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相关概念视频

The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

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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.
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Equivalent Circuits for Practical Transformers01:28

Equivalent Circuits for Practical Transformers

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The practical equivalent circuits of single-phase two-winding transformers exhibit significant deviations from their idealized versions due to the inherent properties of winding resistance and finite core permeability. These properties result in real and reactive power losses, affecting the transformer's performance. Understanding these deviations is crucial for designing more efficient transformers.
In a practical transformer, each winding exhibits resistance and leakage reactance. The...
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Transformers01:26

Transformers

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A device that transforms voltages from one value to another using induction is called a transformer. A transformer consists of two separate coils, or windings, wrapped around the same soft iron core. However, they are electrically insulated from each other.
The iron core has a substantial relative permeability. Therefore, the magnetic field lines generated due to the current in one winding are almost entirely confined within the core, such that the same magnetic flux permeates each turn of both...
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Types Of Transformers01:16

Types Of Transformers

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Transformers can provide desired voltages to a circuit by modifying the number of turns in the secondary windings.
If the ratio of the number of turns in the secondary winding to that of the primary winding is greater than one, then the transformer is said to be a step-up transformer. In a step-up transformer, the voltage at the secondary winding is greater than the voltage applied at the primary winding.
However, if this ratio is less than one, the transformer is said to be a step-down...
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Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

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In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
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Energy Losses in Transformers01:21

Energy Losses in Transformers

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In an ideal transformer, it is assumed that there are no energy losses, and, hence, all the power at the primary winding is transferred to the secondary winding. However, in reality,  the transformers always have some energy losses, and, hence, the output power obtained at the secondary winding is less than the input power at the primary winding due to energy losses.
There are four main reasons for energy losses in transformers.
The first cause can be  the high resistance of the...
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相关实验视频

Updated: Jan 10, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
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Generation and Coherent Control of Pulsed Quantum Frequency Combs

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对于电子量子状态的基于物理的变压器.

João Augusto Sobral1, Michael Perle2, Mathias S Scheurer3

  • 1Institute for Theoretical Physics III, University of Stuttgart, Stuttgart, Germany. joao.sobral@itp3.uni-stuttgart.de.

Nature communications
|November 28, 2025
PubMed
概括
此摘要是机器生成的。

这项研究介绍了一个基于物理的框架,使用变压器来改善复杂的多体系统的神经量子状态. 该方法提高了量子多体计算中的解释性和计算效率.

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科学领域:

  • 量子力学就是量子力学.
  • 计算物理学的计算物理.
  • 机器学习是机器学习.

背景情况:

  • 基于神经网络的变量量子态,特别是自回归模型,用于复杂的多体波函数.
  • 当前的方法面临着计算基础选择的挑战,缺乏物理解释性.

研究的目的:

  • 开发一个修改的变量蒙特卡洛框架,包括先前的物理信息.
  • 提高神经量子状态表示的解释性和计算效率.

主要方法:

  • 基于物理的基础是使用先前的物理知识构建的,包括参考状态.
  • 一个变压器模型被用来自动回归样本对参考状态的纠正.
  • 该方法在表现出金属绝缘体过渡的费米离子模型上进行了演示.

主要成果:

  • 基于变压器的方法产生了更易于解释和计算效率更高的基本状态表示.
  • 变压器的隐藏表现捕捉了基础状态的能量排序.
  • 该框架成功地模拟了一个具有金属绝缘体过渡的费米离子系统.

结论:

  • 这种基于物理学的神经量子状态框架为更高效和可解释的量子多体计算提供了一条道路.
  • 利用物理先验可以提高量子状态的神经网络表示的性能和理解.