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

Multimachine Stability01:25

Multimachine Stability

587
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:
587
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

431
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 of...
431
Sequence Networks of Rotating Machines01:24

Sequence Networks of Rotating Machines

505
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
505
State Space Representation01:27

State Space Representation

622
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...
622
Two-Dimensional Force System: Problem Solving01:29

Two-Dimensional Force System: Problem Solving

1.4K
Solving problems related to two-dimensional force systems is an essential aspect of mechanics and engineering. By applying the principles of vector analysis and force equilibrium, one can determine the effect of multiple forces acting on an object in a two-dimensional space.
The first step to solving a two-dimensional force system problem is to draw a free-body diagram of the object under consideration. This diagram helps identify all the external forces acting on the object, including their...
1.4K
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

379
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
379

You might also read

Related Articles

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

Sort by
Same author

Lightweight cloud masking models for on-board inference in hyperspectral imaging.

Scientific reports·2026
Same author

epiGPTope: A Machine Learning-Based Epitope Generator and Classifier.

ACS synthetic biology·2026
Same author

Limitations of quantum hardware for molecular energy estimation using VQE.

Physical chemistry chemical physics : PCCP·2026
Same author

Quantum-inspired clustering with light.

Scientific reports·2024
Same author

Variational tensor neural networks for deep learning.

Scientific reports·2024
Same author

Physically Motivated Improvements of Variational Quantum Eigensolvers.

Journal of chemical theory and computation·2024
Same journal

Demonstration of a quantum C-NOT gate in a time-multiplexed fully reconfigurable photonic processor.

Nature communications·2026
Same journal

Nonlinear quantum light source with van der Waals ferroelectric NbOX<sub>2</sub> (X = Br, I).

Nature communications·2026
Same journal

Antagonistic histone H2A variants and autonomous heterochromatin formation shape epigenomic patterns in Arabidopsis.

Nature communications·2026
Same journal

The long tail of nitrate pollution in groundwater challenges governance of global water quality.

Nature communications·2026
Same journal

Select microbial metabolites promote tau aggregation in a murine tauopathy model.

Nature communications·2026
Same journal

Warming climate has lengthened global intense tropical cyclone seasons.

Nature communications·2026
See all related articles

Related Experiment Video

Updated: Feb 19, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.1K

A simple tensor network algorithm for two-dimensional steady states.

Augustine Kshetrimayum1, Hendrik Weimer2, Román Orús3

  • 1Institute of Physics, Johannes Gutenberg University, 55099, Mainz, Germany.

Nature Communications
|November 4, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces a novel tensor network algorithm for simulating 2D quantum many-body systems with dissipation. The method efficiently approximates steady states, revealing phase transitions in dissipative quantum models.

Related Experiment Videos

Last Updated: Feb 19, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.1K

Area of Science:

  • Quantum physics
  • Condensed matter physics
  • Computational physics

Background:

  • Dissipation in 2D quantum many-body systems presents significant computational challenges.
  • Understanding steady states in these systems is crucial for various applications.

Purpose of the Study:

  • To develop a numerical method for simulating steady states of 2D quantum lattice dissipative systems.
  • To investigate phase transitions in specific dissipative quantum models.

Main Methods:

  • A tensor network algorithm is employed to approximate steady states in the thermodynamic limit.
  • The algorithm leverages the principle that strong dissipation limits quantum entanglement growth.
  • Simulations were benchmarked against a variational algorithm using product and correlated states.

Main Results:

  • The study successfully simulated a dissipative quantum Ising model, supporting a first-order phase transition without bistability.
  • Simulations of a dissipative spin 1/2 XYZ model indicated no re-entrance of the ferromagnetic phase.
  • The tensor network method proved effective for computing steady states in 2D quantum lattice systems.

Conclusions:

  • The developed tensor network algorithm provides a viable approach for studying dissipation in 2D quantum many-body systems.
  • The findings offer insights into the nature of phase transitions in dissipative quantum models.
  • This method opens new avenues for exploring complex quantum phenomena computationally.