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

Parallel Processing01:20

Parallel Processing

179
The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...
179
Multimachine Stability01:25

Multimachine Stability

188
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
188
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

666
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...
666
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving01:29

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

79
Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
79
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

127
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
127
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

1.6K
Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
1.6K

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

Circulating osteocalcin: A potential predictor of ketosis in type 2 diabetes.

Diabetes/metabolism research and reviews·2019
Same author

Provincial and sector-level material footprints in China.

Proceedings of the National Academy of Sciences of the United States of America·2019
Same author

Functionalized selenium nanoparticles for targeted siRNA delivery silence Derlin1 and promote antitumor efficacy against cervical cancer.

Drug delivery·2019
Same author

Long non-coding RNA RNCR3 promotes glioma progression involving the Akt/GSK-3β pathway.

Oncology letters·2019
Same author

Doxorubicin-loaded functionalized selenium nanoparticles for enhanced antitumor efficacy in cervical carcinoma therapy.

Materials science & engineering. C, Materials for biological applications·2019
Same author

Functionalization of Silver Nanoparticles Loaded with Paclitaxel-induced A549 Cells Apoptosis Through ROS-Mediated Signaling Pathways

Current topics in medicinal chemistry·2019

相关实验视频

Updated: Jul 17, 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

598

为多任务机器学习进行配置的量子储库计算.

Wei Xia1, Jie Zou1, Xingze Qiu2

  • 1State Key Laboratory of Surface Physics, Key Laboratory of Micro and Nano Photonic Structures (MOE), and Department of Physics, Fudan University, Shanghai 200433, China.

Science bulletin
|September 7, 2023
PubMed
概括
此摘要是机器生成的。

研究人员在可编程量子设备上配置了量子储库计算,以提高学习性能. 这种量子方法准确地预测复杂的系统和金融市场,优于经典方法.

关键词:
配置的量子储库计算计算.多任务学习多任务学习量子优势是一个量子优势.量子连贯性就是量子连贯性.

更多相关视频

Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

12.9K
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

相关实验视频

Last Updated: Jul 17, 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

598
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

12.9K
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

科学领域:

  • 量子计算是一种量子计算.
  • 人工智能的人工智能
  • 计算科学 计算科学

背景情况:

  • 可编程噪声中间尺度量子 (NISQ) 设备为量子计算优势提供了新的途径.
  • 量子储库计算利用量子动力学来完成机器学习任务.
  • 配置量子储库可以系统地提高学习性能.

研究的目的:

  • 探索可编程NISQ设备用于量子储库计算的动态.
  • 系统地提高学习效率,使用一个遗传算法来配置水库.
  • 为了评估与经典方法相比配置量子储库计算的性能.

主要方法:

  • 利用遗传算法来配置量子储库动力学.
  • 应用于各种学习任务的配置量子储库:合成基因网络,混乱电路和外汇市场.
  • 量子储库计算性能与经典储库计算性能进行了比较.

主要成果:

  • 一个单个配置的量子容器成功地同时学习了多个复杂的任务.
  • 在所有测试的应用中实现了高度精确的预测,在所有测试的应用中表现优于经典的水库计算.
  • 在捕捉外汇市场动态方面表现出卓越的准确性.

结论:

  • 配置量子储库计算有效地利用NISQ设备进行先进的机器学习.
  • 量子连贯性在量子储库的优越学习能力中起着至关重要的作用.
  • 这种方法显示出开发通用人工智能的巨大潜力.