Chairs: Sarah Greenstreet and Colin Orion Chandler

This session will focus on Solar System science with the LSST.

Please contact the session chair with any questions, or if you'd like to volunteer to speak or help with this session.

Session schedule (time slots include 7 min for talks + 3 min for questions):
(abstracts for invited talks below)

• (2:00-2:10) An Overview of Sorcha (Meg Schwamb; invited)

• (2:10-2:20) Predictions of the LSST SSO Yield (Pedro Bernardinelli speaking for Jake Kurlander; invited)

• (2:20-2:30) Detecting Non-Gravitational Acceleration in Near-Earth Objects with the LSST (W. Garrett Levine; contributed)

• (2:30-2:40) The Solar System Notification Alert Processing System (SNAPS): Asteroid Population Outlier Detection (Mike Gowanlock; contributed)

• (2:40-2:50) Individual Outlier detection in LSST using SNAPS (Maria Chernyavskaya; contributed)

• (2:50-3:00) Artificial-intelligence powered twilight discovery of Aylos, Atiras and Comets at Palomar Observatory (Bryce T. Bolin; contributed)

• (3:00-3:10) Accelerated Asteroid Characterization Using PhAst (Arushi Nath; contributed)

• (3:10-3:20) Scaling Citizen Science for LSST: The Active Asteroids Program (Colin Orion Chandler; invited)

• (3:20-3:30) Introduction to exploring the Data Preview 0.3 (DP0.3) simulated catalogs of Solar System objects with the Rubin Science Platform (Sarah Greenstreet; invited)

Abstracts for invited talks:

An Overview of Sorcha (Meg Schwamb)

Sorcha is an open-source community LSST Solar System Survey Simulator currently under development. The software takes any defined small body population inputted and will bias it to what the LSST would have detected utilizing the survey’s pointing history, observation metadata, camera footprint, search algorithm detection efficiency, and other information about the telescope and observatory. In this talk, I will give a brief overview of Sorcha and provide an update on our timeline for completion.

Predictions of the LSST SSO Yield (Jake Kurlander)
We use Sorcha (Meritt et al., in prep), a new solar system survey simulator, to simulate ten years of LSST detections of solar system objects (SSOs) including near-Earth objects (NEOs), main belt asteroids (MBAs), and trans-Neptunian objects (TNOs). We report the expected yield of the survey under different assumptions of state-of-the-art orbital, size, color, and light curve distributions, and provide an update to the 2009 LSST Science Book predictions. We discuss the number of objects discoverable given LSST linking requirements as well as the shortcomings of this strategy.

Scaling Citizen Science for LSST: The Active Asteroids Program (Colin Orion Chandler)
We present our NASA Partner program Active Asteroids and its strategy for Citizen Science with
LSST. Active Asteroids launched in 2021 with the goal of engaging the public in the search for rare
“active asteroids” – small solar system bodies that display comet-like tails (or comae) despite being
on asteroidal orbits. To date, some 10,000 volunteers have conducted 9 million image classifications,
leading to our discovering over 25 active minor planets. LSST data, however, will dwarf our current
DECam dataset, with more small solar system body detections anticipated in a single week than an
entire decade of DECam data. Here, we (1) describe the logistical and techincal challenges associated with
scaling our program for LSST, and (2) discuss our efforts to preparare and adapt Active Asteroids for
the incoming data deluge, such as advanced data screening techinques that include the deployment of
an AI assistant (named TailNet0). We hope our experiences and approaches will be of use to other
Citizen Science programs (and similar endeavors) preparing for LSST-scale datasets.

Introduction to exploring the Data Preview 0.3 (DP0.3) simulated catalogs of Solar System objects with the Rubin Science Platform (Sarah Greenstreet)
Data Preview 0 (DP0) is the first of three data previews during the period leading up to the start of Rubin Observatory Operations. The goals of DP0 are to serve as an early integration test of the Legacy Survey of Space and Time (LSST) Science Pipelines and the Rubin Science Platform (RSP) and to enable a limited number of scientists and students to begin early preparations for science with simulated LSST-like data sets. The DP0.3 data set contains simulated catalogs of Solar System objects and is currently accessible on the Rubin Science Platform for users to utilize in preparation for Rubin Observatory Operations. I will provide an overview of the DP0.3 simulated catalogs, the Rubin Solar System Data Products and processing pipeline, the Rubin Science Platform, and resources available to help the community get started with DP0.3 on the RSP.