Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

State Space Representation01:27

State Space Representation

631
The frequency-domain technique, commonly used in analyzing and designing feedback control systems, is effective for linear, time-invariant systems. However, it falls short when dealing with nonlinear, time-varying, and multiple-input multiple-output systems. The time-domain or state-space approach addresses these limitations by utilizing state variables to construct simultaneous, first-order differential equations, known as state equations, for an nth-order system.
Consider an RLC circuit, a...
631
State Space to Transfer Function01:21

State Space to Transfer Function

629
The conversion of state-space representation to a transfer function is a fundamental process in system analysis. It provides a method for transitioning from a time-domain description to a frequency-domain representation, which is crucial for simplifying the analysis and design of control systems.
The transformation process begins with the state-space representation, characterized by the state equation and the output equation. These equations are typically represented as:
629
Transfer Function to State Space01:23

Transfer Function to State Space

852
State-space representation is a powerful tool for simulating physical systems on digital computers, necessitating the conversion of the transfer function into state-space form. Consider an nth-order linear differential equation with constant coefficients, like those encountered in an RLC circuit. The state variables are selected as the output and its n−1 derivatives. Differentiating these variables and substituting them back into the original equation produces the state equations.
In an RLC...
852
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

1.3K
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 the...
1.3K
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

60.3K
Shortly after de Broglie published his ideas that the electron in a hydrogen atom could be better thought of as being a circular standing wave instead of a particle moving in quantized circular orbits, Erwin Schrödinger extended de Broglie’s work by deriving what is now known as the Schrödinger equation. When Schrödinger applied his equation to hydrogen-like atoms, he was able to reproduce Bohr’s expression for the energy and, thus, the Rydberg formula governing hydrogen spectra.
60.3K
Observational Learning01:12

Observational Learning

1.1K
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
1.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Explainable deep-learning-based ischemia detection using hybrid O-15 H<sub>2</sub>O perfusion positron emission tomography and computed tomography imaging with clinical data.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology·2024
Same author

Plaque volume, composition, and fraction versus ischemia and outcomes in patients with coronary artery disease.

Journal of cardiovascular computed tomography·2023
Same author

Incorporating coronary artery calcium scoring in the prediction of obstructive coronary artery disease with myocardial ischemia: a study with sequential use of coronary computed tomography angiography and positron emission tomography imaging.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology·2022
Same author

Coronary computed tomography angiography-based endothelial wall shear stress in normal coronary arteries.

The international journal of cardiovascular imaging·2022
Same author

Importance of plaque volume and composition for the prediction of myocardial ischaemia using sequential coronary computed tomography angiography/positron emission tomography imaging.

European heart journal. Cardiovascular Imaging·2022
Same author

Detailed behaviour of endothelial wall shear stress across coronary lesions from non-invasive imaging with coronary computed tomography angiography.

European heart journal. Cardiovascular Imaging·2022
Same journal

Computational modelling distinguishes diverse contributors to aneurysmal progression in the Marfan aorta.

Proceedings. Mathematical, physical, and engineering sciences·2025
Same journal

Inferring the shape of data: a probabilistic framework for analysing experiments in the natural sciences.

Proceedings. Mathematical, physical, and engineering sciences·2023
Same journal

The Elbert range of magnetostrophic convection. I. Linear theory.

Proceedings. Mathematical, physical, and engineering sciences·2022
Same journal

Soft wetting with (a)symmetric Shuttleworth effect.

Proceedings. Mathematical, physical, and engineering sciences·2022
Same journal

The quantum theory of time: a calculus for q-numbers.

Proceedings. Mathematical, physical, and engineering sciences·2022
Same journal

Integrable nonlinear evolution equations in three spatial dimensions.

Proceedings. Mathematical, physical, and engineering sciences·2022
See all related articles

Related Experiment Video

Updated: Mar 1, 2026

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
09:23

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Published on: May 30, 2014

15.1K

Probing quantum state space: does one have to learn everything to learn something?

Claudio Carmeli1, Teiko Heinosaari2, Jussi Schultz2

  • 1DIME, Università di Genova, Via Magliotto 2, 17100 Savona, Italy.

Proceedings. Mathematical, Physical, and Engineering Sciences
|June 8, 2017
PubMed
Summary
This summary is machine-generated.

Researchers explored if full quantum state determination is always necessary for specific tasks. They found that less demanding measurements can suffice, optimizing quantum information processing.

Keywords:
fidelitypurityquantum measurementquantum tomographyvon Neumann entropy

More Related Videos

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

1.2K
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

13.3K

Related Experiment Videos

Last Updated: Mar 1, 2026

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators
09:23

Quantum State Engineering of Light with Continuous-wave Optical Parametric Oscillators

Published on: May 30, 2014

15.1K
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

1.2K
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

13.3K

Area of Science:

  • Quantum Information Science
  • Quantum Measurement Theory

Background:

  • Determining the complete state of a quantum system is resource-intensive.
  • Often, only specific properties of a quantum state are of interest.

Purpose of the Study:

  • To investigate if informationally complete measurements are essential for all quantum state property determination tasks.
  • To determine if less demanding measurement strategies can achieve specific quantum information goals.

Main Methods:

  • Formulated the task as a membership problem within the quantum state space.
  • Analyzed the geometry of the quantum state space to establish criteria for measurement completeness.
  • Studied physically relevant examples to validate theoretical findings.

Main Results:

  • Proved sufficient criteria that necessitate informationally complete measurements for general membership problems.
  • Identified specific cases where informationally complete measurements are not required.
  • Determined the minimal number of measurement outcomes needed for tasks not requiring full state determination.

Conclusions:

  • Informationally complete measurements are not always required for characterizing quantum states.
  • Optimized measurement strategies can reduce the resources needed for specific quantum information tasks.
  • The geometry of the quantum state space plays a crucial role in determining measurement requirements.