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Bulletin of the American Physical Society

Chaos in quantum many-body systems

Gary E. Mitchell

Published Oct 28, 2006• 1 citation
OpenAlex

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We address the problem of the dissipative character of collective motion in finite Fermi systems. We study this problem from the point of view of chaotic features of the fermionic degrees of freedom of the many-body Fermi systems. Our main aim is of two kinds: first, we investigate how quantum chaos sets in in many-body systems and then, we try to relate quantum many-body chaos of the intrinsic fermionic degrees of freedom to the corresponding dissipative properties of the macroscopic collective motion. The main focus is on the role of two-body interaction between fermions in onset of the quantum many-body chaos and collective dissipation.
The central research objects are bosonic many-body systems and their instabilities. One powerful approach to probing these instabilities in quantum systems is through Out-of-Time-Ordered Correlators (OTOCs), and they are the focus of the first chapter. We investigate a transition phenomenon governed primarily by local instabilities, which differentiates integrable dynamics from generic chaotic behavior. This transition provides a promising route to reliably detect quantum chaos in many-body systems, motivating us to study the onset of chaos as a system evolves from integrable to mixed and fully chaotic regimes. Under the assumption that chaos is properly identified, we exploit its characteristic exponential sensitivity and mixing properties in the second part of our work. Here, we propose a novel protocol for Controlling Many-Body Quantum Chaos, utilizing chaos as a resource to achieve exponentially fast targeting of macroscopically occupied single-particle states, connected via chaotic heteroclinic trajectories. This theoretical framework offers a coherent targeting procedure for state preparation in experimental platforms. Finally, in the third part, we explore the manifestation of quantum chaos in low-energy states of many-body systems relevant for quantum computation, as system size increases. Recent advances in Neural Quantum States (NQS), leveraging machine learning progress driven by the surge of artificial intelligence, have significantly extended the numerical boundaries of many-body simulations, such that we now reach system sizes with a hundred sites. These developments open new opportunities for understanding chaos in large-scale quantum systems.