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Krylov Complexity and Spectral Form Factor for Noisy Random Matrix Models

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arxiv 2307.15495 v3 pith:OH5OKJVI submitted 2023-07-28 hep-th quant-ph

classification hep-thquant-ph
keywords spectralcomplexityfactorformmodelsquantumkrylovnoise
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We study the spectral properties of two classes of random matrix models: non-Gaussian RMT with quartic and sextic potentials, and RMT with Gaussian noise. We compute and analyze the quantum Krylov complexity and the spectral form factor for both of these models. We find that both models show suppression of the spectral form factor at short times due to decoherence effects, but they differ in their long-time behavior. In particular, we show that the Krylov complexity for the non-Gaussian RMT and RMT with noise deviates from that of a Gaussian RMT. We discuss the implications and limitations of our results for quantum chaos and quantum information in open quantum systems. Our study reveals the distinct sensitivities of the spectral form factor and complexity to non-Gaussianity and noise, which contribute to the observed differences in the different time domains.

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Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Analytic Spread Complexity from Level Statistics: From Chaos to Integrability

    hep-th 2026-08 conditional novelty 7.0 of 10

    The finite-time peak of spread complexity is controlled by the Fourier transform of the nearest-neighbour energy-level spacing distribution.

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  3. Dynamics of monitored SSH Model in Krylov Space: From Complexity to Quantum Fisher Information

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  4. Higher-Order Krylov State Complexity in Random Matrix Quenches

    hep-th 2024-12 conditional novelty 5.0 of 10

    Higher-order generalized spread complexities show a more pronounced pre-equilibration peak than standard spread complexity in random matrix quenches, quantifying chaos more sharply up to third order.

  5. Statistics and Complexity of Wavefunction Spreading in Quantum Dynamical Systems

    quant-ph 2024-11 conditional novelty 5.0 of 10

    The moments of the spreading-operator measurement distribution are generalized spread complexities, which for GUE Hamiltonians peak more sharply at higher order and obey a norm bound.

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