Seminar by Rachel Somerville, CCA, Flatiron Institute

Monday, October 19, 2026, 3 PM in MP1318A/ Zoom

A new generation of multi-tracer surveys has the potential to yield huge progress in our understanding of galaxy formation and cosmology, but only if we can overcome certain challenges. These include accurately modeling the intertwined effects of baryonic processes and the nature of dark matter and dark energy, as well as incorporating diverse types of data and observational tracers into a robust statistical framework. I will discuss how my collaborators and I are working towards building more robust, physically motivated sub-grid models for star formation, stellar feedback, and black hole formation and growth. I will describe the status of our efforts to use these new models to train accelerated forward models using machine learning, create detailed multi-probe synthetic observations, and fold all of these elements into a Simulation Based Inference pipeline, with the ultimate goal of constraining galaxy formation, cosmology, and the initial conditions that gave rise to our Universe.

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