求解量子版概率路径问题,发现其演化规律与经典不同。
Exact Solutions to the Quantum Schrödinger Bridge Problem
- 从拉格朗日视角推导量子路径演化方程,引入非局域量子势。
- 精确求解高斯分布间的量子桥接问题,协方差演化受量子效应影响。
- 适用于生成模型、单细胞数据建模及分子生成等场景。
量子薛定谔桥问题(QSBP)描述了在薛定谔方程支配下,任意两个概率分布之间的随机过程演化。尽管该问题在数学文献中已有研究,本文从拉格朗日角度重新构建,并推导其特征,特别适合生成建模应用。结果表明,演化方程包含玻姆(量子)势,体现过程的非局域性,区别于经典随机动力学,反映典型量子系统特性。本文推导出高斯分布间QSBP的精确闭式解,基于拉格朗日形式下的福克-普朗克方程(FPE)和哈密顿-雅可比方程(HJE)求解。与经典情况类似,高斯分布间的解仍为高斯过程,但协方差演化受量子效应影响。利用这些显式解,我们提出一种基于高斯混合模型框架的改进算法,并在单细胞演化数据、图像生成、分子翻译及平均场博弈等多个实验中验证其有效性。
原文摘要 · Abstract (English)
The Quantum Schrödinger Bridge Problem (QSBP) describes the evolution of a stochastic process between two arbitrary probability distributions, where the dynamics are governed by the Schrödinger equation rather than by the traditional real-valued wave equation. Although the QSBP is known in the mathematical literature, we formulate it here from a Lagrangian perspective and derive its main features in a way that is particularly suited to generative modeling. We show that the resulting evolution equations involve the so-called Bohm (quantum) potential, representing a notion of non-locality in the stochastic process. This distinguishes the QSBP from classical stochastic dynamics and reflects a key characteristic typical of quantum mechanical systems. In this work, we derive exact closed-form solutions for the QSBP between Gaussian distributions. Our derivation is based on solving the Fokker-Planck Equation (FPE) and the Hamilton-Jacobi Equation (HJE) arising from the Lagrangian formulation of dynamical Optimal Transport. We find that, similar to the classical Schrödinger Bridge Problem, the solution to the QSBP between Gaussians is again a Gaussian process; however, the evolution of the covariance differs due to quantum effects. Leveraging these explicit solutions, we present a modified algorithm based on a Gaussian Mixture Model framework, and demonstrate its effectiveness across several experimental settings, including single-cell evolution data, image generation, molecular translation and applications in Mean-Field Games.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。