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

The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

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. Schrödinger...
The Bohr Model02:18

The Bohr Model

Following the work of Ernest Rutherford and his colleagues in the early twentieth century, the picture of atoms consisting of tiny dense nuclei surrounded by lighter and even tinier electrons continually moving about the nucleus was well established. This picture was called the planetary model since it pictured the atom as a miniature “solar system” with the electrons orbiting the nucleus like planets orbiting the sun. The simplest atom is hydrogen, consisting of a single proton as the nucleus...
State Space Representation01:27

State Space Representation

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...
Ampere-Maxwell's Law: Problem-Solving01:17

Ampere-Maxwell's Law: Problem-Solving

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

Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving

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...
State Space to Transfer Function01:21

State Space to Transfer Function

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:

You might also read

Related Articles

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

Sort by
Same author

SERS Facemask for Rapid and Portable Sensing Mycobacterium Tuberculosis Antigens for TB Screening.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

ATF3 in metabolic homeostasis and vascular disease: integrating bibliometric evidence with therapeutic potential.

American journal of physiology. Endocrinology and metabolism·2026
Same author

Molecular mechanisms and therapeutic targets of traditional Chinese Medicine compounds in renal cell carcinoma: A comprehensive narrative review.

Journal of ethnopharmacology·2026
Same author

Letter: Predictors and Outcomes of Pulmonary Embolism After Coronary Artery Bypass Grafting.

Angiology·2026
Same author

A case-control study on blood vessel morphology, hemodynamic parameters, and rupture status of posterior communicating artery aneurysms.

Frontiers in neurology·2026
Same author

Persistent Fermi pockets and robust electron pairing in lightly doped CuO<sub>2</sub> planes of cuprate superconductors.

Nature communications·2026
Same journal

The BRCA1-A complex restricts replication fork reversal-dependent DNA repair in ATM deficient cells.

Nature communications·2026
Same journal

Signaling downstream of tumor-stroma interaction regulates mucinous colorectal adenocarcinoma apicobasal polarity.

Nature communications·2026
Same journal

Click-polymerized polyenamine membranes for efficient lithium extraction.

Nature communications·2026
Same journal

Joint trajectories of brain atrophy, white matter hyperintensities and cognition quantify brain maintenance.

Nature communications·2026
Same journal

Proton shuttling at electrochemical interfaces under alkaline hydrogen evolution.

Nature communications·2026
Same journal

metilene<sup>3</sup>: identifying DMRs across multiple conditions with auto-classification.

Nature communications·2026
See all related articles

Related Experiment Video

Updated: Jun 24, 2026

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

Solving the Hubbard model with neural quantum states.

Yuntian Gu1,2, Wenrui Li1,2, Heng Lin2,3

  • 1State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University, Beijing, China.

Nature Communications
|June 22, 2026
PubMed
Summary
This summary is machine-generated.

Neural quantum states (NQS) achieve state-of-the-art results for the 2D Hubbard model, revealing stripe correlations crucial for high-Tc superconductivity. This demonstrates NQS

Related Experiment Videos

Last Updated: Jun 24, 2026

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
07:56

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference

Published on: September 5, 2019

Area of Science:

  • Computational Physics
  • Quantum Many-Body Systems
  • Condensed Matter Physics

Background:

  • Neural quantum states (NQS) offer a promising framework for simulating complex quantum systems.
  • The two-dimensional (2D) Hubbard model is a fundamental model for understanding high-temperature superconductivity.
  • Capturing long-range correlations in strongly correlated systems remains a significant challenge.

Purpose of the Study:

  • To apply transformer-based NQS with advanced optimization to the doped 2D Hubbard model.
  • To investigate the ability of NQS to encode correlations at various scales.
  • To identify ground-state properties relevant to high-Tc superconductivity.

Main Methods:

  • Utilized transformer-based neural quantum states (NQS) architectures.
  • Developed efficient optimization algorithms for training NQS.
  • Applied the NQS framework to the doped two-dimensional (2D) Hubbard model.

Main Results:

  • Achieved state-of-the-art results for the doped 2D Hubbard model.
  • Demonstrated that different attention heads in NQS capture correlations at different scales.
  • Found evidence for half-filled stripe correlations in the ground state, consistent with cuprate experiments.

Conclusions:

  • NQS, particularly transformer-based architectures, are powerful tools for solving challenging many-fermion systems.
  • NQS can effectively capture long-range correlations in strongly correlated materials.
  • The findings provide insights into the mechanism of high-Tc superconductivity.