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

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arxiv 2309.14027 v3 pith:FYJ7SC6T submitted 2023-09-25 physics.ins-det hep-exstat.ML

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

classification physics.ins-det hep-exstat.ML
keywords detectorsoptimisationsoftwaremuonparticletomographytomoptapplications
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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