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Recent Developments in Longitudinal Phase Space Tomography

Longitudinal phase space tomography has been a mainstay of longitudinal beam diagnostics in most of the CERN synchrotrons for over two decades. Originally, the reconstructions were performed by a highly optimised Fortran implementation. To facilitate increased flexibility, and leveraging the signifi...

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Detalles Bibliográficos
Autores principales: Albright, Simon, Grindheim, Christoffer, Lasheen, Alexandre, Lu, Anton
Lenguaje:eng
Publicado: 2022
Materias:
Acceso en línea:https://dx.doi.org/10.18429/JACoW-IPAC2022-MOPOPT043
http://cds.cern.ch/record/2845831
Descripción
Sumario:Longitudinal phase space tomography has been a mainstay of longitudinal beam diagnostics in most of the CERN synchrotrons for over two decades. Originally, the reconstructions were performed by a highly optimised Fortran implementation. To facilitate increased flexibility, and leveraging the significant increase in computing power since the original development, a new version of the reconstruction code has been developed. This implements an object-oriented Python API, with the computationally heavy calculations in C++ for improved performance. The Python/C++ implementation is designed to be highly modular, enabling new and diverse use cases. For example, the macro-particle tracking for the tomography can now be performed externally, or a single set of tracked particles can be reused for multiple reconstructions. This paper summarises the features of the new implementation, and some of the key applications that have been enabled as a result.