Bulletin of the American Physical Society
APS April Meeting 2021
Volume 66, Number 5
Saturday–Tuesday, April 17–20, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session H01: Data Science and Machine Learning in Particle and AstrophysicsInvited Live
|
Hide Abstracts |
Sponsoring Units: GDS Chair: Dimitri Bourilkov, University of Florida |
Sunday, April 18, 2021 10:45AM - 11:21AM Live |
H01.00001: Recent progresses in using Artificial Intelligence for Particle Physics Invited Speaker: David ROUSSEAU Use of Machine Learning in High Energy Physics is growing exponentially. I shall report on most recent advances in particular generative models to accelerate simulation, Invertible Neural Networks and Normalising Flows, anomaly detection for automatic data quality monitoring (and maybe new physics ?), and Graph Neural Networks applications. [Preview Abstract] |
Sunday, April 18, 2021 11:21AM - 11:57AM Live |
H01.00002: Cosmology in the machine learning era Invited Speaker: Francisco Villaescusa-Navarro Recent advances in deep learning are triggering a revolution across fields in science. In this talk I will show how these techniques can also benefit cosmology and astrophysics. I will present a new approach whose final goal is to extract every single bit of information from cosmological surveys. I will start showing the large amount of cosmological information that is embedded on small, non-linear, scales; information that cannot be retrieved using the traditional power spectrum. I will then show how neural networks can learn the optimal estimator needed to extract that information. I will discuss the role played by baryonic effects and point out how neural networks can automatically learn to marginalize over them. This approach requires combining machine learning techniques with numerical simulations. Along the talk, I will present the simulations we are using in this program: the Quijote and the CAMELS simulations. These two suites contain thousands of N-body and state-of-the-art (magneto-)hydrodynamic simulations covering a combined volume larger than the entire observable Universe (Quijote) and sampling the largest volume in parameter space for astrophysics models to-date (CAMELS). [Preview Abstract] |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700