aiqbench analysis
This research establishes a direct link between quantum random walks on graphs and Krylov complexity, enabling the analytic computation of Lanczos coefficients for the SYK model and a full characterization of the hypercube graph. The study reveals that quantum speed-ups can cause complexity saturation to occur significantly faster than predictions based on random unitary circuits, offering new insights into the relationship between Krylov and circuit complexities in black hole physics.
Emergence of Krylov complexity through quantum walks: An exploration of the quantum origins of complexity
arXiv:2602.04949v3 Announce Type: replace-cross Abstract: In this work we study the relationship between quantum random walks on graphs and Krylov/spread complexity. We show that the latter's definition naturally emerges through a canonical method of reducing a graph to a chain, on which we can identify the usual Krylov structure. We use this identification to construct families of graphs corresponding to special classes of systems with known complexity features and conversely, to compute Krylov complexity for graphs of physical interest. The two main outcomes are the analytic computation of the Lanczos coefficients for the SYK model for an arbitrary number $q$ of interacting fermions and the complete characterization of Krylov complexity for the hypercube graph in any number of dimensions. The latter serves as the starting point for an in-depth comparison between Krylov and circuit complexities as they purportedly arise in the context of black holes. We find that while under certain conditions Krylov complexity follows the growth and saturation pattern ascribed to such systems, the timescale at which saturation happens can generally be shorter than what is predicted by random unitary circuits, due to the effects of quantum speed-ups commonly occurring when comparing quantum and classical random walks.
Abstract:In this work we study the relationship between quantum random walks on graphs and Krylov/spread complexity. We show that the latter's definition naturally emerges through a canonical method of reducing a graph to a chain, on which we can identify the usual Krylov structure. We use this identification to construct families of graphs corresponding to special classes of systems with known complexity features and conversely, to compute Krylov complexity for graphs of physical interest. The two main outcomes are the analytic computation of the Lanczos coefficients for the SYK model for an arbitrary number $q$ of interacting fermions and the complete characterization of Krylov complexity for the hypercube graph in any number of dimensions. The latter serves as the starting point for an in-depth comparison between Krylov and circuit complexities as they purportedly arise in the context of black holes. We find that while under certain conditions Krylov complexity follows the growth and saturation pattern ascribed to such systems, the timescale at which saturation happens can generally be shorter than what is predicted by random unitary circuits, due to the effects of quantum speed-ups commonly occurring when comparing quantum and classical random walks.
High Energy Physics - Theory (hep-th); Strongly Correlated Electrons (cond-mat.str-el); Quantum Physics (quant-ph)
arXiv:2602.04949 [hep-th]
(or arXiv:2602.04949v3 [hep-th] for this version)
Full text under the publisher's open licence · 214 words
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