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相关概念视频

Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

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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...
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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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Randomized Experiments01:13

Randomized Experiments

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
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Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
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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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In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
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相关实验视频

Updated: Sep 10, 2025

Large Scale Energy Efficient Sensor Network Routing Using a Quantum Processor Unit
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Published on: September 8, 2023

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基于深度学习的微加速评估用于高速量子随机数生成

Xiaomin Guo1,2, Wenhe Zhou1,2, Yue Luo1,2

  • 1Key Laboratory of Advanced Transducers and Intelligent Control System, Ministry of Education, Taiyuan University of Technology, Taiyuan 030024, China.

Entropy (Basel, Switzerland)
|August 28, 2025
PubMed
概括

这项研究通过极化控制的异质因子检测增强了量子随机数生成 (QRNG). 它实现了高速,安全的随机位生成和快速评估,改进了实际的QRNG应用.

关键词:
深度卷积神经网络双方位异质子检测量子条件的最小量子密码学量子随机数生成

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相关实验视频

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科学领域:

  • 量子信息科学
  • 安全的通信技术
  • 应用物理

背景情况:

  • 安全的通信依赖于高速,高安全的量子随机数生成 (QRNG).
  • 实际的QRNG系统面临影响效率和安全性的非理想性.
  • 准确的值对于量化随机性至关重要.

研究的目的:

  • 通过新的响应方式提高QRNG的效率和安全性.
  • 研究系统非理想性对量子随机性的影响.
  • 开发一个快速而准确的方法来评估QRNG中的.

主要方法:

  • 采用极化控制的异质体检测来测量真空射击噪声波动.
  • 分析了不平衡检测,振幅相重叠,以及量子条件最小的安全参数.
  • 开发了一个深度卷积神经网络 (CNN) 以快速评估.

主要成果:

  • 在37.25Gbps的高安全参数中实现了83.16%的真实随机比特提取比率.
  • 已证实可以缓解随机性过度估计和加强对窃听的安全性.
  • 美国国家广播公司以高准确度快速处理了大量的平方数据 (MAPE为0.004).
  • 超出了85Gbps的生成速度.

结论:

  • 拟议的方法显著提高了QRNG的性能和安全性.
  • 使用CNN的快速值加速了QRNG的实际部署.
  • 这项工作促进了高速,安全的随机数生成的发展.