Astro Seminar Series - VIA ZOOM

Francisco Villaescusa-Navarro is an associate research scholar at Princeton University. He completed his PhD at the Instituto de Fisica Corpuscular in Valencia, Spain. He has held post-doctoral positions at the Trieste Observatory, Italy and the Flatiron Institute in New York City. Francisco is interested in studying cosmology using the large-scale structure of the Universe. More recently, he has been applying machine learning techniques to cosmology and astrophysics. Francisco is the main architect of the Quijote and CAMEL simulations.

Talk Title and Abstract:

Cosmology in the machine learning era

Machine learning is revolutionizing many fields. In this seminar I will present a new approach to do cosmology that aims at maximizing the scientific return of upcoming cosmological missions. I will start showing how neural networks can be used to extract cosmological information from all scales, including the highly non-linear regime that is affected by baryonic effects. This approach relies on having a large and accurate set of numerical simulations. I will introduce the Quijote and CAMEL simulations, two very large suites of cosmological simulations containing thousands of N-body and state-of-the-art (magento-)hydrodynamic simulations. I will describe how we can utilize these simulations to provide theory predictions for any observable, or entire density field, as a function of cosmology and astrophysics. These predictions can then be used to extract cosmological and astrophysical information from cosmological surveys.

Would you like to join this Zoom seminar?  Please email Donna Hayes.