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関連する概念動画

The Pauli Exclusion Principle03:06

The Pauli Exclusion Principle

45.7K
The arrangement of electrons in the orbitals of an atom is called its electron configuration. We describe an electron configuration with a symbol that contains three pieces of information:
45.7K
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

42.8K
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.
42.8K
Electron Orbital Model01:18

Electron Orbital Model

68.4K
Orbitals are the areas outside of the atomic nucleus where electrons are most likely to reside. They are characterized by different energy levels, shapes, and three-dimensional orientations. The location of electrons is described most generally by a shell or principal energy level, then by a subshell within each shell, and finally, by individual orbitals found within the subshells.
The first shell is closest to the nucleus, and it has only one subshell with a single spherical orbital called the...
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Quantum Numbers02:43

Quantum Numbers

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It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
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Reduced Mass Coordinates: Isolated Two-body Problem01:12

Reduced Mass Coordinates: Isolated Two-body Problem

1.4K
In classical mechanics, the two-body problem is one of the fundamental problems describing the motion of two interacting bodies under gravity or any other central force. When considering the motion of two bodies, one of the most important concepts is the reduced mass coordinates, a quantity that allows the two-body problem to be solved like a single-body problem. In these circumstances, it is assumed that a single body with reduced mass revolves around another body fixed in a position with an...
1.4K
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

730
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
730

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

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機械学習で量子多電子問題を2電子に減らす

LeeAnn M Sager-Smith1, David A Mazziotti1

  • 1Department of Chemistry and The James Franck Institute, The University of Chicago, Chicago, Illinois60637, United States.

Journal of the American Chemical Society
|October 4, 2022
PubMed
まとめ
この要約は機械生成です。

複雑な化学計算を簡素化する 新しい機械学習手法です このメソッドは,双子の占いを学習し,正確な電子構造の予測のために,多くの電子問題を有効な2電子問題に減らします.

さらに関連する動画

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Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform

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Picometer-Precision Atomic Position Tracking through Electron Microscopy
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関連する実験動画

Last Updated: Aug 26, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
05:30

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit

Published on: September 8, 2023

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Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
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Picometer-Precision Atomic Position Tracking through Electron Microscopy
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科学分野:

  • コンピュータ化学
  • 量子力学について
  • 機械学習

背景:

  • 多くの電子の問題は計算化学において重要な課題であり,既存の方法はシステムのサイズに合わせてスケーリングが不十分である.
  • 分子エネルギーの計算は2電子の波関数に依存しているが,その占有分布 (双子占有) を決定することは複雑である.
  • 拡張された"aufbau"原則は,物理的にエレガントなアプローチを提供しますが,正確なゲミナル占有分布が必要です.

研究 の 目的:

  • 電子構造計算のための新しい計算パラダイムを導入する.
  • ゲミナル職業分布を学習できる機械学習モデルを開発する.
  • 計算化学における多くの電子の問題に取り組むために

主な方法:

  • 折り畳みニューラルネットワークは,近似のゲミナル占有分布を学習するために使用されました.
  • ニューラルネットワークは 2〜7個の炭素原子の 炭素同位体で訓練されました
  • このモデルは,オクタン同位体とより大きな炭化水素 (8−15炭素) のエネルギーを予測することによって検証された.

主要な成果:

  • コンボリューションニューラルネットワークは,有効な電子分布を保証し,N-表現性の条件を成功裏に学びました.
  • このモデルは,訓練セットを超えたシステムの 分子エネルギーを正確に予測しました.
  • このアプローチは,多くの電子問題を有効な2電子問題に減らすことの実現可能性を実証した.

結論:

  • 機械学習は伝統的な計算化学の方法の限界を克服する強力なツールです.
  • この新しいパラダイムは,多くの電子問題を効果的に解決することによって,正確な電子構造の予測を可能にします.
  • 開発された方法は,効率的で正確な分子エネルギー計算のための新しい道を開きます.