Speaker
Dr.
Maria Zurita
(University of Santiago de Compostela)
Description
We discuss the Hessian PDF reweighting - a technique intended to estimate the effects that new measurements have on a set of PDFs. The method stems straightforwardly from considering new data in a usual χ2 fit and it naturally incorporates also non-zero values for the tolerance, Δχ2>1. In comparison to the contemporary Bayesian reweighting techniques, there is no need to generate large ensembles of PDF Monte-Carlo replicas, and the observables need to be evaluated only with the central and the error sets of the original PDFs. In spite of the apparently rather different methodologies, we show that the Hessian and the Bayesian techniques are actually one and the same, but only if the Δχ2 criterion is properly included to the Bayesian likelihood function that is a simple exponential. We illustrate the situation by considering a simplified example and the case of inclusive jets at the LHC.
We also apply the method to proton-lead and heavy ion (lead-lead) collisions to explore their constraining power on nuclear parton distributions.
Primary author
Dr.
Maria Zurita
(University of Santiago de Compostela)
Co-author
Dr.
Hannu Paukkunen
(University of Jyväskylä)