We illustrate how Bayesian reweighting can be used to incorporate the
constraints provided by new measurements into a global Monte Carlo
analysis of the Standard Model Effective Field Theory (SMEFT). This
method, extensively applied to study the impact of new data on the
parton distribution functions of the proton, is here validated by means
of our recent SMEFiT analysis of the top quark sector. We show how,
under well-defined conditions and for the SMEFT operators directly
sensitive to the new data, the reweighting procedure is equivalent to a
corresponding new fit. We quantify the amount of information added to
the SMEFT parameter space by means of the Shannon entropy and of the
Kolmogorov-Smirnov statistic. We investigate the dependence of our
results upon the choice of alternative expressions of the weights.
Constraining the SMEFT with Bayesian reweighting