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Asfandiyarov, R.; Bayes, R.; Blackmore, V.; Bogomilov, M.; Colling, D.; Dobbs, A.J.; Drielsma, F.; Drews, M.; Ellis, M.; Fedorov, M.; Franchini, P.; Gardener, R.; Greis, J.R.; Hanlet, P.M.; Heidt, C.; Hunt, C.; Kafka, G.; Karadzhov, Y.; Kurup, A.; Kyberd, P.; Littlefield, M.; Liu, A.; Long, K.; Maletic, D.; Martyniak, J.; Middleton, S.; Mohayai, T.; Nebrensky, J.J.; Nugent, J.C.; Overton, E.; Pec, V.; Pidcott, C.E.; Rajaram, D.; Rayner, M.; Reid, I.D.; Rogers, C.T.; Santos, E.; Savic, M.; Taylor, I.; Torun, Y.; Tunnell, C.D.; Uchida, M.A.; Verguilov, V.; Walaron, K.; Winter, M.; Wilbur, S.
Journal of instrumentation, 04/2019, Volume: 14, Issue: 4Journal Article
The Muon Ionization Cooling Experiment (MICE) collaboration has developed the MICE Analysis User Software (MAUS) to simulate and analyze experimental data. It serves as the primary codebase for the experiment, providing for offline batch simulation and reconstruction as well as online data quality checks. The software provides both traditional particle-physics functionalities such as track reconstruction and particle identification, and accelerator physics functions, such as calculating transfer matrices and emittances. The code design is object orientated, but has a top-level structure based on the Map-Reduce model. This allows for parallelization to support live data reconstruction during data-taking operations. MAUS allows users to develop in either Python or C++ and provides APIs for both. Various software engineering practices from industry are also used to ensure correct and maintainable code, including style, unit and integration tests, continuous integration and load testing, code reviews, and distributed version control. The software framework and the simulation and reconstruction capabilities are described.
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