Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Quantum Numbers

Quantum Numbers

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.

The Quantum-Mechanical Model of an Atom

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.

Heat and Free Expansion

Heat and Free Expansion

The work done by a thermodynamic system depends not only on the initial and final states but also on the intermediate states—that is, on the path. Like work, when heat is added to a thermodynamic system, it undergoes a change of state, and the state attained depends on the path from the initial state to the final state. Consider an ideal gas cylinder fitted with a piston. When the cylinder is heated at a constant temperature, the gas molecules absorb energy and expand slowly in a...

Thermal Expansion

Thermal Expansion

The expansion of alcohol in a thermometer is one of many commonly encountered examples of thermal expansion, which is the change in size or volume of a given system as its temperature changes. The most visible example is the expansion of hot air. When air is heated, it expands and becomes less dense than the surrounding air, which then exerts an upward force on the hot air to, for example, make steam and smoke rise, and hot air balloons float. The same behavior happens in all liquids and gases,...

Binomial Expansion Using Pascal's Triangle

Binomial Expansion Using Pascal's Triangle

Expanding a binomial expression such as (a + b)n results in a predictable sequence of terms that can be systematically derived using Pascal’s Triangle. This triangular array of numbers plays a central role in understanding and computing the coefficients of binomial expansions.Pascal’s Triangle is constructed such that each row corresponds to the coefficients of a binomial raised to a power. The topmost row, known as the zeroth row, corresponds to (a + b)0, and each successive row...

Expansion and Contraction in Masonry Walls

Expansion and Contraction in Masonry Walls

Masonry walls are subject to slight expansion and contraction due to variations in temperature and moisture. Thermal movement in masonry is relatively straightforward to measure and plan for. On the other hand, moisture movement poses more of a challenge. New clay masonry units typically absorb water and expand over time under normal environmental conditions. Conversely, new concrete masonry units tend to shrink as they lose the excess moisture acquired during their production process.
To...

You might also read

Related Articles

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

Sort by

Same author

Optimizing temperature distributions for training neural quantum states using parallel tempering.

Physical review. E·2025

Same author

Resolution of the sign problem for a frustrated triplet of spins.

Physical review. E·2019

Same author

On the computational complexity of curing non-stoquastic Hamiltonians.

Nature communications·2019

Same author

Finite temperature quantum annealing solving exponentially small gap problem with non-monotonic success probability.

Nature communications·2018

Same author

Solving spin glasses with optimized trees of clustered spins.

Physical review. E·2017

Same author

Temperature Scaling Law for Quantum Annealing Optimizers.

Physical review letters·2017

Same journal

Erratum: Low-dimensional model for adaptive networks of spiking neurons [Phys. Rev. E 111, 014422 (2025)].

Physical review. E·2026

Same journal

Disentangling the effects of many-body forces on depletion interactions.

Physical review. E·2026

Same journal

Charge transport and mode transition in dual-energy electron beam diodes.

Physical review. E·2026

Same journal

Optimization of multisite reactions in complex compartmentalized media.

Physical review. E·2026

Same journal

Origin of geometric cohesion in nonconvex granular materials: Interplay between interdigitation and rotational constraints enhancing frictional stability.

Physical review. E·2026

Same journal

Interaction of walkers with a standing Faraday wave.

Physical review. E·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Feb 15, 2026

Diagonal Method to Measure Synergy Among Any Number of Drugs

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

Off-diagonal expansion quantum Monte Carlo.

Tameem Albash^1,2, Gene Wagenbreth³, Itay Hen^1,2

¹Information Sciences Institute, University of Southern California, Marina del Rey, California 90292, USA.

Physical Review. E

|January 20, 2018

Summary

This summary is machine-generated.

We developed a new Monte Carlo algorithm for simulating quantum and classical systems, unifying thermal simulation techniques. This method efficiently handles systems from fully quantum to fully classical behaviors.

More Related Videos

Gradient Echo Quantum Memory in Warm Atomic Vapor

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

Production and Targeting of Monovalent Quantum Dots

Production and Targeting of Monovalent Quantum Dots

Published on: October 23, 2014

Related Experiment Videos

Last Updated: Feb 15, 2026

Diagonal Method to Measure Synergy Among Any Number of Drugs

Diagonal Method to Measure Synergy Among Any Number of Drugs

Published on: June 21, 2018

Gradient Echo Quantum Memory in Warm Atomic Vapor

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

Production and Targeting of Monovalent Quantum Dots

Production and Targeting of Monovalent Quantum Dots

Published on: October 23, 2014

Area of Science:

Computational Physics
Quantum Many-Body Systems
Statistical Mechanics

Background:

Simulating quantum systems at equilibrium presents significant algorithmic challenges, often requiring distinct methods for quantum and classical approaches.
Existing quantum Monte Carlo methods may struggle with systems exhibiting a spectrum of quantum to classical behavior.

Purpose of the Study:

To introduce a novel Monte Carlo algorithm capable of simulating both quantum and classical systems at equilibrium.
To bridge the existing algorithmic gap between quantum and classical thermal simulation.

Main Methods:

The proposed method decomposes the quantum partition function as a series expansion around its classical component.
It unifies quantum and classical thermal parallel tempering techniques into a single algorithmic framework.

Main Results:

The algorithm demonstrates significant advantages, achieving orders-of-magnitude improvements over state-of-the-art methods like path integral quantum Monte Carlo and stochastic series expansion.
It effectively simulates quantum many-body systems across the entire spectrum from fully quantum to fully classical.

Conclusions:

This new Monte Carlo algorithm represents a theoretical advancement in quantum simulation.
It offers a unified and efficient approach for tackling diverse quantum many-body systems and practical thermal simulation problems.