Kickstarter Colloquium Dec 5, 2022: Solar System Small Body Dynamics and Pulsating Stars

Описание: *Preparing for Astrophysics with LSST Program*
Kickstarter Science Colloquium held on Dec 5, 2022

Featuring:
*Solar System Small Body Dynamical Characterization in the LSST Era*
By Kat Volk

Dynamical analyses of the solar system’s small body populations have led to many important insights in planetary science. The dynamical evolution of an observed small body’s orbit can place it into context as, for example, a primordial small body that has remained largely unchanged since formation (like the New Horizons target Arrokoth in the Kuiper belt) or as an object that was captured into a mean motion resonance with a planet during the epoch of giant planet migration; both kinds of objects are critical for testing models of the solar system’s early dynamical history. In the past, the number of small bodies discovered in any new solar system survey has been small enough (~1000 objects) that dynamical analyses could be done in a human-intensive way (such as via visual inspection of numerical integration outputs). Given that LSST is expected to discover millions of main belt asteroids and tens of thousands of new transneptunian objects (amongst other small body populations!), we need a more robust approach to automated dynamical characterization! We used our LSST kickstarter funds to start developing a now NASA-funded open-source, user-friendly Python package that can take a small body orbit, perform dynamical integrations of its orbital evolution, calculate a variety of dynamical parameters, and output dynamical characterizations and classifications. I will briefly review the key dynamical parameters that are of most value for small body science, then show how machine learning can be a powerful tool for converting relatively simple, well-chosen time-series analysis of orbital integration results into robust dynamical classifications in the outer solar system.

*PulsationStarRecovery metric for LSST data*
By Vittorio Braga

Pulsating variable stars are precise standard candles and stellar population tracers. LSST will deliver ugrizy time series down to r~25, over a wide sky area, allowing to constrain their distance diagnostics with unprecedented precision. I will describe a new tool called PulsationStarRecovery, designed to quantify the recovery of the light curve period and amplitude from a Rubin LSST simulated time series. The metric takes, as input, synthetic light curves of Cepheids, RR Lyrae and Long-Period Variables from pulsation models, and gives as outputs the estimated pulsation properties (period, mean magnitude, pulsation amplitude…). PulsationStarRecovery is included within the MAF and its main purpose is to check how well the pulsation properties are recovered, depending on the observation strategy adopted, distance, coordinates, time of observation. I will show the results of a few tests for some realistic science cases, focussing on the Local Group galaxies.