Special EPE Seminar: Jake Rudolph

US/Pacific
Henry J Lubatti (lubatti@uw.edu), Henry Lubatti (University of Washington (US)), Quentin Buat (University of Washington (US)), Shih-Chieh Hsu (University of Washington Seattle (US))
Description

Title: Autonomous Model Building with Reinforcement Learning: An Application with Neutrino Flavor Symmetries

Abstract:  To build models of Beyond the Standard Model physics, a theorist has many choices to make in regards to new fields, internal symmetries, and charge assignments, collectively creating an enormous space of possible models. We describe the development and findings of an Autonomous Model Builder (AMBer), which uses Reinforcement Learning (RL) to efficiently find models satisfying specified discrete flavor symmetries and particle content. Aside from valiant efforts by theorists following their intuition, these theory spaces are not deeply explored due to the vast number of possibilities and the time-consuming nature of building and fitting a model for a given symmetry group and particle assignment. The lack of any guarantee of continuity or differentiability prevents the application of typical machine learning approaches. We describe an RL software pipeline that interfaces with newly optimized versions of physics software, and apply it to the task of neutrino model building. Our agent learns to find fruitful regions of theory space, uncovering new models in commonly analyzed symmetry groups, and exploring for the first time previously unexamined symmetries.


Bio:  Jake Rudolph is a graduate student at UC Irvine focusing on machine learning applications in high-energy physics theory. His research aims to develop reinforcement learning techniques to help theorists explore complex model spaces. Jake holds a bachelor's degree from UCLA and previously worked at SLAC National Lab, where he developed software for the LCLS linear accelerator.

Zoom Meeting ID
66336943729
Host
Shih-Chieh Hsu
Alternative hosts
Quentin Buat, Henry Lubatti, Gordon Watts
Useful links
Join via phone
Zoom URL
    • 08:30 09:10
      Autonomous Model Building with Reinforcement Learning: An Application with Neutrino Flavor Symmetries 40m
      Speaker: Jake Rudolph (UC Irvine)