Operator complexity: a journey to the edge of Krylov space

TL;DR

This paper investigates the growth of Krylov complexity in chaotic and integrable quantum systems, providing rigorous bounds and numerical analysis that distinguish chaotic from integrable dynamics.

Contribution

It offers the first rigorous bounds on K-complexity for long times and compares chaotic SYK$_4$ with integrable SYK$_2$, revealing fundamental differences.

Findings

SYK$_4$ saturates the K-complexity bound

SYK$_2$ remains exponentially below the bound

Chaotic systems tend to saturate the complexity bound

Abstract

Heisenberg time evolution under a chaotic many-body Hamiltonian $H$ transforms an initially simple operator into an increasingly complex one, as it spreads over Hilbert space. Krylov complexity, or `K-complexity', quantifies this growth with respect to a special basis, generated by $H$ by successive nested commutators with the operator. In this work we study the evolution of K-complexity in finite-entropy systems for time scales greater than the scrambling time $t_s>\log (S)$. We prove rigorous bounds on K-complexity as well as the associated Lanczos sequence and, using refined parallelized algorithms, we undertake a detailed numerical study of these quantities in the SYK$_4$ model, which is maximally chaotic, and compare the results with the SYK$_2$ model, which is integrable. While the former saturates the bound, the latter stays exponentially below it. We discuss to what extent this is a generic feature distinguishing between chaotic vs. integrable systems.