English(EN) What resources are needed for optimal learning of bosonic Gaussian states?

为学习量子态设定新界限

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-15 04:00

研究人员为学习量子系统中未知的玻色子高斯态所需的资源设定了新的理论界限。该研究证明了对于具有能量小于 $E$ 的 $n$ 模式态，高斯测量的下界为 $\Omega(n^3/\varepsilon^2)$，任意测量的下界为 $\Omega(n^2/\varepsilon^2)$，精度为 $\varepsilon$ 迹距离。该工作还展示了纯态或被动高斯态的上限为 $\widetilde{O}(n^2/\varepsilon^2)$，并强调了非高斯测量对于被动态的最佳学习是必要的。这些发现推动了量子学习理论的发展，并对量子传感和基准测试具有启示意义。 AI

排序理由详细介绍量子物理学理论发现的学术论文。[lever_c_demoted from research: ic=1 ai=0.1]

在 arXiv cs.LG 阅读 →

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Senrui Chen, Francesco Anna Mele, Marco Fanizza, Alfred Li, Zachary Mann, Hsin-Yuan Huang, Yanbei Chen, John Preskill · 2026-09-15 04:00

学习玻色子高斯态的最佳资源需要什么？

arXiv:2603.18136v2 Announce Type: replace-cross Abstract: Continuous-variable systems enable key quantum technologies in computation, communication, and sensing. Bosonic Gaussian states emerge naturally in various such applications, including gravitational-wave and dark-matter de…

本文如何被排名

报道来源 [1]

学习玻色子高斯态的最佳资源需要什么？

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