Spectral and Parametric Averaging for Integrable Systems

TL;DR

This paper compares spectral and parametric ensemble averaging methods in quantum chaos, introducing a new rescaled spectral averaging technique that better captures spectral correlations and oscillations.

Contribution

It introduces rescaled spectral averaging and evaluates its advantages over traditional methods in describing spectral statistics of integrable systems.

Findings

Rescaled spectral averaging captures spectral staircase correlations.

Parametric averaging better describes saturation level rigidity.

Rescaled spectral averaging produces persistent oscillations in spectral statistics.

Abstract

We analyze two theoretical approaches to ensemble averaging for integrable systems in quantum chaos - spectral averaging and parametric averaging. For spectral averaging, we introduce a new procedure - rescaled spectral averaging. Unlike traditional spectral averaging, it can describe the correlation function of spectral staircase and produce persistent oscillations of the interval level number variance. Parametric averaging, while not as accurate as rescaled spectral averaging for the correlation function of spectral staircase and interval level number variance, can also produce persistent oscillations of the global level number variance and better describes saturation level rigidity as a function of the running energy. Overall, it is the most reliable method for a wide range of statistics.