Introduces a parallelizable hybrid tensor network algorithm for time-evolving matrix product states that combines classical BUG integration with quantum methods without synchronization barriers.
Towards robust benchmarking of quantum optimization algorithms
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QAOA-based QuSO achieves end-to-end speedup over classical baselines for power grid unit commitment with up to 14 qubits using 16 layers in high-load scenarios via efficient classical pre-computation.
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Time Evolution on Hybrid Tensor Networks -- A Novel and Parallelizable Algorithm
Introduces a parallelizable hybrid tensor network algorithm for time-evolving matrix product states that combines classical BUG integration with quantum methods without synchronization barriers.