New techniques for error-independent unified path variation, non-degenerate batched sampling, and flexible contraction accelerate tensor network quantum trajectory simulations by more than 10^8 times.
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A classical agent extracts more work from quantum temporal correlations via adaptive strategies bounded by the new Time-Ordered Free Energy, while reinforcement learning achieves polylogarithmic dissipation when learning unknown states.
Gravitational redshift may be incompatible with the Heisenberg uncertainty principle, testable via a continuous-variable photonic entanglement thought experiment in weak gravity.
A review that contrasts common assumptions about the Lindblad equation with refined expectations drawn from examples, culminating in a checklist for assessing its breakdown.
citing papers explorer
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Accelerating Quantum Tensor Network Simulations with Unified Path Variations and Non-Degenerate Batched Sampling
New techniques for error-independent unified path variation, non-degenerate batched sampling, and flexible contraction accelerate tensor network quantum trajectory simulations by more than 10^8 times.
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A Demon that remembers: An agential approach towards quantum thermodynamics of temporal correlations
A classical agent extracts more work from quantum temporal correlations via adaptive strategies bounded by the new Time-Ordered Free Energy, while reinforcement learning achieves polylogarithmic dissipation when learning unknown states.
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Gravitational Redshift of Light and the Heisenberg Uncertainty Principle
Gravitational redshift may be incompatible with the Heisenberg uncertainty principle, testable via a continuous-variable photonic entanglement thought experiment in weak gravity.
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Is Lindblad for me?
A review that contrasts common assumptions about the Lindblad equation with refined expectations drawn from examples, culminating in a checklist for assessing its breakdown.