Academic Journal
TomOpt: differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography
| Τίτλος: | TomOpt: differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography |
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| Συγγραφείς: | Strong, Giles C, Author, Lagrange, Maxime, Author, Orio, Aitor, Author, Bordignon, Anna, Author, Bury, Florian, Author, Dorigo, Tommaso, Author, Giammanco, Andrea, Author, Heikal, Mariam, Author, Kieseler, Jan, Author, Lamparth, Max, Author, Martínez Ruíz del Árbol, Pablo, Author, Nardi, Federico, Author, Vischia, Pietro, Author, Zaraket, Haitham, Author |
| Συνεισφορές: | Strong, Giles C, Author, Lagrange, Maxime, Author, Orio, Aitor, Author, Bordignon, Anna, Author, Bury, Florian, Author, Dorigo, Tommaso, Author, Giammanco, Andrea, Author, Heikal, Mariam, Author, Kieseler, Jan, Author, Lamparth, Max, Author, Martínez Ruíz del Árbol, Pablo, Author, Nardi, Federico, Author, Vischia, Pietro, Author, Zaraket, Haitham, Author |
| Πηγή: | Machine Learning. 5(3) |
| Θεματικοί όροι: | detector design, differentiable programming, differentiable optimisation, end-to-end optimisation, muon tomography, inference aware learning, automatic differentiation, Machine Learning, Maskininlärning |
| Περιγραφή: | 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). |
| Περιγραφή αρχείου: | electronic |
| Σύνδεσμος πρόσβασης: | https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-108312 https://doi.org/10.1088/2632-2153/ad52e7 |
| Βάση Δεδομένων: | SwePub |
| ISSN: | 26322153 |
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| DOI: | 10.1088/2632-2153/ad52e7 |