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.
Quantum machine learning: A comprehensive review of integrating ai with quantum computing for computational advancements
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Quantum annealing combined with a Neural Hash Function lets generative models create molecules that are more drug-like than classical versions or the training set itself.
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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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Molecular Design beyond Training Data with Novel Extended Objective Functionals of Generative AI Models Driven by Quantum Annealing Computer
Quantum annealing combined with a Neural Hash Function lets generative models create molecules that are more drug-like than classical versions or the training set itself.