Random matrix theory analysis of a temperature-related transformation in statistics of Fano-Feshbach resonances in Thulium atoms

TL;DR

This study uses random matrix theory simulations to analyze temperature-related changes in Fano-Feshbach resonance statistics in thulium atoms, finding that Stark shifts alone do not explain the observed transition to chaos.

Contribution

The paper demonstrates through simulations that Stark shifts are insufficient to account for the temperature-induced statistical transformation, suggesting other mechanisms are involved.

Findings

Resonance statistics remain largely unchanged with temperature when only Stark shifts are considered.

Including Stark shifts causes minor statistical changes, but does not explain the observed transition to chaos.

Additional mechanisms beyond Stark shifts likely influence the resonance statistics at higher temperatures.

Abstract

Recently, transformation from random to chaotic behavior in the statistics of Fano-Feshbach resonances was observed in thulium atoms with rising ensemble temperature. We performed random matrix theory simulations of such spectra and analyzed the resulting statistics. Our simulations show that, when evaluated in terms of the Brody parameter, resonance statistics do not change or change insignificantly with rising temperature if temperature is the only changing parameter. In the experiments evaluated, temperature was changed simultaneously with optical dipole trap depth. Thus, simulations included the Stark shift based on the known polarizability of the free atoms and assuming their polarizability remains the same in the bound state. Somewhat surprisingly, we found that, while including the Stark shift does lead to minor statistical changes, it does not change the resonance statistics and, therefore, is not responsible for the experimentally observed statistic transformation. This observation suggests that either our assumption regarding the polarizability of Feshbach molecules is poor or that an additional mechanism changes the statistics and leads to more chaotic statistical behavior.