1. MAUS: The MICE Analysis User Software
- Author
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R. B. S. Gardener, J. Martyniak, Kenneth Long, Ao Liu, Y. Karadzhov, E. Overton, A. Kurup, A. Dobbs, J. C. Nugent, Scott Wilbur, S. Middleton, R. Bayes, P. Franchini, T. A. Mohayai, K. Walaron, M. Winter, G. Kafka, C. Heidt, C. Pidcott, Yagmur Torun, V. Pec, C. Hunt, M. Uchida, F. Drielsma, V. Verguilov, David Colling, P. Kyberd, I. Taylor, Chris Rogers, Mike Rayner, E. M. Santos, M. Savic, D. Rajaram, J. J. Nebrensky, R. Asfandiyarov, D. Maletic, C. D. Tunnell, J. R. Greis, M. Littlefield, M. Bogomilov, Ivan Reid, Malcolm Ellis, P. Hanlet, M. Drews, M. Fedorov, V. Blackmore, Particle Physics and Astronomy Research Council (PPARC), The Royal Society, Council for the Central Laboratory of the Research Councils' (CCLRC), and Science and Technology Facilities Council (STFC)
- Subjects
Technology ,Integration testing ,FOS: Physical sciences ,computer.software_genre ,01 natural sciences ,030218 nuclear medicine & medical imaging ,PHYSICS ,03 medical and health sciences ,Load testing ,Software architectures (event data models, frameworks and databases) ,0302 clinical medicine ,Software ,0103 physical sciences ,Accelerator modelling and simulations (multiparticle dynamics ,single-particle dynamics) ,Instrumentation ,Instruments & Instrumentation ,Mathematical Physics ,Codebase ,computer.programming_language ,Code review ,Science & Technology ,010308 nuclear & particles physics ,business.industry ,GEOMETRY ,Python (programming language) ,Computational Physics (physics.comp-ph) ,Object (computer science) ,Nuclear & Particles Physics ,Software framework ,physics.comp-ph ,SIMULATION ,Operating system ,Simulation methods and programs ,business ,computer ,Physics - Computational Physics ,Data reduction methods - Abstract
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.
- Published
- 2018
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