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A Python Library for Longitudinal Beam Tomography

Measuring the longitudinal phase space distribution of particle beams is needed for a myriad of purposes. Among these are machine calibration and bunch quality assessment. Since the tomographic reconstruction algorithm was developed, it has been a vital part of operation at CERN. The current pr...

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Detalles Bibliográficos
Autor principal: Grindheim, Christoffer Hjerto
Lenguaje:eng
Publicado: 2020
Materias:
Acceso en línea:http://cds.cern.ch/record/2717822
Descripción
Sumario:Measuring the longitudinal phase space distribution of particle beams is needed for a myriad of purposes. Among these are machine calibration and bunch quality assessment. Since the tomographic reconstruction algorithm was developed, it has been a vital part of operation at CERN. The current program is outdated, complex and hard to develop further. Its functionality should be able to be customised for each machine, and for the needs of the individual users. For this reason, a new version must be developed, able to serve the wide range of requirements the future might bring. This dissertation describes the translation from a program written in highly optimised Fortran95 code, to a modular Python library. It also addresses experiments with a hardware accelerated implementation of the tomographic reconstruction routine. Finally, the code is profiled with respect to both output quality and run time, and it is confirmed that it is ready for operational usage.