Machine learning efforts in Sherpa
نویسندگان
چکیده
Abstract Modern machine learning methods offer great potential for increasing the efficiency of Monte Carlo event generators. We present latest developments in context SHERPA generation framework. These include phase space sampling amended by normalizing flows and a new unweighting procedure based on neural-network surrogates full matrix elements. discuss corresponding general construction criteria show examples gains selected LHC production processes.
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ژورنال
عنوان ژورنال: Journal of Physics: Conference Series
سال: 2023
ISSN: ['1742-6588', '1742-6596']
DOI: https://doi.org/10.1088/1742-6596/2438/1/012144