STAR task force for tuning PYTHIA

[Raghav Kunnawalkam Elayavalli <kunnawalkamraghav AT gmail.com>]

Title: Apprentice for Event Generator Tuning
Authors: Mohan Krishnamoorthy, Holger Schulz, Xiangyang Ju, Wenjing Wang, Sven
 Leyffer, Zachary Marshall, Stephen Mrenna, Juliane Muller, James B.
 Kowalkowski
Categories: hep-ex hep-ph physics.comp-ph
Comments: 9 pages, 2 figures, submitted to the 25th International Conference on
 Computing in High-Energy and Nuclear Physics
\\
 Apprentice is a tool developed for event generator tuning. It contains a
range of conceptual improvements and extensions over the tuning tool Professor.
Its core functionality remains the construction of a multivariate analytic
surrogate model to computationally expensive Monte-Carlo event generator
predictions. The surrogate model is used for numerical optimization in
chi-square minimization and likelihood evaluation. Apprentice also introduces
algorithms to automate the selection of observable weights to minimize the
effect of mis-modeling in the event generators. We illustrate our improvements
for the task of MC-generator tuning and limit setting.
\\ ( https://arxiv.org/abs/2103.05748 ,  9872kb)
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Cheers

Raghav 

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Raghav Kunnawalkam Elayavalli

email: raghav.ke AT yale.edu 

Associate Research Scientist  

Yale University and 

Brookhaven National Lab

<he/him/his>

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