  We present a new methodology that is able to yield a simultaneous
determination of the Parton Distribution Functions (PDFs) of the proton
alongside any set of parameters that determine the theory predictions; whether
within the Standard Model (SM) or beyond it. The SIMUnet methodology is based
on an extension of the NNPDF4.0 neural network architecture, which allows the
addition of an extra layer to simultaneously determine PDFs alongside an
arbitrary number of such parameters. We illustrate its capabilities by
simultaneously fitting PDFs with a subset of Wilson coefficients within the
Standard Model Effective Field Theory framework and show how the methodology
extends naturally to larger subsets of Wilson coefficients and to other SM
precision parameters, such as the strong coupling constant or the heavy quark
masses.
