Forecasting Dark Matter Physics with the Milky Way Satellite Galaxies: A Forward-Modeling Approach

  • Nuclear, Particle, Astroparticle and Cosmology (NUPAC) Seminars

April 22, 2025 2:00 PM
PAIS 3205

Host:
Francis-Yan Cyr-Racine
Presenter:
Soumyodipta Karmakar (UNM)
Zoom link
Understanding the fundamental properties of dark matter (DM) is a major objective in astrophysics and cosmology. In this talk, I will focus on recent work in which we forecast constraints on DM microphysics by modeling the satellite galaxy population of the Milky Way (MW). We develop a semi-analytic forward-modeling framework that stochastically simulates MW satellite populations under different DM scenarios, including cold DM (CDM), warm DM (WDM), and self-interacting DM (SIDM). The model incorporates key physical processes such as tidal and gravothermal evolution of DM subhalos. These synthetic populations are statistically compared to observed MW satellite data using Bayesian inference techniques, enabling quantitative forecasts of constraints on DM particle properties. The framework is designed to be both flexible and computationally efficient, making it well-suited for interpreting data from next-generation astronomical surveys.

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