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相关概念视频

Frequency of Spring-Mass System01:17

Frequency of Spring-Mass System

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One interesting characteristic of the simple harmonic motion (SHM) of an object attached to a spring is that the angular frequency, and the period and frequency of the motion, depend only on the mass and the force constant of the spring, and not on other factors such as the amplitude of the motion or initial conditions. We can use the equations of motion and Newton's second law to find the angular frequency, frequency, and period.
Consider a block on a spring on a frictionless surface. There...
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IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations01:08

IR Spectrum Peak Splitting: Symmetric vs Asymmetric Vibrations

1.0K
Identical bonds within a polyatomic group can stretch symmetrically (in-phase) or asymmetrically (out-of-phase). Similar to hydrogen bonding, these vibrations also influence the shape of the IR peak. Generally, asymmetric stretching frequencies are higher than symmetric stretching frequencies. For example, primary amines exhibit two distinct IR peaks between 3300–3500 cm−1 corresponding to the symmetric and asymmetric N-H stretching, while secondary amines exhibit a single...
1.0K
Damped Oscillations01:07

Damped Oscillations

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In the real world, oscillations seldom follow true simple harmonic motion. A system that continues its motion indefinitely without losing its amplitude is termed undamped. However, friction of some sort usually dampens the motion, so it fades away or needs more force to continue. For example, a guitar string stops oscillating a few seconds after being plucked. Similarly, one must continually push a swing to keep a child swinging on a playground.
Although friction and other non-conservative...
5.7K
State Space to Transfer Function01:21

State Space to Transfer Function

206
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:
206
IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration01:16

IR Spectroscopy: Hooke's Law Approximation of Molecular Vibration

1.3K
A covalently bonded heteronuclear diatomic molecule can be modeled as two vibrating masses connected by a spring. The vibrational frequency of the bond can be expressed using an equation derived from Hooke's law, which describes how the force applied to stretch or compress a spring is proportional to the displacement of the spring. In this case, the atoms behave like masses, and the bond acts like a spring.
According to Hooke's law, the vibrational frequency is directly proportional to...
1.3K
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

81
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
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相关实验视频

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Author Spotlight: Efficient Image Recognition Using Directional Gradient Histogram Technique and Support Vector Machines
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基于弹振动的Ising模型基础状态研究的点卷积神经网络算法.

Zhelong Jiang1,2, Gang Chen3, Ruixiu Qiao1

  • 1Institute of Semiconductors, Chinese Academy of Sciences, Beijing, China.

Scientific reports
|February 1, 2024
PubMed
概括

新的Spring-Ising算法使用弹振动模型进行高效的Ising地面状态搜索. 这种新的方法与AI芯片进行映射,在K2000基准上取得最佳结果.

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科学领域:

  • 计算物理 计算物理
  • 人工智能的人工智能
  • 优化算法 优化算法

背景情况:

  • 对于解决组合优化问题的Ising模型至关重要.
  • 当前的计算机架构需要专门的算法来有效地搜索基础状态,特别是硬件实现.
  • 由于计算需求,现有的方法在实际解决问题方面面临挑战.

研究的目的:

  • 介绍一种新的算法,即Spring-Ising算法,用于高效的Ising基本状态搜索.
  • 开发一个适合硬件计算和AI芯片的算法.
  • 通过优化中的动态平衡来提高本地搜索的细节性.

主要方法:

  • 斯普林-伊辛算法模型将旋转作为由弹连接的质点,建立运动方程.
  • 它使用点卷积神经网络结构,使AI芯片上的并行计算成为可能.
  • 该算法结合了动态平衡来调整权重,从而促进了更细致的本地搜索.

主要成果:

  • 在解决Ising模型方面,Spring-Ising算法展示了有希望的结果.
  • 在K2000基准测试中,该算法在10,000次代后,在2.9%的案例中取得了最佳结果.
  • 该算法的设计可以在AI硬件上进行高效的并行计算.

结论:

  • 春季Ising算法提供了一个新的,硬件加速的方法来Ising地面状态搜索.
  • 它提供了一种可行的方法来计算Ising模型在专门的AI芯片上.
  • 算法的动态平衡概念在优化问题中增强了本地搜索功能.