Abstract:

Recent measurements have reached sub-percent accuracy, opening the door to detailed studies of theoretical inputs that are crucial within the Standard Model. Given this level of precision — and the fact that an accurate description of the qT spectrum involves many different theoretical ingredients — a robust treatment of theoretical predictions and their associated uncertainties is essential. Among these, perturbative uncertainties remain dominant and are traditionally estimated via scale variations. However, this method has well-known limitations.

In this talk, I will present a novel approach based on theory nuisance parameters (TNPs) to quantify such uncertainties. This method properly accounts for theoretical correlations and enables the data itself to constrain, and potentially reduce, these uncertainties in a consistent way. To illustrate the potential of this framework, I will discuss an ongoing project involving the extraction of alphas(mZ) and its uncertainty using fits to pseudodata, analyzing both perturbative and non-perturbative uncertainties. Although this study does not yet include other subdominant sources of theoretical uncertainty, which will be addressed in future extractions of alphas(mZ) from real experimental data, I will briefly comment on the recent CMS mW determination, which successfully employed TNPs as part of its uncertainty modeling.

Zoom-Link:

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