English(EN) DistributedEstimator: Distributed Training of Quantum Neural Networks via Circuit Cutting

DistributedEstimator 通过电路切割训练量子神经网络

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-07 04:00

研究人员开发了 DistributedEstimator 系统，该系统通过将大型量子电路分解为更小、可管理的子电路来训练量子神经网络。该方法包括分区、子实验生成、并行执行和经典重构，其中重构被证明是最耗时的阶段。尽管存在重构开销，该系统在 Iris 和 MNIST 等基准数据集上保持了测试准确性，并保持了对噪声和扰动的鲁棒性，尽管子实验的指数级增长限制了实际应用到较少量子比特的数量。 AI

影响这项研究探索了扩展量子神经网络训练的方法，可能对未来的 AI 硬件和算法产生影响。

排序理由学术论文，详细介绍了一种训练量子神经网络的新系统。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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arXiv cs.LG TIER_1 English(EN) · Prabhjot Singh, Adel N. Toosi, Rajkumar Buyya · 2026-05-07 04:00

DistributedEstimator：通过电路切割实现量子神经网络的分布式训练

arXiv:2602.16233v2 Announce Type: replace-cross Abstract: 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…

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DistributedEstimator：通过电路切割实现量子神经网络的分布式训练

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