Apprentice for Event Generator Tuning

Krishnamoorthy, Mohan; Schulz, Holger; Ju, Xiangyang; Wang, Wenjing; Leyffer, Sven; Marshall, Zachary; Mrenna, Stephen; Müller, Juliane; Kowalkowski, James B.

DOE OSTI · 1780593

Apprentice for Event Generator Tuning

Krishnamoorthy, Mohan·Schulz, Holger·Ju, Xiangyang·Wang, Wenjing·Leyffer, Sven·Marshall, Zachary·Mrenna, Stephen·Müller, Juliane·Kowalkowski, James B.

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Abstract

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.

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BibTeX RIS

Krishnamoorthy, Mohan, Schulz, Holger, Ju, Xiangyang, Wang, Wenjing, Leyffer, Sven, Marshall, Zachary, Mrenna, Stephen, Müller, Juliane, Kowalkowski, James B.. 2021-03-09. Apprentice for Event Generator Tuning. https://www.osti.gov/biblio/1780593

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