Statistical properties of levels and lines in complex spectra

TL;DR

This paper reviews recent advances in the statistical analysis of complex atomic spectra, focusing on modeling line distributions, transition array properties, and analytical formulas for line counts, enhancing understanding of atomic spectral complexity.

Contribution

It introduces improved statistical methods for modeling spectral lines, extends existing models for electron configuration distributions, and derives a new analytical formula for E1 line counts.

Findings

Enhanced statistical models incorporating high-order moments and different distributions.

Extended the P(M) distribution model for configurations with high-l spectators.

Derived a new analytical formula for counting E1 lines with broader applicability.

Abstract

We review recent developments of the statistical properties of complex atomic spectra, based on the pioneering work of Claire Bauche-Arnoult and Jacques Bauche. We discuss several improvements of the statistical methods (UTA, SOSA) for the modeling of the lines in a transition array: impact of high-order moments, choice of the distribution (Generalized Gaussian, Normal Inverse Gaussian) and corrections at low temperatures. The second part of the paper concerns general properties of transition arrays, such as propensity rule and generalized J-file sum rule (for E1 or E2 lines), emphasizing the particular role of the G1 exchange Slater integral. The statistical modeling introduced by J. Bauche and C. Bauche-Arnoult for the distribution of the M values (projection of total angular momentum J) in an electron configuration, written P(M), was extended in order to account for configurations with a high-l spectator and a new analytical formula for the evaluation of the number of E1 lines with a wider range of applicability was derived.