Speaker
Description
We present a new extension to the toolbox of parton-distribution reweighting methods, which enables a general user to study the impact of an updated theory prediction on the results of a pre-existing parton-distribution global analysis. This new method is a combination of the well-known reweighting method with a new deweighting variant where a dataset is removed from the original analysis in an approximative way. Specific use cases of this method could include e.g. testing the impact of updating the treatment of an observable from NnLO to Nn+1LO precision in the global analysis, or of including previously ignored electroweak, mass, or higher-twist effects, or even testing the impact of some beyond-standard-model physics. We discuss the implementation of this method in the Hessian formalism, and show its use in a single case study.
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