AI RESEARCH
DistributedEstimator: Distributed Training of Quantum Neural Networks via Circuit Cutting
arXiv CS.LG
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ArXi:2602.16233v2 Announce Type: replace-cross Circuit cutting decomposes a large quantum circuit into smaller subcircuits whose outputs are classically reconstructed to recover original expectation values. While prior work characterises cutting overhead via subcircuit counts and sampling complexity, its end-to-end impact on iterative, estimator-driven