Intrinsic dimension of quantum trajectories serves as an unsupervised probe sensitive to chaos, integrability, and ergodicity breaking in dissipative quantum systems.
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A review of how quantum information science is expected to provide new tools and insights for nuclear and high-energy physics phenomenology and quantum simulations.
Krylov subspace methods efficiently describe quantum evolution, operator growth, and chaos in many-body systems, with metrics like Krylov complexity and applications in open systems, QFT, and quantum computing.
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Complexity of Quantum Trajectories
Intrinsic dimension of quantum trajectories serves as an unsupervised probe sensitive to chaos, integrability, and ergodicity breaking in dissipative quantum systems.
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Quantum Complexity and New Directions in Nuclear Physics and High-Energy Physics Phenomenology
A review of how quantum information science is expected to provide new tools and insights for nuclear and high-energy physics phenomenology and quantum simulations.
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Quantum Dynamics in Krylov Space: Methods and Applications
Krylov subspace methods efficiently describe quantum evolution, operator growth, and chaos in many-body systems, with metrics like Krylov complexity and applications in open systems, QFT, and quantum computing.