The NNPDF collaboration has been using Machine Learning techniques to solve the inverse problem of extracting Parton Distribution Functions from finite sets of experimental data for almost two decades. With the increased precision of the LHC measurements, It has become mandatory to understand the robustness of the error bars and of the correlations in the results of PDFs fit. We review the...
Lattice field theory computations of two-point functions are generally
affected by the so called signal to noise problem, wherein the signal
of the Euclidean time correlator decays faster than the variance. In
this talk we propose a different perspective on the origin of this
problem. Following this, we argue that by writing correlators as
derivatives with respect to sources and...
