TomOpt: differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography

Author:

Strong Giles C,Lagrange MaximeORCID,Orio AitorORCID,Bordignon Anna,Bury FlorianORCID,Dorigo TommasoORCID,Giammanco AndreaORCID,Heikal Mariam,Kieseler JanORCID,Lamparth Max,Martínez Ruíz del Árbol PabloORCID,Nardi FedericoORCID,Vischia PietroORCID,Zaraket HaithamORCID

Abstract

Abstract We describe a software package, TomOpt, developed to optimise the geometrical layout and specifications of detectors designed for tomography by scattering of cosmic-ray muons. The software exploits differentiable programming for the modeling of muon interactions with detectors and scanned volumes, the inference of volume properties, and the optimisation cycle performing the loss minimisation. In doing so, we provide the first demonstration of end-to-end-differentiable and inference-aware optimisation of particle physics instruments. We study the performance of the software on a relevant benchmark scenario and discuss its potential applications. Our code is available on Github (Strong et al 2024 available at: https://github.com/GilesStrong/tomopt).

Funder

Fonds De La Recherche Scientifique - FNRS

Horizon 2020 Framework Programme

Deutsche Forschungsgemeinschaft

Ministerio de Ciencia e Innovación

Publisher

IOP Publishing

Reference46 articles.

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