[PAST EVENT] Physics Colloquium - Jeremy Wolcott

March 22, 2024
4pm - 5pm
Location
Small Hall, Room 111
300 Ukrop Way
Williamsburg, VA 23185Map this location
Access & Features
  • Open to the public
outdoors, outside, people, colonial williamsburg, fifes and drums, trees, flowers, uniforms, mason, miller hall, business school, courtyards, trees, miller hall

Dr. Jeremy Wolcott, Postdoctoral Research Associate, Tufts University, Title of talk: Multifaceted Nu Insights: Harnessing MCMC to Inspect Neutrino Oscillations From Every Angle

Abstract: Neutrinos are among the most unusual of the fundamental particles known in modern physics. Besides interacting with ordinary matter so rarely that supermassive detectors or extremely intense sources are required to even observe them, and being separated from the other fundamental fermions by at least six orders of magnitude in mass, neutrinos' “flavor oscillations” exhibit a rich phenomenology that may at last give us hints as to where we should look beyond current theory for new fundamental insights. The discovery of an underlying symmetry in the way the neutrino states interact with one another or the way the neutrinos' masses are arranged, for instance, or the violation of symmetries between neutrinos and their antimatter counterparts, could have profound consequences for both particle physics and cosmology.

However, contemporary experiments attempting to access this phenomenology must grapple with its numerous degeneracies and multiple degrees of freedom. In this talk, I will discuss how Bayesian Markov Chain Monte Carlo (MCMC) is being used to simultaneously examine many different aspects of neutrino oscillation measurements with an efficient computing approach. I will review its applications to current data from the NOvA experiment at Fermilab, and show how we obtain insights into both the underlying physical system and our instrumental setup. I will conclude with some thoughts about MCMC's promise for future neutrino oscillation measurements.





Sponsored by: Physics