Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Sampling Theorem01:15

Sampling Theorem

347
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
347
Detection of Gross Error: The Q Test01:00

Detection of Gross Error: The Q Test

6.1K
When one or more data points appear far from the rest of the data, there is a need to determine whether they are outliers and whether they should be eliminated from the data set to ensure an accurate representation of the measured value. In many cases, outliers arise from gross errors (or human errors) and do not accurately reflect the underlying phenomenon. In some cases, however, these apparent outliers reflect true phenomenological differences. In these cases, we can use statistical methods...
6.1K
Random Sampling Method01:09

Random Sampling Method

11.2K
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...
11.2K
Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

699
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...
699
Sampling Distribution01:12

Sampling Distribution

12.8K
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...
12.8K
Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

230
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...
230

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Effect of nanogroove geometry on adipogenic differentiation.

Nanotechnology·2011
Same author

Measurement of the inclusive jet cross section in pp collisions at √s = 7 TeV.

Physical review letters·2011
Same author

Search for three-jet resonances in pp collisions at square root(s)=7  TeV.

Physical review letters·2011
Same author

Measurement of the t-channel single top quark production cross section in pp collisions at √s=7  TeV.

Physical review letters·2011
Same author

TM-25659 enhances osteogenic differentiation and suppresses adipogenic differentiation by modulating the transcriptional co-activator TAZ.

British journal of pharmacology·2011
Same author

Pulsed quantum optomechanics.

Proceedings of the National Academy of Sciences of the United States of America·2011

相关实验视频

Updated: Jul 9, 2025

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping
14:58

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping

Published on: June 3, 2015

14.7K

非保利误差可以在Qudit表面代码中有效采样.

Yue Ma1, Michael Hanks1, M S Kim1

  • 1QOLS, Blackett Laboratory, Imperial College London, London SW7 2AZ, United Kingdom.

Physical review letters
|December 1, 2023
PubMed
概括
此摘要是机器生成的。

表面代码提供了有前途的容错量子计算. 这项研究表明,即使有非保利误差,量子误差综合征也可以有效地用于量子表面代码,简化解码.

更多相关视频

Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
05:39

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

Published on: August 2, 2019

9.7K
Nanofabrication of Gate-defined GaAs/AlGaAs Lateral Quantum Dots
15:47

Nanofabrication of Gate-defined GaAs/AlGaAs Lateral Quantum Dots

Published on: November 1, 2013

16.3K

相关实验视频

Last Updated: Jul 9, 2025

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping
14:58

Silicon Metal-oxide-semiconductor Quantum Dots for Single-electron Pumping

Published on: June 3, 2015

14.7K
Scalable Quantum Integrated Circuits on Superconducting Two-Dimensional Electron Gas Platform
05:39

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

Published on: August 2, 2019

9.7K
Nanofabrication of Gate-defined GaAs/AlGaAs Lateral Quantum Dots
15:47

Nanofabrication of Gate-defined GaAs/AlGaAs Lateral Quantum Dots

Published on: November 1, 2013

16.3K

科学领域:

  • 量子信息科学 量子信息科学
  • 量子错误纠正方法 量子错误纠正方法
  • 凝聚物质理论 凝聚物质理论

背景情况:

  • 表面代码是容错量子计算的领先候选人.
  • 当前的模型经常将错误简化为保利运算符,可能会忽视复杂的错误动态.
  • 基于量子的量子系统比量子比特系统具有优势,但引入了更复杂的错误模型.

研究的目的:

  • 在2D表面代码中测量综合征测量后剩余的相关性,用于qudit系统.
  • 分析非保利误差对综合征抽样效率的影响.
  • 为了评估表面代码对更广泛的量子错误的稳定性.

主要方法:

  • 使用透理论来模拟网格上的错误传播.
  • 分析格子上的循环结构,以识别和量化相关性.
  • 在非保利误差条件下模拟综合征测量过程.

主要成果:

  • 综合征测量后剩余的相关性是稀疏的,并且局部限制在错误纠正值以下.
  • 综合征抽样的效率在很大程度上独立于非保利误差的具体形式.
  • 透理论有效地捕捉了对应关系的行为在量子表面代码中.

结论:

  • 库迪特表面代码证明了对非保利错误的弹性.
  • 在qudit表面代码中测量综合征是有效的样本,即使有复杂的错误.
  • 这些发现支持量子表面代码的可行性,用于实际的容错量子计算.