Bristol Bayes for the Brain Workshop

11:00-12:00 14 June 2022 - Mike Peardon

Monte Carlo calculations in statistical mechanics and quantum field theories

Abstract: A review of how Monte Carlo methods enable current calculations of quantum field theories and statistical mechanics is presented. The talk will focus on the underlying stochastic algorithms used to estimate the high-dimensional integrals that appear when the Feynman path integrals of quantum fields or partition functions of thermodynamics are represented on a discrete space-time lattice. The development of methods to solve problems in this context have driven much of the progress in computational techniques based on statistical sampling and the Monte Carlo method and these connections will be presented.

Brief bio: Mike Peardon's research aims to improve the efficiency of Monte Carlo techniques in simulations of strongly interacting quantum field theories such as quantum chromodynamics (QCD), the theory of the strong nuclear force which binds quarks inside the protons and neutrons which make up the nucleus. The focus of his recent work is to improve the precision of theory predictions for hadron spectroscopy, hoping to make better connections with scattering data from experiments in high-energy colliders. Prior to joining the School of Mathematics, Trinity College Dublin in 2000 and after completing my Ph.D. at the University of Edinburgh, he was a postdoctoral research fellow in the University of California, San Diego, Forschungszentrum Juelich, Germany and the University of Kentucky.