Neural network-based approach to phase space integration

Neural network-based approach to phase space integration

Monte Carlo methods are widely used in particle physics to integrate and sample probability distributions (differential cross sections or decay rates) on multi-dimensional phase spaces. We present a Neural Network (NN) algorithm optimized to perform this task. The algorithm has been applied to se...

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Bibliographic Details
Main Author:	Matthew D. Klimek, Maxim Perelstein
Format:	Article
Language:	English
Published:	SciPost 2020-10-01
Series:	SciPost Physics
Online Access:	https://scipost.org/SciPostPhys.9.4.053

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