English(EN) The Feedback Hamiltonian is the Score Function: A Diffusion-Model Framework for Quantum Trajectory Reversal

反馈哈密顿量是得分函数：用于量子轨迹反演的扩散模型框架

作者 PulseAugur 编辑部 · [1 个来源] · 2026-04-23 02:02

研究人员在量子轨迹反演与机器学习中使用的基于得分的扩散模型之间建立了一个理论联系。他们证明了反馈哈密顿量（可以统计上反转量子轨迹的时间演化）在数学上等同于量子轨迹分布的得分函数。这一发现表明，诸如去噪得分匹配之类的机器学习技术可以应用于估计在未满足理想条件的现实世界实验中的得分函数。 AI

影响表明机器学习技术可用于分析和潜在地控制量子系统，为实验物理学开辟了新途径。

排序理由在arXiv上发表的学术论文，详细介绍了量子物理学与机器学习之间的理论联系。

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arXiv cs.LG TIER_1 English(EN) · Alan John · 2026-04-23 02:02

反馈哈密顿量即得分函数：用于量子轨迹反转的扩散模型框架

In continuously monitored quantum systems, the feedback protocol of García-Pintos, Liu, and Gorshkov reshapes the arrow of time: a Hamiltonian $H_{\mathrm{meas}} = r A / τ$ applied with gain $X$ tilts the distribution of measurement trajectories, with $X < -2$ producing statistic…