English(EN) Efficient Gradient Estimation for Parameterized Quantum Systems with Lie Algebraic Symmetries

新框架利用李对称性进行高效量子电路梯度估计

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-25 04:00

研究人员开发了一个新的框架，用于估计参数化量子电路（PQC）中的梯度，该框架利用了李代数对称性。该方法使用Hadamard测试并分析矩阵指数的微分，将梯度表示为期望值的线性组合。该方法显著降低了测量成本，所需的采样次数相对于参数呈对数关系，并且与现有技术相比，在时间上提供了多项式加速。 AI

影响引入了一种优化量子机器学习模型的新颖方法，有望加速量子计算领域的研究。

排序理由该集群包含一篇学术论文，详细介绍了一种用于量子电路中梯度估计的新方法。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.LG TIER_1 English(EN) · Mohsen Heidari, Masih Mozakka, Wojciech Szpankowski · 2026-05-25 04:00

利用李代数对称性对参数化量子系统进行高效梯度估计

arXiv:2404.05108v3 Announce Type: replace-cross Abstract: Gradient estimation is a central challenge in training parameterized quantum circuits (PQCs) for hybrid quantum-classical optimization and learning problems. This difficulty arises from several factors, including the expon…