance will be provided by the contributors of this proposal and according to the requirements of the recipient working groups.DESC endorses this proposed contribution, MEX-UNA-S3.
Updated: 2026-07-22
MEX-UNA-S4
Science Pipeline Development in the SMWLV Science Collaboration
Astronomy software Galaxy clusters Variable stars
Primary recipient: LSST Stars Milky Way and Local Volume Science Collaboration
Additional recipients: None
Start (approx.): FY22
This MEX-UNA subgroup will contribute with directable effort on software development in the general area of LSST SMWLV. The staff will work with the SMWLV SC to define needed software development tasks, and then carry out such tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. We have a particular interest in dense regions like the central MW, or stellar clusters, dwarf galaxies and the solar neighborhood.We have local computing resources already available at UNAM, and we will work to secure additional local resources if needed. In parallel, our group is proposing a Lite IDAC and the related resources may be applied to this particular project. As the project progresses we might use resources provided by the SC, and make sure all code/software developed runs in their main computing centers. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, UNAM staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the SMWLV SC.
Updated: 2026-07-22
MEX-UNA-S5
Science Pipeline Development in the Galaxies Science Collaboration
Astronomy software Galaxies Machine learning
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: None
Start (approx.): FY22
The MEX-UNA subgrup will provide a non-directable effort to the LSST Galaxies SC in software development, with emphasis on morphological classification (and eventually LSB) through the image analysis and Machine Learning algorithms. The group has enough local computing support at IA-UNAM to develop this work, but as the scale of the products work it might be necessary to use other SC resources, and we will make sure that codes/software run in the main SC computing center.This proposal is divided in two main sections:1- The automatic morphological classification of galaxies and the detection of independent morphological structures like bars, rings, mergers of galaxies, etc. After applying an adequate image processing following the techniques in Hernandez-Toledo et al. (2010), and in combination with supervised/unsupervised CNN-based models (e.g. Alvarado-Gonzalez et al. 2021), we will provide computational tools able to extract, almost in real time, these structures, additionally to the morphological type of these galaxies, for the corresponding analysis by the scientific community.2- The detection and classification of LSB structures, focusing mainly on tidal debris. This project will be a continuation of Project 1, and will be carried out according to the needs of the WG and the availability of deep images. Once the development of Machine Learning algorithms, to detect specific structures of galaxies, is done, they could be applied to detect tidal arms, tidal bridges and other structures within the image and magnitudes limits. The results reached and software developed will be available entirely to the collaboration, to use them with different scientific purposes, and also to carry out improvements after comparisons with other groups, working with the same interests but using different techniques. We would also be interested in applying the described techniques towards synergetic efforts with other SCs, like SLSC.We will be happy to extend our collaboration to other projects and share our experience if that is of benefit to the Galaxies SC. The Galaxies SC have endorsed this proposed contribution.
Updated: 2026-07-22
NED-UTR-S2
Science Pipeline Development for astrophysical systematics for the LSST DESC Science Collaboration
Astronomy software Cosmology Gravitational lensing
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY22
Chisari’s group will commit 1 FTE-yr non-directable effort towards DESC software pipelines: continuing the development of CCL, ensuring smooth integration to the combined-probes likelihood pipeline, and assessing and providing models for astrophysical systematics (mainly intrinsic alignments) for the successful extraction of cosmological information from weak gravitational lensing with LSST, in the spirit of the DESC Science Roadmap[2] (Chapter 5). Implementation of new intrinsic alignment models in CCL. Currently, CCL incorporates the NLA & standard perturbation theory models (up to one-loop) of intrinsic alignments. Neither can describe the smallest scale alignments, where most of the dark energy information is encoded. The EFT approach we proposed in Vlah, Chisari & Schmidt (2020) incorporates all possible physical contributions to the alignment signal to third order. The modelling on fully nonlinear scales can only be tackled via the halo model, which we have refined in Fortuna et al. (incl. Chisari, 2020) based on recent KiloDegree Survey observations (Georgiou et al., 2019a and 2019b, incl. Chisari). We will implement these models in CCL and perform various validations against our previous results following standard DESC procedure as documented in the CCL paper (Chisari et al., LSST DESC, 2019). Definition of mitigation strategy for LSST. The Theory and Joint Probes (TJP) working group is at the moment constructing the likelihood pipeline for inference of cosmological parameters (“Firecrown”) and an official forecasting code (“Augur”) aimed to carry out assessment of the impact of systematics and modelling choices. Following similar procedure as in the DESC science requirements document, we will use these LSST DESC forecasting and likelihood tools to determine expected cosmological parameter biases in Ωm, σ8, w0, wa depending on the model adopted, knowledge of priors, and the scales utilized for the analysis. We will also work with the collaboration in determining the trade-off with other systematics parameters. The aim will be to demonstrate the robustness of cosmological analyses with LSST.We anticipate the need to make use of the DESC NERSC allocation for these projects, though the usage will in general be minimal compared to the typical investment of the allocation (i.e. no simulations or data processing are needed within our activities). We will report on progress regularly at TJP telecons and collaboration meetings, and invite collaboration through sprint activities.Due to funding limitations (see 2.4.1), we envisage the effort to be non-directable. Nevertheless, we will take into account CCL development status and priorities, and seek feedback from the working group to ensure the contribution is timely and meaningful. Other areas where we can contribute and which have been discussed with LSST DESC leads are: the modelling of baryonic physics and general maintenance of TJP pipelines.The LSST DESC has endorsed this contribution.
Updated: 2026-07-22
NED-UTR-S3
Science Pipeline Development in the crowded field photometry coordination group
Astronomy software Stellar photometry
Primary recipient: Rubin Crowded Field Coordination Group
Additional recipients: Rubin Algorithms & Pipelines Team
Start (approx.): FY22
We will contribute directable software development effort in the area of crowded field photometry. We will work with the crowded field photometry coordination group and the Rubin Algorithms & Pipelines Team to define needed software development tasks , and then carry out those tasks as an integral part of the coordination group, reporting regularly on progress, taking input from the rest of the coordination group and supporting the coordination of group members where we can. We will coordinate with the Rubin Algorithms & Pipelines Team to make sure that the proposed algorithms meet their speed and robustness requirements.
Updated: 2026-07-22
NED-UTR-S5
Construction and maintenance of AGN catalogs to enable early science with LSST alerts
Active galactic nuclei Astroinformatics Astronomy software Supernovae Time domain astronomy Transient detection
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: NOIRLab CSDC
Start (approx.): FY22
We will provide contributed datasets and non-directable software development in the area of AGN identification. The first deliverable is a catalog, which will be ready by the start of transient alert science operations (i.e., when sufficient reference images have been constructed, which are needed to extract alerts from the difference image). Our deadline is much earlier compared to the timeline of catalog production by the AGN SC. This faster timescale is motivated by the needs of TVS to have a catalog of known AGN ready as soon as the stream of alerts starts in earnest. This means this first catalog will be constructed from non-LSST data products. We will work closely with Rubin Observatory staff to embed the catalog into the collaboration infrastructure for alert filtering. The catalog will be made available to all members of the LSST collaboration by incorporating this into NOIRLab. We will advertise and distribute the catalog to the LSST brokers, focusing first on the brokers that most directly serve the US and Chile communities (i.e., ANTARES, ALeRCE). The TVS collaboration has reviewed and endorsed this proposal and requested that we start the process of broker integration as soon as possible (with a prototype catalog). The TVS collaboration acknowledges that this proposed in-kind contribution could “serve as a blueprint for future catalogs and their integration in the discovery of new transients”. During the first year of Rubin alert operations, we will update the known AGN catalog by including Rubin observations from the year prior. At this point, we will have access to time series data from Rubin LSST, which allows us to select AGN based on their variability in LSST data. We will write software that can identify low-level AGN variability in the difference images, using a model that simultaneously fits for variability in all filters. This will yield a valued-added catalog of variability-selected AGN. This effort is complementary to the planned activities of the AGN SC as listed in their Roadmap (and confirmed via recent conversations with active members of the group). The AGN SC current priority is a more theoretical approach (compiling “ground-truth samples”), and is generally focussed on the Deep Drilling fields and measurements based on the total flux. In contrast, this proposed in-kind contribution has a more compressed timeline, is focussed on the full-sky and uses the difference image flux. The AGN SC is aware of this proposal but saw no need for formal endorsement because the science application of the deliverables is strongly geared for the TVS collaboration. However, we will of course coordinate closely with the AGN SC, making sure the lessons learned from our early catalogs are shared. Their in-kind contribution coordinator (Sebastian Hoenig) noted that “Coordinating on the variability selection would absolutely be welcome and appreciated”. The need for early AGN catalogs cannot be overstated, but is often overlooked, which is exactly why we believe this proposed in-kind contribution will be very helpful to increase the (early) scientific output from Rubin Observatory. The need for this catalog is often overlooked because current optical transients surveys (e.g., ASASSN, ZTF) are finding events in much brighter galaxies at lower redshift compared to what will be the yield of LSST. These low-redshifts make AGN identification relatively easy. This might have led to a false sense of security on the efficiency of machine-learning based classifiers for LSST transients (eg, AGN variability was not included in the first set of simulations of the Rubin Observatory transient sky in the PLAsTiCC classification challenge). For the fainter galaxies that dominante the LSST alerts, AGN selection will be more challenging compared to our experience with current surveys. In addition, at the larger distance of LSST alerts, separating AGN flares from off-nuclear events (e.g., supernovae) is also more challenging because the former subtend a larger fraction of the galaxy. By building the best-possible AGN catalog and making this available before the alert stream gets up to full speed, we will avoid a scramble of duplicate efforts from TVS members. The TVS has endorsed this contribution.
Updated: 2026-07-22
POL-NCB-S2
Near-Term Directable computing infrastructure effort for Dark Energy Science Collaboration providing a link between
Astronomy software Cosmology
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY21
NCBJ will contribute directable computing infrastructure effort in the general area of DESC science analysis, in particular science pipelines. NCBJ will work with the DESC SC to define needed computing infrastructure development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. At this point NCBJ anticipates that the main task will revolve around 1/ collaboration with DESC group on a distributed infrastructure, primarily targeted at NERSC; development of this common infrastructure, developed via a work plan in consultation with DESC leadership and would be the primary outcome. The Centre intends to achieve integration with DESC collaborative software efforts using DESC tools and tutorials, enabling the infrastructure to be used for DESC Data Challenges as well as Rubin Data Previews. All code that will be produced will be shared in DESC Community GitHub repositories. A by-product of this collaboration will be also development connected to the local infrastructure: 2/ integration of local computing resources (CIŚ) with DESC computation scheme through local IDAC and using local data resources, NCBJ provided IDAC, for the purpose of DESC group, 3/ integration of DESC science pipeline working at the National Energy Research Scientific Computing Center (NERSC) with local resources 4/ providing aid to the members of the DESC group using IDAC located at NCBJ. NCBJ will provide computational resources for (2-4) tasks. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the NCBJ staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the DESC SC.If selected, NCBJ would secure funding to hire two IT professionals or highly IT-oriented physicists (2 x 0.75 FTE) to give support to DESC infrastructure and DESC group. Ideally, these will be the same individuals overseeing the IDAC at 0.25 of their FTE. The main task for the staff will be to serve DESC infrastructure. This includes installation and maintenance of the software and continuous monitoring of the processes, as well as participation in development of necessary pipelines.
Updated: 2026-07-22
POL-NCB-S3
Science Pipeline Development in the LSST Galaxies Science Collaboration
Astroinformatics Astronomy software Galaxies Machine learning Photometric redshift
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY22
POL-NCB will contribute directable software development effort in the area of estimation of galaxy photometric redshifts and physical properties. NCBJ will base its work on the g developing version of the CIGALE SED fitting tool and we will further optimise it for the work with the LSST data: primarily object catalogs but potentially also the images. This effort will be led in a close collaboration with the main members of the international CIGALE team, embedded in the Galaxies SC, in particular Dr. Veronique Buat, Dr. Denis Burgarella and Dr. Mederic Bouquien. We anticipate cross-correlating the resultant catalogs with similar datasets obtained by other SCs. NCBJ staff will coordinate the work with the Galaxies SC to define necessary precision of the estimated parameters and possibly to include machine learning algorithms to fasten the process of analysis. The resultant user-generated datasets: catalogs of galaxy photometric redshifts and galaxy properties will be made accessible to the Galaxies SC and, with time, to the whole Rubin Observatory community, via appropriate data access centers, among them the local IDAC (S1). NCBJ anticipates usage of both local computing resources associated with IDAC in CIŚ, and Rubin-provided user computing resources to support this work. The aforementioned local computing resources are already available at NCBJ in CIŚ, and additional computing resources will be added if and when needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the NCBJ staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the Galaxies SC.
Updated: 2026-07-22
POL-NCB-S4
Science Pipeline Development in the LSST Dark Energy Science Collaboration
Astroinformatics Astronomy software Cosmology Photometric redshift
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY22
NCBJ will contribute directable software development effort in the general area of LSST large-scale structure (LSS) analysis. This may include selection and photometric redshift (PZ) estimation of galaxies from the LSST data products (primarily the Object catalogs, but potentially also the images). Polish consortium staff will work with the DESC leadership to identify software infrastructure priorities within LSS and PZ, whether self-contained or as part of broader development efforts. NCBJ will take advantage of the relevant successful developments in the Kilo-Degree Survey (KiDS) collaboration, where the Contribution Lead Dr. Maciej Bilicki has been (co-)leading analyses of a similar type. NCBJ will then carry out the identified tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the codes. NCBJ intends to achieve integration with DESC collaborative software efforts using DESC tools and tutorials, and will engage with DESC Data Challenges as well as Rubin Data Previews. The codes will be shared in DESC Community GitHub repositories, to ensure that all DESC members can access them as they are developed. The codes will be prepared to run at NERSC to allow DESC members to engage with the efforts more broadly. The resultant user-generated datasets will be made available to the DESC and, with time, to the whole Rubin Observatory community, via appropriate data access centers, among them the local IDAC (S1).We anticipate using both local computing resources, in particular those associated with the IDAC in CIŚ, and Rubin-provided ones to support this work. The aforementioned local resources are already available at NCBJ in CIŚ, and additional ones will be added if needed. In particular, NCBJ plans to invest into local GPU workstations for the proposed deep-learning developments. In the future, this type of new equipment is aimed to be integrated with the emerging national node for Independent Data Access Center (IDAC).
Updated: 2026-07-22
POL-NCB-S6
Science Pipeline Development in the LSST AGN Collaboration
Active galactic nuclei Astronomy software
Primary recipient: LSST AGN Science Collaboration
Additional recipients: None
Start (approx.): FY21
NCBJ will contribute directable software development effort in the general area of LSST AGN variability science analysis. We will focus on the general area of multi-method time delay determination. Given the expertise of the local group led by the Contribution Lead, and software skills of the postdoctoral fellow who will provide the first stage of this contribution, an exemplary plan for the contributed effort could involve development of a single LSST-adjusted front-end for different packages for quasar lag-recovery methods available and being developed inside the AGN SC. NCBJ will work closely with the AGN SC to define the directions for the development of the needed software, and carry out those tasks as a part of the collaboration, defining milestones and reporting progress. NCBJ will actively seek input from the rest of the collaboration and provide consultations on the use of the new software. The software under development will be tested locally, and subsequent versions will be assimilated into the LSST pipeline. The local computing resources required are already at the group’s disposal and additional resources, if and when needed, will be provided by NCBJ. To acquire the expertise necessary to use the LSST pipeline and its products, Mr. S. Panda has attended a 2-month long LSST Stuck Club program, and he conveyed the acquired knowledge to the rest of the group. NCBJ will actively participate in forthcoming events associated with the Rubin 'Data Previews', all within the context of AGN SC. This plan has been consulted with AGN Science Collaboration.
Updated: 2026-07-22
SER-STG-S1
Credit for past contribution to the LSST by Serbian Technical Group (STG)
Astronomy software
Primary recipient: Rubin Prompt Processing Group
Additional recipients: Rubin Alert Production Group
Start (approx.): FY15
Following agreement about the Serbian Technical Group’s in-kind contribution, signed on November 19, 2013, we were embedded in the LSST Simulations group led by Andrew Connolly (University of Washington) and worked with the LSST Data Management subsystem. The work packages delivered by the STG involved development of an alert simulator using other components of the simulation package (opsim, catsim, stack tools, etc.). This was necessary for having ‘realistic’ objects timing for generating simulated alerts. The alert simulator is a part of the Rubin simulation package (github.com/lsst-sims/sims_alertsim).With a new branch delivered towards the end of the last year, we added support for using MongoDB as a system for a more compact and efficient way of storing alerts. We generated around twenty million alerts and, though there are still some issues, we made all the products available to the Alert Production team. Most of this work is recorded in the LSST JIRA system.In addition, we were testing LSST Stack installations on different Linux flavors, and helped student Yana Kuhanova produce a master thesis in 2016 which played a significant part in a decision to adopt the DM Stack for a different instrument.Members of our team were active at LSST AHM’s and PCW’s and we also organized LSST@Europe2 conference in Belgrade in June 2016 (with support from LSSTC), which connected the European and US LSST communities. We also acted as a proxy for LSST in a very successful EU COST action “Big data in Sky and Earth Observations.”Members of our team are involved in LSST TVS and DESC Science Collaborations.
Updated: 2026-07-22
SLO-UNG-S2
Science Pipeline Development in the LSST TVS Science Collaboration
Astronomy software Time domain astronomy Transient detection
Primary recipient: LSST Transients and Variable Stars Science Collaboration
Additional recipients: None
Start (approx.): FY22
UNG proposes to contribute 1 FTE of directable software development effort preferably with specific emphasis of the contribution geared toward TVS SC, while contributing this 1 FTE to the general pool of fully directable software development is also an option.[a]We are open and flexible for the TVS SC to define needed software development tasks, and then to carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. We anticipate needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources as they become available to ensure the code functions at the needed scale. The aforementioned local computing resources are already available at UNG, and we will work to secure additional local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the Rubin tools and data products: to mitigate this, the UNG staff will engage early with any Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of the TVS SC.
Updated: 2026-07-22
SWE-STK-S1
Science Pipeline Development in the LSST Dark Energy Science Collaboration
Astronomy software Cosmology Galaxy clusters Photometric redshift Supernovae
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY22
SU will contribute directable software development effort in the general area of LSST DESC science analysis. We will contribute two strands of directable effort: (1) computing infrastructure effort supporting areas covering data access, data processing, simulation setup and management, validation and/or provenance tracking; and (2) software development effort in areas requiring domain knowledge, where we have the expertise to contribute to the DESC’s photometric redshift, supernovae, large scale structure WGs; difference imaging and low surface brightness image processing and validation (and related cross-WG activities); and observing-strategy related work. SU staff will work with the DESC to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. This proposed contribution was developed in consultation with the DESC. We anticipate needing modest amounts of local computing to support this work, and will work to ensure that codes run on the needed scale at the primary DESC computing center (currently NERSC); we may use DESC computing resources in the course of code development/testing. Local computing resources are already available at the SU Physics Department through a 29 node cluster with 880 cores, 6128 GB memory and 462 TB storage. We will add local resources if needed. The primary risk associated with this work is in gaining the needed expertise in the DESC and Rubin tools and data products: to mitigate this, SU staff will engage early with any Rubin and LSST DESC tutorials provided, engage with DESC Data Challenges, and look to be active participants in events associated with the Rubin “Data Previews”, all within the context of LSST DESC.
Updated: 2026-07-22
SWE-STK-S2
Past Science Pipeline Development in the LSST Dark Energy Science Collaboration
Astronomy software Cosmology Supernovae Time domain astronomy Transient detection
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY17
SU staff contributed directable software development effort in the general area of LSST Dark Energy science analysis, primarily within the DESC supernova and observing strategy working groups. The contributed effort included substantial contributions to DESC Data Challenge 2 (DC2) software development, as well as enabling contributions to supernova pipeline development, observing strategy studies for transient cosmology, and to transient classification software development and early classification infrastructure. SU staff worked with the LSST DESC to define needed software development tasks, and then carried out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. This summary of past contributions was developed in consultation with DESC.
Updated: 2026-07-22
SWI-EPF-S1
An Interactive and Dynamical Database of Strong Lensing Systems
Active galactic nuclei Astroinformatics Galaxy clusters Gravitational lensing Photometric redshift Strong gravitational lensing Time domain astronomy Transient detection
Primary recipient: LSST Strong Lensing Science Collaboration
Additional recipients: LSST Dark Energy Science Collaboration
Start (approx.): FY22
A strong lensing database is proposed and builds on two existing efforts: 1- the masterlens database of Leonidas Moustakas, who is a collaborator of EPFL and a member of the Euclid strong lensing work group, 2- the EPFL database of time-delay strong lenses which currently contains all known lensed quasars in addition to a number of candidates found at EPFL. This database will contain at least the following: 1- all known lenses, at galaxy, group, and cluster scales (along with the arcs within clusters), 2- positional and redshift information, 3- a classification statement, 4- the method(s) used to find them, 5- lens models either from the literature or linked to the LSST modeling effort, 6- deblending of the lens and source with improved photometry linked to the photo-z group, 7- a catalogue of false positive in view of retraining of neural networks for improved efficiency of the lens finding in LSST, 8- a catalogue of lensed transients. For each object the database will query dynamically all available ancillary public data including SDSS, DES, KiDS, HSC, PanSTARRS, CFIS, in addition to the MAST database and ESAsky database. A query to the literature will also be included. All interactions with the database will be done through APIs written, when needed, in collaboration with other DESC and SLSC infrastructures. The PI’s group has the general policy to produce exclusively open source codes. In fact, collaborative development with other groups working in LSST is something we would welcome. The database shall be updated by any registered member with a minimum effort, for example by uploading .csv files with minimum information or by editing specific fields for specific lenses. EPFL will act as a moderator to make sure that only reliable entries are actually recorded. This will be a long-term maintenance effort over the whole duration of the survey. Specific effort will be devoted to enabling LSST strong lensing science. Links between the database and the modeling tools in the consortium will be made. This is also true for the deblending and photo-z works. Note that EPFL is currently designing new modeling tools based on sparse regularization with wavelets and leading to improved lens/source deblending as well as to exquisite source reconstruction on any grid of arbitrarily small pixels. These tools will be used to feed the database with source reconstruction and source/lens separation. The codes are already freely available as a lenstromy module, SLITromomy. We will work along these lines for any work done in the context of the present proposal. This contribution has been endorsed by the Strong Lensing Science Collaboration and the Dark Energy Strong Lensing Science Collaboration.
Updated: 2026-07-22
SWI-ETH-S1
Science Pipeline Development in the LSST Dark Energy Survey Collaboration
Astronomy software Cosmology Gravitational lensing Photometric redshift
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY22
The ETH Cosmology group will contribute directable software development effort in the area of LSST cosmological science analysis. The ETH Cosmology group will first work with the Dark Energy Science Collaboration (DESC) leadership to define needed software development tasks in DESC working groups and match them to the software expertise available at ETH Zurich. Once these tasks have been agreed upon, a software developer will be appointed at ETH Zurich and will carry out these tasks as an integral part of DESC, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. Software contributions to DESC working groups related to weak lensing, image simulations, photometric redshifts, cosmological inference, cosmological simulation and theoretical predictions are of particular interest to the ETH cosmology group, but other topics can also be discussed with the DESC leadership.The ETH Cosmology group anticipates needing modest amounts of local computing to support this work, and focus on using Rubin-provided user computing resources, as they become available to ensure the code functions at the needed scale. In particular, the developed codes will be implemented and optimised to run at NERSC. The aforementioned local computing resources are already available to the cosmology group at ETH Zurich. To gain the needed expertise in the DESC and Rubin tools and data products, the ETH software developer will engage early with any DESC and Rubin tutorials provided, and look to be active participants in events associated with the Rubin “Data Previews” and DESC data challenges, all within the context of DESC.
Updated: 2026-07-22
SWI-ETH-S2
Covariance Estimation and Cosmology Ppieline Development in DESC
Astronomy software Cosmology
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY26
UZH contributes directable software development effort to the LSST DESC analyses, including the covariance estimation code TJPCov, as described in the resource needs statement DESC-RN-02. UZH staff works within DESC, taking input from the Collaboration, producing detailed documentation, and supporting DESC members in the use of the code as needed. We use modest amounts of existing local computing to support this work as we focus on using Rubin- and DESC-provided user computing resources to ensure the code functions at the needed scale. We avoid risks associated with gaining the needed expertise in the Rubin/DESC tools and data products as one member of our staff has already been working in the pipeline scientists role.
Updated: 2026-07-22
SZA-SAA-S2
MeerKAT high-level data products and services for LSST
Astroinformatics Astronomy software Galaxies High performance computing Radio astronomy
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: NOIRLab CSDC
Start (approx.): FY22
We will produce high-level data products from public MeerKAT data, and any MeerKAT observing programs submitted on behalf of the LSST Galaxies SC. The MeerKAT archive is making visibility data available for all projects after a 1-year proprietary period, but the size and format of the visibility data (TBs per observation) makes it a significant challenge to reduce these to data products suitable for scientific analysis. Although the archival data will be public, the large field of view of MeerKAT means that the data are extremely unlikely to be fully exploited, leaving a lot of scope for serendipitous discoveries using the combination of LSST and MeerKAT data. The MeerKAT data processing will be handled by South Africa, building on software pipelines that are at an advanced stage of development, to produce a homogeneous contributed dataset potentially consisting of thousands of square degrees of science-quality radio continuum images and catalogs to the US and Chilean communities. The data processing itself will be done using high performance computing facilities in South Africa, at the University of KwaZulu-Natal (for prototyping) and the Centre for High Performance Computing. As MeerKAT data are lower resolution (8' at L-band) than the LSST data, we will develop the tools and services to optimally match them to the LSST catalogs. While the traditional 'likelihood ratio' technique may work for point sources, we will need to develop new algorithms to automatically associate multiple component radio sources (jets etc.) to the correct LSST counterparts (and deal with the much higher source density of LSST images). This will be done under the direction of the Galaxies SC, and the tools developed for this may be used as part of a broader effort to optimally use similar multi-wavelength data with LSST. All the software developed for this contribution will be made publicly available under free software licenses.While the MeerKAT data processing challenge is large, the final MeerKAT data products will be relatively small (at most 10 Tb of images and 30 Gb of catalogs, containing tens of millions of objects), and Knut Olsen has confirmed that NOIRLab will host these data in the US IDAC. We will provide all necessary support and documentation for this dataset and associated software over the lifetime of LSST. The Galaxies Science Collaboration endorses the creation of high-level data products from the MeerKAT science archive to facilitate LSST galaxy evolution science.
Also see: dataset (SZA-SAA-S2) →Updated: 2026-07-22
SZA-SAA-S3
Planning and Infrastructure for the LSST Dark Energy Science Collaboration
Astronomy software Cosmology Machine learning Supernovae Time domain astronomy Transient detection
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY17
As the Rubin Observatory will detect millions of transients each night, automatic photometric classification has arisen as a critical requirement for the success of the survey. Dark energy constraints rely on a relatively pure sample of type Ia supernova light curves. Lochner developed one of the first machine learning based supernova classification codes called snmachine, in response to this requirement for the DESC supernova pipeline (see key product SupernovaType on page 117 of the DESC Science Roadmap), as a software development effort guided by the supernova working group. snmachine continues to be actively developed by Lochner and her collaborators, is available to all DESC members and will be made publicly available on publication of the final release paper. While this important contribution was made when Lochner was out of South Africa and so cannot count towards our in-kind contribution, it is mentioned because part of our contribution will be the continued development, improvement and maintenance of snmachine in collaboration with the DESC Supernova Working Group. Future improvements could include optimising the software specifically for LSST data, implementing new features and algorithms and integrating snmachine with broader supernova analysis pipelines.The other component of our contribution concerns observing strategy infrastructure work. The observing strategy of the LSST survey impacts many science cases and the Project has been engaging with the community to develop metrics to help analyse different simulated observing strategies. Lochner has been co-leading efforts to write these metrics for the various cosmology probes. She is also developing a suite of high level tools to visualise the impact of observing strategy on cosmology which will be made publicly available and will continue to serve the DESC throughout the survey as observing strategy gets adjusted. The maintenance of both projects will be done by Lochner and collaborators (not listed on this proposal) and so does not require additional resources. The ongoing maintenance and development effort will be guided by DESC input in terms of which project is higher priority and what additional features are required.DESC has endorsed this contribution in an email exchange between Phil Marshall and Rachel Mandelbaum (spokesperson of DESC).
Updated: 2026-07-22
TAI-ASI-S4
Non-Directable Software Development for the Galaxy SC
Astroinformatics Astronomy software Galaxies Galaxy clusters Machine learning Photometric redshift
Primary recipient: LSST Galaxies Science Collaboration
Additional recipients: None
Start (approx.): FY22
We propose to provide a non-directable software development contribution to the Galaxies SC based on our expertise and experience in scientific code development. Such software development contributions will be provided through professional efforts by two senior astronomers at ASIAA, Dr. Bau-Ching Hsieh (Specialist, equivalent of permanent staff scientist) and Dr. Hung-Yu Jian (Support Scientist), both equipped with relevant skill sets and a track record of developing software for use in extragalactic astronomy and cosmology. Both Dr. Hsieh and Dr. Jian have highly advanced skills and two decades of experience in fortran coding for scientific software development. Dr. Hsieh developed the Direct Empirical Photometric (DEmP; Hsieh & Yee 2014, ApJ, 792, 102) code, an empirical polynomial fitting machine learning algorithm for photometric-redshift estimation that is designed to minimize systematic biases associated with conventional empirical fitting methods. The DEmP code is one of photo-z estimation algorithms implemented into the HSC pipeline (Tanaka et al. 2018, PASJ, 70, S9), and it has been extensively used for a wide range of HSC extragalactic science cases. Its performance is consistently among the best of the algorithms used in the HSC-SSP. We emphasize that, in its current setting, DEmP meets all requirements set in “Roadmap to Photometric Redshifts for the LSST Object Catalog” except for the code language (fortran).Dr. Jian has long-standing experience in writing codes and developing algorithms for analyzing large data sets from the Pan-STARRS (Jian et al. 2017, ApJ, 845, 74) and HSC-SSP (Jian et al. 2018, PASJ, 70, 23; Jian et al. 2020, ApJ, 894, 125). Most importantly, Dr. Jain has written a cluster detection code in fortran called pFOF (Probability Friends-Of-Friends; Jian et al. 2014, 788, 109) that can be applied to data coming from the LSST, taking photo-z of galaxies as the main input.
Updated: 2026-07-22
UKD-OXF-S1
DESC Analysis Pipeline Development
Astroinformatics Astronomy software Cosmology Gravitational lensing Photometric redshift
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY15
Oxford will contribute directable software development effort in “catalog-to-parameters” stage of the data analysis pipeline of the Rubin DESC, which is the main recipient of this contribution. This covers activities relevant to four of the DESC working groups: Large-Scale Structure (LSS), Theory and Joint Probes (TJP), Weak Lensing (WL) and Photometric Redshifts (PZ).These are examples of the activities for which, given our expertise, we could provide a more useful contribution (with references to specific deliverables and products in the DESC Science Roadmap): development of the Core Cosmology Library (TJP5A), likelihood pipeline for joint analyses (TJP5B), joint pipelines with CMB data (TXPipe-LSS), covariances for WL and LSS (TXCov), software for two-point statistics (TXTwoPoint), the design of null tests (WLNullTest), including extensions to external CMB datasets, software for astrophysical systematics (CX5), covariance matrices for joint analyses (CX7), interfaces between LSS, WL and PZ (PZSummarize, PZnzSummarizers), the development of algorithms to obtain optimal source and lens tomographic samples (TXSourceSelector and TXLensSelector), generation of random catalogs (TXRandoms).The relevance of this proposed contribution has been discussed and coordinated with the points of contact in the DESC, and the example activities provided above are valuable active or anticipated deliverables and products.Note that the potential PZ-related activities contained in this part of the proposal are different from those described in S2. While there are obvious synergies between both contributions, there is a clear division of work between the tasks of developing and improving PZ algorithms (the subject of S2), and the developing of interfaces to make use of PZ products in the cosmological analysis of LSS and WL data (relevant to this contribution).The development and validation of these software packages will require access to HPC facilities. The resources available at the Oxford Astrophysics Small Research Facility (to which we have unrestricted access), as well as access to NERSC should be sufficient for this work.
Updated: 2026-07-22
UKD-OXF-S4
Strong Lens Discovery System and Candidate Server
Astroinformatics Astronomy software Citizen science Gravitational lensing Strong gravitational lensing Time domain astronomy Transient detection
Primary recipient: LSST Strong Lensing Science Collaboration
Additional recipients: LSST Dark Energy Science Collaboration
Start (approx.): FY22
Oxford will contribute directable software development effort in the area of the Rubin Strong Lens discovery system and infrastructure in collaboration with the SLSC and DESC SL Working Group. This may include (but won’t encompass all) providing the basic infrastructure for the SL discovery pipeline that connects the DM/DA to UGDP image/stamp generation, explores local PSF determination and applying lens subtraction methods, connects the discovery algorithms and the SL EPO (Rubin-Space Warps) platform, develops and implements active learning between ML and Citizen Science, connects to multiple fast modelling algorithms and then connects the resultant samples to value added databases that will serve the candidates. The work also needs detailed planning and framework and standards definition to achieve this to help all contributors build components that contribute to the overall goal. The foreseen infrastructure will allow multiple lens finders (ML-assisted or otherwise) to plug into the SL discovery system, thereby maximising the number of lenses discovered. As such, the proposed work will help to deliver a system for the US/Chilean Rubin community that will enable e.g. discovery, candidate ranking and follow-up prioritisation, and connect the database to the alert stream to allow the identification of extragalactic lensed transients a quick and fast possibility. The plan of work will be developed in conjunction with the leadership for both collaborations, following priorities and gaps in the infrastructure development to meet the needs of the whole Rubin SL community. We are willing and happy to work with other SL infrastructure S/W teams either in place among the US/Chilean communities or contributing effort via in-kinds to complete this work.We will hire an experienced developer or researcher with strong computational skills who will work along with the DM, EPO and SC teams to ensure that the infrastructure components are effectively generated. Given the large number of cutouts that will be needed, a relationship to either the US-DAC/iDAC will be developed, and accompanying infrastructure to deliver these to the system and lean finders and modellers. In addition, connection of the candidate servers to the alert stream via one of the alert brokers will also be needed to maximize the potential to identify lensed transients from early survey data. We aim to have the infrastructure in place for commissioning/early science to test and then demonstrate the efficacy of the system and then improve, refine, optimise the capability as required.
Updated: 2026-07-22
UKD-UKD-S10
Science Software development: spectroscopic classification of transients and 4MOST spectra
Astronomy software Cosmology Spectroscopy Time domain astronomy Transient detection
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: LSST Transients and Variable Stars Science Collaboration
Start (approx.): FY21
TiDES, the Time Domain Extragalactic Survey, is a survey on the 4-metre Multi-Object Spectrograph Telescope (4MOST) focused on the spectroscopic follow-up of Rubin Observatory LSST extragalactic optical transients. We have 250,000 fibre-hours of spectroscopy time available within the TiDES survey (2% of the total 4MOST fibres). With this, we will obtain (i) spectroscopic observations of 35,000 live transients to iAB=22.5, and (ii) follow-up of 70,000 transient host galaxies to obtain redshift measurements for photometric classification and cosmological applications. We will contribute non-directable software development effort to support developing TiDES into a contributed dataset to DESC and TVS. We expect there to be between 5-10 live (i < 22.5 mag) extragalactic transients per 4MOST field, and we will put a fibre on all these, effectively giving a magnitude limited sample. We will work closely with the DESC SN Working Group to design a selection function for the LSST transient stream to optimise the type Ia SN selection (including host galaxies) for cosmology. We will implement the DESC agreed strategy within the Lasair broker to select SNe with high quality LSST lightcurves (or other measured characteristics as desired). We will provide immediate information, to DESC and TVS (and the whole US/Chilean community) onWhich objects have fibres: DESC will primarily drive the selection function. As it is a magnitude limited sample we also expect all the spectra to be of interest to TVS. Through Lasair, we will highlight which targets will get a spectrum. Which targets have been (successfully) observed : immediate meta-data on what has been observed, signal-to-noise estimate of data.Rapid estimate of redshift and type from quick-look data – available to all DESC, TVS and the US/Chilean community to help decide on other triggers.Full, staged, data releases of fully calibrated data, accessible through the Lasair broker.The 4MOST are ESO public survey data and the raw data are public in the ESO archive immediately. However these data are not in scientifically accessible or useable form without deep knowledge of the pipeline, fibre allocation processes and selection function. Hence we propose this as a non-directable software contribution to ensure maximum scientific exploitation of the data (in line with the Handbook’s guidance on public data). The DESC and TVS endorse this contribution. We note the latter is on the condition that TVS members will be kept informed in a timely manner of all information relevant to these surveys. This is our plan, and we are happy to accept that condition.
Also see: dataset (UKD-UKD-S10) →Updated: 2026-07-22
UKD-UKD-S11
Science Software development: photometric redshift estimation and DESC related software development
Astronomy software Cosmology Galaxy clusters Gravitational lensing Photometric redshift
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: Rubin Photo-z Coordination Group
Start (approx.): FY21
This directable staff effort contribution has been developed jointly with DESC. We will contribute directable software development effort to the DESC primary science analysis, including but not limited to robust photo-z solutions, modelling and validation of photometric redshift sample distribution, their uncertainties and how these impact the DESC cosmological parameter pipelines. As directable effort within DESC we will model statistical and systematic uncertainties in weak lensing and clustering signals, as well as propagation of these uncertainties, especially their spatial variation across the survey, into cosmological likelihoods. Joachimi and Lahav will work with relevant members of the DESC Management Team and Working Group conveners to define needed software development tasks, and then carry out those tasks as an integral part of the collaboration, reporting regularly on progress, taking input from the rest of the collaboration, and supporting the collaboration’s members in the use of the code. Joachimi and Lahav have also joined Rubin’s Photometric Redshift Coordination Group and will work with this Team to define additional benefits of the proposed work for LSST’s users beyond the DESC remit. The work will make use of DESC’s computing resources, HPC facilities at UCL, as well as UK ‘s IRIS computing dedicated to LSST (as part of the UK’s IDAC, see S3), all of which are already available or are part of this in-kind proposal. Note that Joachimi’s PhD student is currently road-testing GridPP facilities for DESC photo-z applications. The primary risk associated with this work is the timely hiring of qualified personnel. This will be mitigated by fast-tracking the funding line of this proposal if and when successful. Moreover, we have ample experience recruiting highly qualified staff for infrastructure work in galaxy surveys, and are currently gaining experience with COVID-era hires and work models. We will also invite additional DESC management personnel onto the recruitment panel.
Updated: 2026-07-22
UKD-UKD-S12
Science Software development: Phases C and D
Astronomy software
Primary recipient: Rubin International Program Coordinator (Software Development)
Additional recipients: None
We propose to fund a cadre of directable software developers during Phases C and D of the LUSC programme, running from April 2023 to March 2027 and April 2027 to March 2033, respectively; although the Phase D end-date will depend on when the final data release appears. These developers will be physically located in UK universities but functionally embedded within an appropriate Recipient Group, usually a Science Collaboration, but, potentially, part of the Rubin Observatory operations team. Our nominal plan is for 7 full-time positions to be funded for the four years of Phase C (i.e. 28 staff years in total) and a further six staff-years during Phase D, for a total contribution of 34 staff-years of directable effort, although the detailed profiling of this effort can be negotiated. Our proposal is that bids for developer positions are developed by UK groups in conjunction with a relevant Recipient Group, and, as for our Phase B DEV WPs, are assessed by a panel that combines senior UK scientists and Rubin-nominated representatives, to ensure that the selected projects both make best use of existing expertise within the UK community and deliver high priority outputs to the Recipient Group. These bids should include consideration of maintenance of software to be delivered, for which support can be provided in Phase D. Projects selected by the panel would then be included in the LUSC Phase C funding proposal to be submitted to the STFC Project Peer Review Panel (PPRP) some time around April 2022; this would be a submission against an agreed funding line, but all project grants are peer reviewed by PPRP. This timescale then necessitates the start of the proposal preparation phase in Summer 2021 - i.e. as soon as this in-kind package is agreed. Computational resources will be provided through IRIS (www.iris.ac.uk), a collaboration between the providers and users of computing infrastructure for STFC-funded astronomy, particle and nuclear physics projects; as an IRIS member, LSST:UK makes an annual bid to secure IRIS resources for the coming year.STFC will require that all funded teams report to an Oversight Committee, which will monitor progress against deliverables. This has begun during LUSC Phase B, with a process based around six-monthly plans, so we propose that this should be the mechanism through which funded staff are redirected, with new six-monthly plans agreed between the Recipient Group and the local supervisor.
Updated: 2026-07-22
UKD-UKD-S16
Adler - Solar System Transient Classification
Astroinformatics Astronomy software Solar system astronomy Time domain astronomy Transient detection
Primary recipient: LSST Solar System Science Collaboration
Additional recipients: None
Start (approx.): FY23
LSST will discover ~6 million new Solar System small bodies, including the comet that ESA’s Comet Inceptor mission will go to (Schwamb et al. 2018, IvezÍc et al. 2019). With each planetesimal receiving hundreds of observations across six filters, LSST will radically transform the view of our planetary system and usher in a revolution for time domain Solar System science. LSST:UK will develop Adler, an open source python-based LSST Solar System transient classifier, and incorporate Adler into Lasair, the UK’s LSST transient alert broker (Smith et al. 2019). Rubin Observatory’s automated routines will broadcast a “transient” alert for each new, variable, or moving source. Solar System bodies are always changing in their apparent brightness (possibly spanning many magnitudes) as they rotate and move closer to or further away from the Sun and Earth. It will be up to the Rubin user community to identify the deviations from these trends to find the interesting time domain Solar System phenomena in the LSST alert stream. Lasair will contextually classify LSST astrophysical alerts using Sherlock (Smith et al. 2020) but current Lasair development plans are for Solar System alerts to only be stored in a database. Adler will utilise either the LSST alert stream through Lasair or the prompt data products available on the Rubin Science Platform (RSP) and International Data Access Centres (IDACs) to identify truly changing Solar System bodies. Adler will flag potential dynamically new comets and interstellar objects first entering our Solar System, identify possible planetesimal collisions, break up events, or the onset of cometary activity and cometary outbursts. Adler will fit rotational light curves and phase curves and identify outlying photometric points; Adler will also automatically flag suitable Comet Interceptor fly-by targets, and identify cometary coma/tails, through multi-aperture photometry of the alert images and source extendedness. This staff effort contribution has been developed jointly with SSSC. The Edinburgh postdoc will develop the core small body/comet analysis functions, and the QUB software developer postdoc will focus on Lasair integration and Adler user interface and infrastructure. Adler’s core functionality achieves several of the key tasks in the SSSC’s Software Roadmap (Schwamb et al. 2019). The SSSC supports this contribution and welcomes the flexibility to use Adler on the RSP and IDACs for an individual small body or with Lasair running automatically in bulk on all incoming Solar System alerts.
Updated: 2026-07-22
UKD-UKD-S6
Science Software development: Low surface brightness science
Astronomy software Gravitational lensing
Primary recipient: Rubin Algorithms & Pipelines Team
Additional recipients: LSST Galaxies Science Collaboration
Start (approx.): FY20
The LSB Universe – the regime that is inaccessible in past wide-area surveys – hosts virtually all of LSST’s extra-galactic discovery space. However, LSST’s ability to access this revolutionary domain depends on the sky-subtraction in the DM pipeline preserving LSB flux in LSST images. We will contribute directable pipeline development to produce sky-background modelling and subtraction that preserves LSB flux, which is essential for LSST Galaxies science. The immediate recipient is the Rubin Algorithms and Pipelines team and the eventual beneficiary is the Galaxies Science Collaboration (GSC). We have already been working on this project, in a directable fashion, with the DM team (Kelvin/Al-Sayyad/Lupton/Reed) since March 20. We have developed quality-assurance metrics, in the form of surface-brightness/magnitude deficits, to quantify how the pipeline handles LSB flux. As a proof of concept, injection of fake single-Sersic sources into coadded imaging, from the continuously re-reduced COSMOS tract 9813, has revealed potentially significant sky over-subtraction at flux levels fainter than ~26 mag arcsec-2 around large objects (>8 arcsec), with a flux-loss ratio of >15 percent in the worst cases. This relatively aggressive sky-subtraction ensures that LSB flux does not connect objects and confuse de-blenders, making it ideal for weak-lensing science. However, it compromises the majority of Galaxies science. A bifurcation of the pipeline appears necessary to satisfy both communities. Ongoing testing in collaboration with the DM team will repeat these analyses for a more realistic scenario, injecting fake sources at the visit level and propagating those images through to final coaddition. The broad plan is to explore intermediate points in the DM pipeline, where the sky-subtraction is not as aggressive, as a starting point to developing sky-background modelling and subtraction that preserves LSB flux. We will continue to work closely with the DM team to identify future development tasks and perform these as an integral part of the GSC, taking input from members and reporting regularly on progress in telecons and via interaction on Slack. We are using the Rubin Science Platform (RSP) to access and analyze pre- and post-model injection outputs from the DM pipeline, since the RSP computing architecture is built specifically for the Project, and using local resources to interpret the results. We do not anticipate a change in our resource needs. The primary risk is gaining an understanding of the DM pipeline architecture. However, our close and ongoing interaction with the DM team mitigates this.
Updated: 2026-07-22
UKD-UKD-S8
Science Software development: DESC operations
Astroinformatics Astronomy software Cosmology Galaxy clusters Gravitational lensing
Primary recipient: LSST Dark Energy Science Collaboration
Additional recipients: None
Start (approx.): FY23
Zuntz is designing and implementing the catalogue-to-cosmology pipeline, TXPipe, for the weak lensing and large-scale structure joint analysis, implementing (at LSST scale) algorithms for data reduction and analysis from DM catalogues into two-point measurements and other summary statistics. This has been identified as a key pipeline in the DESC Science Roadmap. He has also written and is managing the infrastructure framework, Ceci, for running the collected complete pipeline. This software was/is all written specifically for the DESC.Perry will manage simulation data generation, storage, and analysis as a key part of the data challenge simulation process. In both cases this activity is directable by the collaboration; Zuntz reports to the analysis coordinator, providing quarterly reports and annual plans, and Perry ultimately to the computing coordinator, with day-to-day coordination by Zuntz. Computing for Zuntz's work on the lensing/clustering pipeline is available from NERSC via DESC's allocation. Computing for Perry's work on the UK Grid is provided by an existing GridPP grant. All software developed by the team will be public, in accordance with the proposed DESC software policy.This proposal has been developed in consultation with DESC. The past contribution FY19-FY20 has been endorsed by DESC.
Updated: 2026-07-22