Spacing Statistics of Energy Spectra: Random Matrices, Black Hole Thermalization, and Echoes
Krishan Saraswat, Niayesh Afshordi

TL;DR
This paper explores how the energy spectrum's statistical properties influence thermalization and echoes in black hole models, using random matrix theory and spectral form factors to connect quantum chaos with gravitational phenomena.
Contribution
It introduces a statistical framework for generating and analyzing random spectra, linking spectral statistics to black hole thermalization and echoes in holographic models.
Findings
Spectral form factor varies with different nearest neighbor statistics.
Late time oscillations can occur in $eta$-ensemble random matrix models.
Weakly coupled oscillators exhibit decaying spectral form factor oscillations.
Abstract
Recent advances in AdS/CFT holography have suggested that the near-horizon dynamics of black holes can be described by random matrix systems. We study how the energy spectrum of a system with a generic random Hamiltonian matrix affects its early and late time thermalization behaviour using the spectral form factor (which captures the time-dependence of two-point correlation functions). We introduce a simple statistical framework for generating random spectra in terms of the nearest neighbor spacing statistics of energy eigenvalues, enabling us to compute the averaged spectral form factor in a closed form. This helps to easily illustrate how the spectral form factor changes with different choices of nearest neighbor statistics ranging from the Poisson to Wigner surmise statistics. We suggest that it is possible to have late time oscillations in random matrix models involving…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
