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関連する概念動画

Cluster Sampling Method01:20

Cluster Sampling Method

11.0K
Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
11.0K
Random Sampling Method01:09

Random Sampling Method

11.8K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
11.8K
Sampling Distribution01:12

Sampling Distribution

17.6K
Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
17.6K
Sampling Methods: Overview01:06

Sampling Methods: Overview

3.7K
A sample refers to a smaller subset representative of a larger population. In analytical chemistry, studying or analyzing an entire population is often impractical or impossible. Therefore, samples are used to draw inferences and generalize the whole population. The sampling method selects individuals or items from a population to create a sample. Standard sampling methods include random, judgemental, systematic, stratified, and cluster sampling. 
In analytical chemistry, the choice of...
3.7K
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

3.3K
Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
3.3K
Sampling Plans01:23

Sampling Plans

1.5K
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
1.5K

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Updated: May 4, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

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量子大都市サンプリング

K Temme1, T J Osborne, K G Vollbrecht

  • 1Vienna Center for Quantum Science & Technology, Fakultät für Physik, Universität Wien, 1090 Wien, Austria.

Nature
|March 4, 2011
PubMed
まとめ
この要約は機械生成です。

研究者は,量子システムをシミュレートするために量子メトロポリスアルゴリズムを開発しました. この量子コンピューティングのアプローチは,固有状態から直接サンプリングを可能にし,古典的なシミュレーションの制限を克服します.

さらに関連する動画

Isotopic Effect in Double Proton Transfer Process of Porphycene Investigated by Enhanced QM/MM Method
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Isotopic Effect in Double Proton Transfer Process of Porphycene Investigated by Enhanced QM/MM Method

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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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関連する実験動画

Last Updated: May 4, 2026

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics
10:52

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

Published on: April 12, 2019

14.1K
Isotopic Effect in Double Proton Transfer Process of Porphycene Investigated by Enhanced QM/MM Method
05:51

Isotopic Effect in Double Proton Transfer Process of Porphycene Investigated by Enhanced QM/MM Method

Published on: July 19, 2019

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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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科学分野:

  • 量子コンピューティング
  • 計算物理学の物理
  • 量子力学は,量子力学という

背景:

  • 量子コンピュータは,古典的なコンピュータでは扱えない複雑な量子システムをシミュレートすることを約束しています.
  • 均衡と静的性質をシミュレートするには,グラウンドとギブス状態を準備する必要があります.
  • クラシックなメトロポリスアルゴリズムは,相互作用する粒子をシミュレートするための標準です.

研究 の 目的:

  • メトロポリスアルゴリズムの量子バージョンを開発する.
  • 量子コンピュータがグラウンドとギブス状態を準備できるようにするためです.
  • 量子システムの均衡と静的性質のシミュレーションに取り組む.

主な方法:

  • 量子メトロポリスアルゴリズムの実装.
  • 量子ゲートを利用して時間進化演算子分解.
  • ハミルトニアンの固有状態から直接サンプリングする.

主要な成果:

  • 量子システムシミュレーションのための量子メトロポリスアルゴリズムの実証.
  • 固有状態からの直接サンプリングを有効にし,古典的な記号問題を回避しました.
  • 量子コンピュータでグラウンドとギブスの状態を準備する方法を紹介した.

結論:

  • 量子メトロポリスアルゴリズムは,量子システムを効果的にシミュレートすることができます.
  • このアプローチは,記号問題を含む古典的なシミュレーションの限界を克服します.
  • 小規模な実装は,現在の量子技術で実現可能である.