Speaker
Description
The interpretation of precision measurements requires theory predictions with reliable and meaningful uncertainties and in particular correct correlations. Theory correlations are for example essential when fitting to differential spectra, but our default scale-variation-based methods, among their many shortcomings, are incapable of providing correct correlations. This is becoming a severe limitation in many precision studies.
Theory nuisance parameters (TNPs) overcome the limitations of scale variations.
After reviewing their basic idea (which was put forward some time ago), I will present as an example a concrete application of TNP-based uncertainty estimates for the resummed Drell-Yan $p_T$ spectrum, demonstrating how TNPs capture the correlations across the $p_T$ spectrum and between Z and W production. I will also show more generally that TNPs can provide statistically meaningful theory uncertainties.
