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

Dimensional Analysis01:23

Dimensional Analysis

2.6K
Dimensional analysis is a powerful tool that is used in physics and engineering to understand and predict the behavior of physical systems. The basic idea behind dimensional analysis is to express physical quantities in terms of fundamental dimensions such as the mass, length, and time. Derived dimensions like the velocity, acceleration, and force are derived from the combinations of these fundamental dimensions.
Dimensional analysis allows us to analyze and compare physical quantities on a...
2.6K
Dimensional Analysis01:27

Dimensional Analysis

860
Dimensional analysis is a valuable technique in fluid mechanics for simplifying complex problems by reducing them into dimensionless groups. These groups capture the essential relationships between the variables involved, allowing researchers and engineers to analyze fluid flow without dealing with each variable individually. This approach reduces the number of independent variables, allowing for easier analysis and better understanding of physical phenomena.
In fluid mechanics, dimensional...
860
Dimensional Analysis03:40

Dimensional Analysis

51.4K
Dimensional analysis, also known as the factor label method, is a versatile approach for mathematical operations. The main principle behind this approach is: the units of quantities must be subjected to the same mathematical operations as their associated numbers. This method can be applied to computations ranging from simple unit conversions to more complex and multi-step calculations involving several different quantities and their units.
Conversion Factors and Dimensional Analysis
The unit...
51.4K
Dimensional Analysis02:19

Dimensional Analysis

19.4K
The concept of dimension is important because every mathematical equation linking physical quantities must be dimensionally consistent, implying that mathematical equations must meet the following two rules. The first rule is that, in an equation, the expressions on each side of the equal sign must have the same dimensions. This is fairly intuitive since we can only add or subtract quantities of the same type (dimension). The second rule states that, in an equation, the arguments of any of the...
19.4K
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

500
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
500
Quantum Numbers02:43

Quantum Numbers

39.8K
It is said that the energy of an electron in an atom is quantized; that is, it can be equal only to certain specific values and can jump from one energy level to another but not transition smoothly or stay between these levels.
39.8K

You might also read

Related Articles

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

Sort by
Same author

Control simulations of many-body quantum systems by a synergism of discrete real-time learning and optimal control theory.

The Journal of chemical physics·2025
Same author

Machine learning for estimation and control of quantum systems.

National science review·2025
Same author

Tomography of Quantum States From Structured Measurements via Quantum-Aware Transformer.

IEEE transactions on cybernetics·2025
Same author

Direction of impact for explainable risk assessment modeling.

Risk analysis : an official publication of the Society for Risk Analysis·2025
Same author

Ultrafast control of the LnF<sup>+</sup>/LnO<sup>+</sup> ratio from Ln(hfac)<sub>3</sub>.

Physical chemistry chemical physics : PCCP·2024
Same author

The Surprising Ease of Finding Optimal Solutions for Controlling Nonlinear Phenomena in Quantum and Classical Complex Systems.

The journal of physical chemistry. A·2023
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

Related Experiment Video

Updated: Apr 30, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.0K

Dynamic dimensionality identification for quantum control.

Jonathan Roslund1, Herschel Rabitz1

  • 1Department of Chemistry, Princeton University, Princeton, New Jersey 08544, USA.

Physical Review Letters
|April 29, 2014
PubMed
Summary
This summary is machine-generated.

Quantum control using shaped laser pulses is simplified by understanding that dimensionality depends on participating states, not pulse shaper elements. Measuring the Hessian matrix reveals this reduced dimensionality for atomic rubidium control.

More Related Videos

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy
06:37

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

5.0K

Related Experiment Videos

Last Updated: Apr 30, 2026

Generation and Coherent Control of Pulsed Quantum Frequency Combs
06:42

Generation and Coherent Control of Pulsed Quantum Frequency Combs

Published on: June 8, 2018

9.0K
Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy
06:37

Quantifying Cytoskeleton Dynamics Using Differential Dynamic Microscopy

Published on: June 15, 2022

5.0K

Area of Science:

  • Quantum control
  • Laser physics
  • Atomic physics

Background:

  • Controlling quantum systems with shaped laser pulses appears complex due to numerous pulse shape possibilities.
  • Quantum landscape theory suggests the effective dimensionality is lower, related to system states rather than pulse shaper components.

Purpose of the Study:

  • To investigate the dimensionality of quantum control search spaces.
  • To test the predictions of quantum landscape theory regarding control dimensionality.
  • To develop a method for characterizing the essential dynamics of light-matter interactions.

Main Methods:

  • Measurement of the Hessian matrix for controlled transitions between states in atomic rubidium.
  • Eigendecomposition of the Hessian matrix to determine the effective dimensionality.
  • Analysis of the sensitivity of observed yield to pulse shaper elements.

Main Results:

  • The measured dimensionality of the quantum control landscape is consistent with predictions from quantum landscape theory.
  • The eigendecomposition revealed a low-dimensional picture of the light-matter interaction.
  • The sensitivity analysis confirmed that dimensionality is linked to the number of participating states.

Conclusions:

  • The effective dimensionality of quantum control is determined by the number of states involved in the dynamics, not the complexity of the pulse shaper.
  • Hessian matrix analysis provides a robust method for characterizing quantum control landscapes.
  • This approach simplifies the understanding of light-matter interactions and quantum dynamics.