强化学习代理高效合成Clifford量子电路

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-11 17:49

研究人员开发了一种新颖的强化学习方法来合成Clifford量子电路。他们的方法利用了一个大小无关、等变的神经网络，该网络学习发现Clifford门的最佳序列。该代理表现出色，能在毫秒内找到六量子比特系统的近最优电路，并扩展到三十量子比特，性能优于现有合成器。 AI

影响这项研究通过优化电路设计，有望实现更高效的量子计算。

排序理由该集群包含一篇学术论文，详细介绍了一种新的量子电路合成方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Rob Cornish · 2026-05-11 17:49

Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis

We consider the problem of synthesizing Clifford quantum circuits for devices with all-to-all qubit connectivity. We approach this task as a reinforcement learning problem in which an agent learns to discover a sequence of elementary Clifford gates that reduces a given symplectic…