Spectral chaos bounds from scaling theory of maximally efficient quantum-dynamical scrambling

A key conjecture about the evolution of complex quantum systems towards an ergodic steady state, known as scrambling, is that this process acquires universal features when it is most efficient. We develop a single-parameter scaling theory for the spectral statistics in this scenario, which embodies exact self-similarity of the spectral correlations along the complete scrambling dynamics. We establish that the scaling predictions are matched by a privileged stochastic process and serve as bounds for other dynamical scrambling scenarios, allowing one to quantify inefficient or incomplete scrambling on all time scales.

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Publication Details

Journal
Quantum
Published
2025-02-26
DOI
https://doi.org/10.22331/q-2025-02-26-1651
Citations
1
Primary Topic
Quantum chaos and dynamical systems
Type
article
Field-Weighted Citation Impact
1.32
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article

Spectral chaos bounds from scaling theory of maximally efficient quantum-dynamical scrambling

Henning Schomerus, Tara Kalsi, Alessandro Romito
1 citations
Quantum
Quantum chaos and dynamical systems
1.32
article

Spectral chaos bounds from scaling theory of maximally efficient quantum-dynamical scrambling

Henning Schomerus, Tara Kalsi, Alessandro Romito
article en
1 citations

Abstract

A key conjecture about the evolution of complex quantum systems towards an ergodic steady state, known as scrambling, is that this process acquires universal features when it is most efficient. We develop a single-parameter scaling theory for the spectral statistics in this scenario, which embodies exact self-similarity of the spectral correlations along the complete scrambling dynamics. We establish that the scaling predictions are matched by a privileged stochastic process and serve as bounds for other dynamical scrambling scenarios, allowing one to quantify inefficient or incomplete scrambling on all time scales.

QuantumVol. 9
Lancaster University (GB)
Openalex Percentile: Top 22%
Quantum chaos and dynamical systems
1.32
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