Complexity growth in integrable and chaotic models

• DOI: 10.1007/jhep07(2021)011
• Publication Date: 2021-07-06T05:02:32Z
• Authors: Vijay Balasubrama...; Matthew DeCross; Arjun Kar; Yue Li; Onkar Parrikar
• Keywords: High Energy Physics - Theory; FOS: Computer and information sciences; Quantum Physics; cs.CC; hep-th; FOS: Physical sciences; QC770-798; AdS-CFT Correspondence; Computational Complexity (cs.CC); 01 natural sciences; Computer Science - Computational Complexity; quant-ph; High Energy Physics - Theory (hep-th); Nuclear and particle physics. Atomic energy. Radioactivity; 0103 physical sciences; Models of Quantum Gravity; Integrable Field Theories; Quantum Physics (quant-ph)

Abstract We use the SYK family of models with N Majorana fermions to study the complexity of time evolution, formulated as the shortest geodesic length on the unitary group manifold between the identity and the time evolution operator, in free, integrable, and chaotic systems. Initially, the shortest geodesic follows the time evolution trajectory, and hence complexity grows linearly in time. We study how this linear growth is eventually truncated by the appearance and accumulation of conjugate points, which signal the presence of shorter geodesics intersecting the time evolution trajectory. By explicitly locating such “shortcuts” through analytical and numerical methods, we demonstrate that: (a) in the free theory, time evolution encounters conjugate points at a polynomial time; consequently complexity growth truncates at O($$ \sqrt{N} $$

N

), and we find an explicit operator which “fast-forwards” the free N-fermion time evolution with this complexity, (b) in a class of interacting integrable theories, the complexity is upper bounded by O(poly(N)), and (c) in chaotic theories, we argue that conjugate points do not occur until exponential times O(eN), after which it becomes possible to find infinitesimally nearby geodesics which approximate the time evolution operator. Finally, we explore the notion of eigenstate complexity in free, integrable, and chaotic models.