Machine learning-based longitudinal phase space prediction of particle accelerators
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DOI: 10.1103/physrevaccelbeams.21.112802
Abstract: We report on the application of machine learning (ML) methods for predicting the longitudinal phase space (LPS) distribution of particle accelerators. Our approach consists of training a ML-based virtual diagnostic to predict the LPS using… read more here.
Keywords: machine learning; longitudinal phase; phase space; particle ... See more keywords