Event generator tuning using Bayesian optimization
Monte Carlo event generators contain a large number of parameters that must be determined by comparing the output of the generator with experimental data. Generating enough events with a fixed set of parameter values to enable making such a comparison is extremely CPU intensive, which prohibits perf...
Main Authors: | , , , , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
IOP Publishing,
2019-03-01T16:40:11Z.
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Subjects: | |
Online Access: | Get fulltext |