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Localization for random CMV matrices

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arxiv 2110.11386 v1 pith:3N4IUYW4 submitted 2021-10-21 math-ph math.DSmath.MPmath.PRmath.SP

Xiaowen Zhu This is my paper · ORCID
classification math-phmath.DSmath.MPmath.PRmath.SP
keywords localizationdynamicalmatricesrandomandersonarbitrarycoefficientsdistribution
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We prove Anderson localization (AL) and dynamical localization in expectation (EDL, also known as strong dynamical localization) for random CMV matrices for arbitrary distribution of i.i.d. Verblunsky coefficients.

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  1. Streamlined Krylov construction and classification of ergodic Floquet systems

    quant-ph 2024-12 conditional novelty 7.0 of 10

    A Szegő/CMV Krylov construction maps Floquet unitary dynamics to a five-diagonal chain, with a conjectured classification of chaos and integrability by Verblunsky coefficient asymptotics.

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