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

Temperature and Thermal Equilibrium01:11

Temperature and Thermal Equilibrium

9.0K
Heat and temperature are essential concepts for everyone every day. The study of heat and temperature is part of an area of physics known as thermodynamics. It is not always easy to distinguish heat and temperature.
The concept of temperature has evolved from the common concepts of hot and cold. The scientific definition of temperature explains more than just our sense of hot and cold. Temperature is operationally defined as the quantity measured with a thermometer. Furthermore, temperature is...
9.0K
Effect of Temperature Change on Reaction Rate02:28

Effect of Temperature Change on Reaction Rate

4.9K
The Arrhenius equation,
4.9K
Temperature Dependence on Reaction Rate02:55

Temperature Dependence on Reaction Rate

88.2K
The Collision Theory
Atoms, molecules, or ions must collide before they can react with each other. Atoms must be close together to form chemical bonds. This premise is the basis for a theory that explains many observations regarding chemical kinetics, including factors affecting reaction rates.
The collision theory is based on the postulates that (i) the reaction rate is proportional to the rate of reactant collisions, (ii) the reacting species collide in an orientation allowing contact between...
88.2K
Le Chatelier's Principle: Changing Temperature02:19

Le Chatelier's Principle: Changing Temperature

34.7K
Consistent with the law of mass action, an equilibrium stressed by a change in concentration will shift to re-establish equilibrium without any change in the value of the equilibrium constant, K. When an equilibrium shifts in response to a temperature change, however, it is re-established with a different relative composition that exhibits a different value for the equilibrium constant.
To understand this phenomenon, consider the elementary reaction:
34.7K
Effects of Temperature on Free Energy02:11

Effects of Temperature on Free Energy

27.8K
The spontaneity of a process depends upon the temperature of the system. Phase transitions, for example, will proceed spontaneously in one direction or the other depending upon the temperature of the substance in question. Likewise, some chemical reactions can also exhibit temperature-dependent spontaneities. To illustrate this concept, the equation relating free energy change to the enthalpy and entropy changes for the process is considered:
27.8K
Thermal expansion and Thermal stress: Problem Solving01:27

Thermal expansion and Thermal stress: Problem Solving

2.0K
San Francisco's Golden Gate Bridge is exposed to temperatures ranging from -15 °C to 40 °C. At its coldest, the main span of the bridge is 1275 m long. Assuming that the bridge is made entirely of steel, what is the change in its length between these temperatures?
To solve the problem, first, identify the known and unknown quantities. The initial length (L) of the bridge is 1275 m, the coefficient of linear expansion (α) for steel is 12 x 10-6/°C, and the change in temperature (ΔT) is 55...
2.0K

You might also read

Related Articles

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

Sort by
Same author

Accelerating hybrid XOR-CNF Boolean satisfiability problems natively with in-memory computing.

Nature communications·2026
Same author

Direct comparison of stochastic driven nonlinear dynamical systems for combinatorial optimization.

Physical review. E·2025
Same author

Behavior of Ising spins and ecological oscillators on dynamically rewired small-world networks.

Physical review. E·2025
Same author

Quadratic unconstrained binary optimization and constraint programming approaches for lattice-based cyclic peptide docking.

Scientific reports·2025
Same author

Optimal schedules for annealing algorithms.

Physical review. E·2024
Same author

Variation in Avian Predation Pressure as a Driver for the Diversification of Periodical Cicada Broods.

The American naturalist·2024

Related Experiment Video

Updated: Jan 3, 2026

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
04:35

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

Published on: July 5, 2024

2.3K

Effects of setting temperatures in the parallel tempering Monte Carlo algorithm.

Ignacio Rozada1, Maliheh Aramon1, Jonathan Machta2,3

  • 11QB Information Technologies (1QBit), Vancouver, BC, V6C 2B5, Canada.

Physical Review. E
|November 28, 2019
PubMed
Summary
This summary is machine-generated.

Optimizing temperature sets in parallel tempering Monte Carlo (PTMC) is key for efficiency. A feedback-optimized method offers significant speedups for problems with first-order phase transitions, outperforming other approaches.

More Related Videos

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer
10:11

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Published on: April 19, 2021

4.2K
Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
05:56

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

1.7K

Related Experiment Videos

Last Updated: Jan 3, 2026

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment
04:35

Author Spotlight: Simulation and Analysis of the Temperature Rise of Ring Main Unit Equipment

Published on: July 5, 2024

2.3K
Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer
10:11

Temperature-Controlled Assembly and Characterization of a Droplet Interface Bilayer

Published on: April 19, 2021

4.2K
Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches
05:56

Exploring Caspase Mutations and Post-Translational Modification by Molecular Modeling Approaches

Published on: October 13, 2022

1.7K

Area of Science:

  • Computational Physics
  • Statistical Mechanics
  • Optimization Algorithms

Background:

  • Parallel tempering Monte Carlo (PTMC) is a powerful technique for optimization and sampling.
  • Algorithm efficiency in PTMC is significantly enhanced by an optimized temperature set, leading to more frequent replica exchanges.
  • Existing methods for optimizing temperature sets fall into two categories: constant replica swapping ratios and temperature distributions with higher density at simulation bottlenecks.

Purpose of the Study:

  • To compare the performance of various temperature setting methods within parallel tempering Monte Carlo.
  • To evaluate these methods on diverse problems, including spin-glass and Wishart problems with varying phase transition characteristics.
  • To identify which temperature setting strategies are most effective for different types of computational challenges.

Main Methods:

  • Implementation and comparison of different temperature set optimization strategies for parallel tempering Monte Carlo.
  • Testing on sparse and fully connected spin-glass problems with continuous phase transitions.
  • Evaluation on fully connected Wishart problems exhibiting first-order phase transitions (discontinuous).

Main Results:

  • No performance advantage was observed for non-uniform swapping probability methods on spin-glass problems with smooth phase transitions.
  • The feedback-optimized method demonstrated a time-to-solution speedup of at least a factor of two for Wishart problems with first-order phase transitions.
  • This indicates that adaptive temperature distributions are beneficial for problems with discontinuous phase transitions.

Conclusions:

  • The choice of temperature setting strategy in parallel tempering Monte Carlo is problem-dependent.
  • Feedback-optimized methods excel in scenarios with first-order phase transitions, offering substantial computational speedups.
  • For problems with continuous phase transitions, simpler temperature distribution methods may suffice without performance degradation.