Speaker
Description
The Legacy Survey of Space and Time (LSST) is expected to begin survey operations in 2026, and the resulting dataset will revolutionise our understanding of the Solar System. Its large on-sky footprint, fast cadence and deep limiting magnitude will probe small body populations to smaller sizes and larger distances than current ground based facilities, which will provide a fresh perspective on current population models.
LSST will be particularly beneficial for understanding small body populations in the inner Solar System, such as near-Earth objects (NEOs) and interstellar objects (ISOs). NEOs are objects which occupy orbits similar to the Earth’s and originate from perturbed main belt orbits, displaying heritage size distributions and signatures of thermal processing from the Sun. In contrast, ISOs are planetesimals which have been ejected from their original planetary system, macroscopic clues of exo-planetary formation processes which are observed as they pass through the Solar System. Both populations are predicted to increase in number by an order of magnitude from LSST discoveries alone, providing a higher level of detail for modeling the dynamical and physical evolution of Solar System objects and planetesimals from other planetary systems in the Galaxy.
Despite their distinct origins, NEOs and ISOs share similar observational biases in moving object discovery surveys: their apparent motion on-sky can be very large and their sizes are typically small, making discovery difficult for certain orbit or object types. Therefore, even though LSST will discover many new objects, it will also miss some. Information on these missed discoveries is equally important for understanding the intrinsic populations, so the careful debiasing of the LSST dataset will be crucial.
In this talk, I will describe ongoing efforts to develop debiasing tools at a larger scale and in a higher resolution than previously achieved. These tools can be used for any type of small body population and are model agnostic, meaning they are independent of current population theories. This approach will be especially critical for understanding the ISO discoveries expected from LSST, which will be the first self-consistent sample of ISOs.