Learning-to-rank models trained on measured GPU runtimes can rank tensor-network contraction plans well enough to make Top-3 selection practical, but performance drops under circuit-family shift and is partly backend-dependent.
A practical introduction to tensor networks: Matrix product states and projected entangled pair states
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Learning to Rank Tensor Network Contraction Plans for GPU-Accelerated Quantum Circuit Simulation
Learning-to-rank models trained on measured GPU runtimes can rank tensor-network contraction plans well enough to make Top-3 selection practical, but performance drops under circuit-family shift and is partly backend-dependent.