非马科夫量子状态扩散的神经网络解决方案和量子随机过程的运算符构造
Jiaji Zhang1, Carlos L Benavides-Riveros2,3, Lipeng Chen1
1Zhejiang Laboratory, Hangzhou 311100, China.
The Journal of chemical physics
|November 17, 2025
概括
这项研究引入了量子动力学的新机器学习方法,从轨迹中重建量子进化运算符. 这种方法准确地建模开放量子系统,并增强复杂系统的计算.
科学领域:
- 量子物理学 量子物理学 是一种量子物理学.
- 机器学习 机器学习
- 计算化学计算化学
背景情况:
- 开放的量子系统需要先进的建模技术.
- 非马科夫量子态扩散提供了一个基于波函数的框架.
- 现有的机器学习方法往往近似波函数或预期值.
研究的目的:
- 介绍一个新的机器学习方法用于量子动力学.
- 使用神经网络开发一个运算符构建算法.
- 证明波函数近似之外的更广泛的适用性.
主要方法:
- 使用神经网络作为通用发电机.
- 从量子轨迹中重建了随机时间演变运算符.
- 使用了一个运算符构造算法.
主要成果:
- 在不同的光谱密度上,成功地将算法与自旋玻色子模型进行了基准测试.
- 在模拟量子动力学方面表现出高精度.
- 在计算吸收光谱和减少密度矩阵方面展示了实用性.
结论:
- 在量子动力学中建立了机器学习的新范式.
- 基于操作者的方法为随机过程提供了更广泛的适用性.
- 该方法在延长的时间尺度上准确地建模开放量子系统.
相关概念视频
State Space Representation
509
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
Consider an RLC circuit, a...
509
Entropy Change in Reversible Processes
3.2K
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
3.2K
The Quantum-Mechanical Model of an Atom
56.5K
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
56.5K
Transfer Function to State Space
739
State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
In an RLC...
In an RLC...
739
Poisson's And Laplace's Equation
4.1K
The electric potential of the system can be calculated by relating it to the electric charge densities that give rise to the electric potential. The differential form of Gauss's law expresses the electric field's divergence in terms of the electric charge density.
4.1K
State Space to Transfer Function
548
The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
548


