An optimization framework for high-efficiency quantum Feshbach engines in trapped BECs is developed using variational dynamics and Nelson's stochastic quantization to minimize cost functionals for protocol duration versus physical constraints.
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HAVQDS achieves higher approximation ratios on 6-14 qubit SK instances than adiabatic or CD methods while cutting CNOT counts by 1-2 orders of magnitude.
QOSTE derives minimal-energy controls for N-level quantum protocols by finding geodesics in the rotating frame, yielding quadratic energy improvement over STA for long times.
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Optimal Quantum Feshbach Engines
An optimization framework for high-efficiency quantum Feshbach engines in trapped BECs is developed using variational dynamics and Nelson's stochastic quantization to minimize cost functionals for protocol duration versus physical constraints.
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Hybrid Real-Imaginary Time Evolution for Low-Depth Hamiltonian Simulation in Quantum Optimization
HAVQDS achieves higher approximation ratios on 6-14 qubit SK instances than adiabatic or CD methods while cutting CNOT counts by 1-2 orders of magnitude.
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Energy shortcut of N-level quantum protocols by optimal control
QOSTE derives minimal-energy controls for N-level quantum protocols by finding geodesics in the rotating frame, yielding quadratic energy improvement over STA for long times.