Local refinement after cotengra yields a bond-dimension-dependent cost advantage on Sycamore topologies that is absent on random or QAOA graphs.
Markov and Yaoyun Shi
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A new GPU quantum simulator framework achieves 64x-146x speedups for 20-28 qubit circuits via backend selection, gate fusion, and adaptive precision while integrating with Qiskit and others.
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Bond-dimension scaling of a local-refinement advantage over hyperoptimized tensor-network contraction on Sycamore like topologies
Local refinement after cotengra yields a bond-dimension-dependent cost advantage on Sycamore topologies that is absent on random or QAOA graphs.
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GPU-Accelerated Quantum Simulation: Empirical Backend Selection, Gate Fusion, and Adaptive Precision
A new GPU quantum simulator framework achieves 64x-146x speedups for 20-28 qubit circuits via backend selection, gate fusion, and adaptive precision while integrating with Qiskit and others.