Superstatistical random-matrix-theory approach to transition intensities in mixed systems

TL;DR

This paper introduces a superstatistical random matrix theory approach to model transition intensities in systems transitioning from chaos, providing an analytic distribution that aligns well with nuclear data and improves upon traditional models.

Contribution

It develops a new superstatistical framework for transition intensities in mixed systems, extending random matrix theory to better match experimental and nuclear model data.

Findings

Analytic distribution for transition probabilities in mixed systems

Better fit to experimental nuclear data than Porter-Thomas distribution

Applicable to systems transitioning out of chaos

Abstract

We study the fluctuation properties of transition intensities applying a recently proposed generalization of the random matrix theory, which is based on Beck and Cohen's superstatistics. We obtain an analytic expression for the distribution of the reduced transition probabilities that applies to systems undergoing a transition out of chaos. The obtained distribution fits the results of a previous nuclear shell model calculations for some electromagnetic transitions that deviate from the Porter-Thomas distribution. It agrees with the experimental reduced transition probabilities for the 26A nucleus better than the commonly used chi-squared distribution.