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Efficient Forward-Mode Algorithmic Derivatives of Geant4

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arxiv 2407.02966 v1 pith:VYIDKOFO submitted 2024-07-03 physics.comp-ph

Max Aehle , Xuan Tung Nguyen , Mihály Novák , Tommaso Dorigo , Nicolas R. Gauger , Jan Kieseler , Markus Klute , Vassil Vassilev This is my paper · ORCID
classification physics.comp-ph
keywords geant4algorithmicanalysisderivativesdifferentiatedforward-modeoperator-overloadinguser-defined
verification ladder T0 review T1 audit T2 compute T3 formal
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We have applied an operator-overloading forward-mode algorithmic differentiation tool to the Monte-Carlo particle simulation toolkit Geant4. Our differentiated version of Geant4 allows computing mean pathwise derivatives of user-defined outputs of Geant4 applications with respect to user-defined inputs. This constitutes a major step towards enabling gradient-based optimization techniques in high-energy physics, as well as other application domains of Geant4. This is a preliminary report on the technical aspects of applying operator-overloading AD to Geant4, as well as a first analysis of some results obtained by our differentiated Geant4 prototype. We plan to follow up with a more refined analysis.

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    A reinforcement learning agent that sequentially places detector components produced calorimeter and spectrometer designs that outperform hand-made baselines in simulation.

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