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Main Author: Humbert, Philippe
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2408.04971
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author Humbert, Philippe
author_facet Humbert, Philippe
contents Methods used to infer nuclear parameters from neutron count statistics fall into two categories depending on whether they use moments or count number probabilities. As probabilities are in general more difficult to calculate, we are interested here in the reconstruction of distributions from their first moments. For this, we explore two approaches. The first one relies on a generalization of the 2-forked branching correlation (quadratic) approximation used in the PMZBB and Poisson radical distributions, the second one is based on the expansion of the distribution on a basis of Meixner discrete orthogonal polynomials.
format Preprint
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institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Neutron multiplicity counting distribution reconstruction from moments using Meixner polynomial expansion and N-forked branching approximations
Humbert, Philippe
Nuclear Theory
Mathematical Physics
Methods used to infer nuclear parameters from neutron count statistics fall into two categories depending on whether they use moments or count number probabilities. As probabilities are in general more difficult to calculate, we are interested here in the reconstruction of distributions from their first moments. For this, we explore two approaches. The first one relies on a generalization of the 2-forked branching correlation (quadratic) approximation used in the PMZBB and Poisson radical distributions, the second one is based on the expansion of the distribution on a basis of Meixner discrete orthogonal polynomials.
title Neutron multiplicity counting distribution reconstruction from moments using Meixner polynomial expansion and N-forked branching approximations
topic Nuclear Theory
Mathematical Physics
url https://arxiv.org/abs/2408.04971