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Multiseed Krylov complexity

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arxiv 2409.15666 v2 pith:SRSHGTZB submitted 2024-09-24 quant-ph hep-th

Multiseed Krylov complexity

classification quant-ph hep-th
keywords complexitykrylovoperatorschaoticcollectiondynamicalevolutioninitial
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Krylov complexity is an attractive measure for the rate at which quantum operators spread in the space of all possible operators under dynamical evolution. One expects that its late-time plateau would distinguish between integrable and chaotic dynamics, but its ability to do so depends precariously on the choice of the initial seed. We propose to apply such considerations not to a single operator, but simultaneously to a collection of initial seeds in the manner of the block-Lanczos algorithm. We furthermore suggest that this collection should comprise all simple (few-body) operators in the theory, which echoes the applications of Nielsen complexity to dynamical evolution. The resulting construction, unlike the conventional Krylov complexity, reliably distinguishes integrable and chaotic Hamiltonians without any need for fine-tuning.

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Cited by 10 Pith papers

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

  1. Polynomial Initial-State Jumps and Christoffel Transforms in Krylov Complexity

    hep-th 2026-07 conditional novelty 7.0

    Changing the initial state to Q(H)|K0⟩ is exactly a Christoffel reweighting of the spectral measure by |Q|²; Krylov complexity then transfers from the reference problem through finite-band connectors and finite-rank k...

  2. Polynomial Initial-State Jumps and Christoffel Transforms in Krylov Complexity

    hep-th 2026-07 accept novelty 7.0

    Polynomial changes of the initial state in Krylov complexity are solved exactly via Christoffel transforms of the spectral measure, yielding finite-band amplitude transfer and projected-kernel complexity formulas with...

  3. Holographic Krylov Complexity for Charged, Composite and Extended Probes

    hep-th 2026-04 unverdicted novelty 7.0

    Holographic Krylov complexity for charged composite and extended probes retains universal leading large-time growth but acquires structure-dependent subleading corrections.

  4. Holographic Spread Complexity from Branes and Strings

    hep-th 2026-06 unverdicted novelty 6.0

    D0-branes in ABJM, rotating D3-branes, and wound strings realize holographic spread complexity via proper momentum and Routhian prescriptions that match short-time Krylov behavior.

  5. Controlled Chaos in 4D SCFTs

    hep-th 2026-06 unverdicted novelty 6.0

    Orbifolds of N=4 SYM produce SCFTs whose dilatation operator in a subsector is realized by a tunable spin chain whose eigenvalue statistics exhibit chaos for specific marginal couplings.

  6. Bridging Krylov Complexity and Universal Analog Quantum Simulator

    quant-ph 2026-05 unverdicted novelty 6.0

    Generalized Krylov complexity predicts the minimum time to realize target operations in analog quantum simulators such as Rydberg atom arrays.

  7. Black Hole States in Quantum Spin Chains

    hep-th 2025-12 conditional novelty 6.0

    An equal-weight superposition of all non-crossing singlet pairings in a Heisenberg chain shows logarithmic entanglement growth (c≈5.2) and near-infinite-temperature thermalization.

  8. Quantum Cosmology in Krylov Space: Complexity and Entropy

    gr-qc 2025-11 conditional novelty 6.0

    In a sharply peaked Gaussian state of a flat FLRW universe with a massless scalar clock, Krylov state complexity grows as σ²(φ−φ0)²/4 and operator complexity is exactly twice that, in both Wheeler-DeWitt and loop quan...

  9. Emergence of Krylov complexity through quantum walks: An exploration of the quantum origins of complexity

    hep-th 2026-02 conditional novelty 5.0

    Reducing a graph walk to distance-layers reproduces Krylov/spread complexity, yielding analytic finite-q SYK Lanczos coefficients and hypercube complexity D sin²(t/D), with faster saturation than classical-walk circuits.

  10. A Quantum Computational Perspective on Spread Complexity

    hep-th 2025-06 unverdicted novelty 5.0

    Spread complexity is recovered as the infinitesimal-time limit of a circuit complexity defined by minimal-cost synthesis with time-evolution and beam-splitting operations.