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quant-ph2026
CT-bMPS: Approximate Tensor Network Contraction with Boundary MPS on Contraction Trees
Hidetaka Manabe, Feng Pan
We introduce contraction tree boundary matrix product states (CT-bMPS), a scalable approximate contraction method for general closed tensor networks. CT-bMPS represents the boundar…
quant-ph2026
Classical Simulation and Design Frontiers for IBM's Doped Clifford Sampling Experiment
Hidetaka Manabe, Hanfeng Gu, Feng Pan
We classically simulate the IBM doped Clifford random circuit sampling experiment, comprising qubits, entangling layers, and inserted gates. A deterministic tem…
quant-ph2026
Sampling hard circuits with verifiably high fidelity
Simon Martiel, Jay-U Chung, Alireza Seif +9
Sampling-based proposals are prominent candidates for demonstrating quantum computations beyond the reach of classical supercomputers. However, it has been difficult to combine the…