An analytical method is presented to calculate Lanczos coefficients governing Krylov complexity in the reduced pulsating fuzzy sphere version of the BMN matrix model for large and small deformations.
Random matrix theory for complexity growth and black hole interiors
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Krylov complexity is a canonical, parameter-independent measure of operator spreading that probes chaotic dynamics to late times and admits a geometric interpretation in holographic duals.
Krylov subspace methods efficiently describe quantum evolution, operator growth, and chaos in many-body systems, with metrics like Krylov complexity and applications in open systems, QFT, and quantum computing.
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Krylov state complexity for BMN matrix model
An analytical method is presented to calculate Lanczos coefficients governing Krylov complexity in the reduced pulsating fuzzy sphere version of the BMN matrix model for large and small deformations.
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Krylov Complexity
Krylov complexity is a canonical, parameter-independent measure of operator spreading that probes chaotic dynamics to late times and admits a geometric interpretation in holographic duals.
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Quantum Dynamics in Krylov Space: Methods and Applications
Krylov subspace methods efficiently describe quantum evolution, operator growth, and chaos in many-body systems, with metrics like Krylov complexity and applications in open systems, QFT, and quantum computing.