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arxiv: 2205.12815 · v1 · pith:JVXXRUJV · submitted 2022-05-25 · hep-th · cond-mat.stat-mech· quant-ph

Krylov complexity and orthogonal polynomials

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classification hep-th cond-mat.stat-mechquant-ph
keywords polynomialscomplexitykrylovorthogonalbasisadaptedalgorithmanalytically
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Krylov complexity measures operator growth with respect to a basis, which is adapted to the Heisenberg time evolution. The construction of that basis relies on the Lanczos algorithm, also known as the recursion method. The mathematics of Krylov complexity can be described in terms of orthogonal polynomials. We provide a pedagogical introduction to the subject and work out analytically a number of examples involving the classical orthogonal polynomials, polynomials of the Hahn class, and the Tricomi-Carlitz polynomials.

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Cited by 9 Pith papers

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

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  3. q-Askey Deformations of Double-Scaled SYK

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    q-Askey deformations of DSSYK produce transfer matrices from basic orthogonal polynomials whose chord numbers map to ER bridge lengths and signal geometric transitions with discrete spectra in sine dilaton gravity.

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  7. On the Universality of Probe Complexity in $\mathcal{N}=4$ SYM

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