A1 Refereed original research article in a scientific journal
Sorcha: A Solar System Survey Simulator for the Legacy Survey of Space and Time
Authors: Merritt, Stephanie R.; Fedorets, Grigori; Schwamb, Megan E.; Cornwall, Samuel; Bernardinelli, Pedro H.; Juric, Mario; Holman, Matthew J.; Kurlander, Jacob A.; Eggl, Siegfried; Oldag, Drew; West, Maxine; Kubica, Jeremy; Murtagh, Joseph; Jones, R. Lynne; Yoachim, Peter; Lyttle, Ryan R.; Kelley, Michael S. P.; Moeyens, Joachim; Kiker, Kathleen; Naidu, Shantanu P.; Snodgrass, Colin; Matthews, Shannon M.; Chandler, Colin Orion
Publisher: American Astronomical Society
Publishing place: BRISTOL
Publication year: 2025
Journal: The Astronomical Journal
Journal name in source: The Astronomical Journal
Journal acronym: ASTRON J
Article number: 100
Volume: 170
Issue: 2
Number of pages: 41
ISSN: 0004-6256
eISSN: 1538-3881
DOI: https://doi.org/10.3847/1538-3881/add3ec
Publication's open availability at the time of reporting: Open Access
Publication channel's open availability : Open Access publication channel
Web address : https://doi.org/10.3847/1538-3881/add3ec
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/499423925
The upcoming Legacy Survey of Space and Time(LSST)at the Vera C. Rubin Observatory is expected torevolutionize solar system astronomy. Unprecedented in scale, this 10 yr wide-field survey will collect billions ofobservations and discover a predicted similar to 5 million new solar system objects. Like all astronomical surveys, itsresults will be affected by a complex system of intertwined detection biases. Survey simulators have long beenused to forward-model the effects of these biases on a given population, allowing for a direct comparison to realdiscoveries. However, the scale and tremendous scope of the LSST requires the development of new tools. In thispaper we presentSorcha, an open-source survey simulator written inPython. Designed with the scale ofLSST in mind,Sorchais a comprehensive survey simulator to cover all solar system small-body populations. Itsflexible, modular design allowsSorchato be easily adapted to other surveys by the user. The simulator is builtto run both locally and on high-performance computing clusters, allowing for repeated simulation of millions tobillions of objects(both real and synthetic).
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Funding information in the publication:
This work was supported by an LSST Discovery Alliance LINCC Frameworks Incubator grant [2023-SFF-LFI-01-Schwamb]. Support was provided by Schmidt Sciences. S.R.M. and M.E.S. acknowledge support in part from UK Science and Technology Facilities Council (STFC) grants ST/V000691/1 and ST/X001253/1. G.F. acknowledges support in part from STFC grant ST/P000304/1. This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sk & lstrok;odowska-Curie grant agreement No. 101032479. M.J. and P.H.B. acknowledge the support from the University of Washington College of Arts and Sciences, Department of Astronomy, and the DiRAC (Data-intensive Research in Astrophysics and Cosmology) Institute. The DiRAC Institute is supported through generous gifts from the Charles and Lisa Simonyi Fund for Arts and Sciences and the Washington Research Foundation. M.J. wishes to acknowledge the support of the Washington Research Foundation Data Science Term Chair fund, and the University of Washington Provost's Initiative in Data-Intensive Discovery. J.M. acknowledges support from the Department for the Economy (DfE) Northern Ireland postgraduate studentship scheme and travel support from the STFC for UK participation in LSST through grant ST/S006206/1. J.A.K. and J.M. thank the LSST-DA Data Science Fellowship Program, which is funded by LSST-DA, the Brinson Foundation, and the Moore Foundation; their participation in the program has benefited this work. S.E. and S.C. acknowledge support from the National Science Foundation through the following awards: Collaborative Research: SWIFT-SAT: Minimizing Science Impact on LSST and Observatories Worldwide through Accurate Predictions of Satellite Position and Optical Brightness NSF award No. 2332736 and Collaborative Research: Rubin Rocks: Enabling near-Earth asteroid science with LSST NSF award No. 2307570. R.R.L. was supported by the UK STFC grant ST/V506990/1. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
