Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

State Space Representation01:27

State Space Representation

496
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...
496
Graphing the Wave Function01:13

Graphing the Wave Function

2.8K
Consider the wave equation for a sinusoidal wave moving in the positive x-direction. The wave equation is a function of both position and time. From the wave equation, two different graphs can be plotted.
2.8K
Propagation of Action Potentials01:23

Propagation of Action Potentials

8.7K
The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
8.7K
Exponential and Sinusoidal Signals01:18

Exponential and Sinusoidal Signals

663
The exponential function is crucial for characterizing waveforms that rise and decay rapidly. This continuous-time exponential function is defined using exponential terms with constants α and A. When both constants are real, the function is represented as,
663
Transfer Function to State Space01:23

Transfer Function to State Space

727
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...
727
Equations of Wave Motion01:02

Equations of Wave Motion

8.2K
Mathematically, the motion of a wave can be studied using a wavefunction. Consider a string oscillating up and down in simple harmonic motion, having a period T. The wave on the string is sinusoidal and is translated in the positive x-direction as time progresses. Sine is a function of the angle θ, oscillating between +A and −A and repeating every 2π radians. To construct a wave model, the ratio of the angle θ and the position x is considered.
8.2K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Dataset distillation for machine learning force field in phase transition regime.

The Journal of chemical physics·2026
Same author

Deep-learning electronic structure calculations.

Nature computational science·2025
Same author

Down to one network for computing crystalline materials.

Nature computational science·2025
Same author

A multi-resolution systematically improvable quantum embedding scheme for large-scale surface chemistry calculations.

Nature communications·2025
Same author

Individual and Cooperative Superexchange Enhancement in Cuprates.

Journal of chemical theory and computation·2025
Same author

Molecularly resolved mapping of heterogeneous ice nucleation and crystallization pathways using in-situ cryo-TEM.

Nature communications·2025

相关实验视频

Updated: Jan 8, 2026

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
12:03

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

8.9K

基于神经网络的波函数的随时演变的随机表示.

Bizi Huang1, Weizhong Fu1, Ji Chen1,2,3

  • 1School of Physics, Peking University, Beijing 100871, People's Republic of China.

The Journal of chemical physics
|December 24, 2025
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的计算方法,将随机表示和神经网络结合起来,以解决电子动态的时间依赖施罗丁格方程 (TDSE). 这种方法准确地模拟了激光场中的电离过程.

更多相关视频

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays
10:45

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

10.3K
Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
09:32

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Published on: December 18, 2016

12.8K

相关实验视频

Last Updated: Jan 8, 2026

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials
12:03

A Method for Tracking the Time Evolution of Steady-State Evoked Potentials

Published on: May 25, 2019

8.9K
Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays
10:45

Time-dependent Increase in the Network Response to the Stimulation of Neuronal Cell Cultures on Micro-electrode Arrays

Published on: May 29, 2017

10.3K
Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
09:32

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients

Published on: December 18, 2016

12.8K

科学领域:

  • 量子力学就是量子力学.
  • 计算物理学的计算物理.
  • 一秒钟的物理学.

背景情况:

  • 解决时间依赖的施罗丁格方程 (TDSE) 对于理解超快光谱和激光物质相互作用中的电子动态至关重要.
  • 精确的TDSE解决方案在计算上昂贵,因为希尔伯特空间与系统维度的指数增长.

研究的目的:

  • 开发和验证一种计算效率高的方法来解决TDSE.
  • 为了建模非电电子动力学,特别是强激光场下的电离过程.

主要方法:

  • 将随机表示框架与神经网络波函数替代品集成.
  • 在模拟电离动力学的一维单电子系统上进行验证.
  • 探索扩展到三维系统的探索.

主要成果:

  • 量子演变的准确复制,包括电离过程中的能量和双极演变.
  • 证明了将方法应用于三维系统的可行性.
  • 确定了对更高维度模拟的先进稳定策略的需求.

结论:

  • 拟议的混合方法为模拟复杂的量子动态提供了一个有希望的途径.
  • 该方法显示了在现实系统中准确建模超快电子动态的潜力.
  • 需要进一步开发,以便对更高维度的问题有可靠的应用.