A1 Refereed original research article in a scientific journal
Sorcha: Optimized Solar System Ephemeris Generation
Authors: Holman, Matthew J.; Bernardinelli, Pedro H.; Schwamb, Megan E.; Juric, Mario; Oldag, Drew; West, Maxine; Napier, Kevin J.; Merritt, Stephanie R.; Fedorets, Grigori; Cornwall, Samuel; Kurlander, Jacob A.; Eggl, Siegfried; Kubica, Jeremy; Kiker, Kathleen; Murtagh, Joseph; Naidu, Shantanu P.; 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: 97
Volume: 170
Issue: 2
Number of pages: 10
ISSN: 0004-6256
eISSN: 1538-3881
DOI: https://doi.org/10.3847/1538-3881/ade435
Web address : https://doi.org/10.3847/1538-3881/ade435
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/499426749
Sorcha is a solar system survey simulator built for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) and future large-scale wide-field surveys. Over the 10 yr survey, the LSST is expected to collect roughly a billion observations of minor planets. The task of a solar system survey simulator is to take a set of input objects (described by orbits and physical properties) and determine what a real or hypothetical survey would have discovered. Existing survey simulators have a computational bottleneck in determining which input objects lie in each survey field, making them infeasible for LSST data scales. Sorcha can swiftly, efficiently, and accurately calculate the on-sky positions for sets of millions of input orbits and surveys with millions of visits, identifying which exposures these objects cross, in order for later stages of the software to make detailed estimates of the apparent magnitude and detectability of those input small bodies. In this paper, we provide the full details of the algorithm and software behind Sorcha's ephemeris generator. Like many of Sorcha's components, its ephemeris generator can be easily used for other surveys.
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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. M.J.H. gratefully acknowledges support from the NSF (grant No. AST2206194), the NASA YORPD Program (grant No. 80NSSC22K0239), and the Smithsonian Scholarly Studies Program (2022, 2023). 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 UK Science and Technology Facilities Council (STFC) grant ST/P000304/1. This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Skodowska-Curie grant agreement No. 101032479. C.O.C, 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 Number: 2332736 and Collaborative Research: Rubin Rocks: Enabling near-Earth asteroid science with LSST NSF Award Number: 2307570. 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.
