Speaker
Description
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. A possible solution to the problem can be found by
expressing the Euclidean correlators as derivatives with respect to
sources in the action. Following this, two methods are presented, one as an extension
of reweighting methods, and another inspired in the ideas of numerical
stochastic perturbation theory. Both approaches involve 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.