1pm - 2pm: The Signal to Noise problem and Stochastic Automatic Differentiation

Lattice field theory allows for the direct computation of physical quantities in strongly coupled theories. In particular, numerical Monte Carlo simulations using Euclidean correlation functions give direct access to the energy spectrum of the theory.  However, the fast degradation of the signal with the Euclidean time, known as the signal to noise problem, significantly affects the precision of such computations.  After introducing the topic and expressing the Euclidean correlators as derivatives with respect to sources in the action, a potential solution to the problem will be presented.  This approach involves the concept of Automatic Differentiation, which requires
an extension to stochastic processes, in particular for its use in Monte Carlo simulations.  Results will be shown in a four-dimensional scalar theory.