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関連する概念動画

Random Error01:04

Random Error

848
Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

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The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
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Random Sampling Method01:09

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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...
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Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

656
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
656
Random Variables01:09

Random Variables

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A random variable is a single numerical value that indicates the outcome of a procedure. The concept of random variables is fundamental to the probability theory and was introduced by a Russian mathematician, Pafnuty Chebyshev, in the mid-nineteenth century.
Uppercase letters such as X or Y denote a random variable. Lowercase letters like x or y denote the value of a random variable. If X is a random variable, then X is written in words, and x is given as a number.
For example, let X = the...
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Uncertainty in Measurement: Accuracy and Precision03:37

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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追跡可能なランダムな数字は非ローカルな量子優位性から

Gautam A Kavuri1,2, Jasper Palfree3,4, Dileep V Reddy3,4

  • 1Department of Physics, University of Colorado, Boulder, CO, USA. gautam.kavuri@colorado.edu.

Nature
|June 11, 2025
PubMed
まとめ
この要約は機械生成です。

この研究は,完全に追跡可能で証明可能な 新しい量子ランダムナンバージェネレータを導入します. デジタルセキュリティの強化とリソースの分配のための予測不可能なランダムな番号の生成を保証します.

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科学分野:

  • 量子情報科学
  • 暗号化
  • コンピュータ科学

背景:

  • 予測不能なランダムな数字は デジタルセキュリティと 公正なリソース配分に不可欠です
  • 現在のランダムナンバージェネレーター (RNG) は,トレーサビリティ,監査可能性,および予測不可能な証明能力に制限があります.
  • アルゴリズムのRNGは監査可能ですが,事前の予測不能性を保証することはできませんが,デバイス独立の量子RNGには脆弱な抽出ステップがあります.

研究 の 目的:

  • 完全に追跡可能なランダムナンバー生成プロトコルの実証です.
  • 既存のRNGの限界を解決し,監査可能で証明可能な予測不可能性を確保する.
  • 公開され,追跡され,証明される 量子ランダム性ビーコンを確立する

主な方法:

  • 装置独立の量子技術に基づくプロトコルを開発した.
  • 予測できない非局所的な量子相関から抽出したランダム性
  • 暗号の追跡とランダム性の抽出の検証のために分散された相互に絡み合ったハッシュチェーンを使用しました.

主要な成果:

  • 完全に追跡可能で 証明可能なランダムナンバー生成プロトコルを成功裏に実証しました
  • 公開量子ランダム性ビーコンを発射 40日間で99.7%の成功率を達成しました
  • 成功したプロトコル実行ごとに追跡可能なランダム性の512ビットを放出し,境界のエラー確率 (2^-64) と一致していることが証明されています.

結論:

  • このプロトコルは,証明可能で追跡可能なランダム性を生成するための公共サービスを提供します.
  • この量子的なアプローチは 確実なランダム性生成のための クラシックな方法よりも 絡み合いを引き出す利点を提供します
  • 開発された方法は,重要なアプリケーションのランダム番号生成の信頼性とセキュリティを高めます.