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February 19, 20260 citationsOpen Access

Signatures of Instability in Bosonic Many-Body Systems

MSMathias Steinhuber

Key Points

  • This research investigates instabilities in bosonic many-body systems, focusing on quantum chaos detection.
  • Analyzed out-of-time-ordered correlators to identify local instabilities
  • Developed a protocol for controlling many-body quantum chaos
  • Explored low-energy states related to quantum chaos in larger systems using neural quantum states
  • Identified a transition from integrable to chaotic behavior in many-body systems
  • Proposed a method for rapid state preparation via chaotic trajectories
  • Demonstrated potential for large-scale simulations of many-body systems with over a hundred sites

Abstract

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.

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Cite This Study

Mathias Steinhuber (2026) studied this question.

synapsesocial.com/papers/6996a768ecb39a600b3ed0a6https://doi.org/10.5283/epub.78114
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