Jove
Visualize
Contact Us

Related Concept Videos

Poisson's And Laplace's Equation01:25

Poisson's And Laplace's Equation

The electric potential of the system can be calculated by relating it to the electric charge densities that give rise to the electric potential. The differential form of Gauss's law expresses the electric field's divergence in terms of the electric charge density.
Differential Form of Maxwell's Equations01:17

Differential Form of Maxwell's Equations

James Clerk Maxwell (1831–1879) was one of the significant contributors to physics in the nineteenth century. He is probably best known for having combined existing knowledge of the laws of electricity and the laws of magnetism with his insights to form a complete overarching electromagnetic theory, represented by Maxwell's equations. The four basic laws of electricity and magnetism were discovered experimentally through the work of physicists such as Oersted, Coulomb, Gauss, and Faraday.
Maxwell-Boltzmann Distribution: Problem Solving01:20

Maxwell-Boltzmann Distribution: Problem Solving

Individual molecules in a gas move in random directions, but a gas containing numerous molecules has a predictable distribution of molecular speeds, which is known as the Maxwell-Boltzmann distribution, f(v).
This distribution function f(v) is defined by saying that the expected number N (v1,v2) of particles with speeds between v1 and v2 is given by
Transmission-Line Differential Equations01:26

Transmission-Line Differential Equations

Transmission lines are essential components of electrical power systems. They are characterized by the distributed nature of resistance (R), inductance (L), and capacitance (C) per unit length. To analyze these lines, differential equations are employed to model the variations in voltage and current along the line.
Line Section Model
A circuit representing a line section of length Δx helps in understanding the transmission line parameters. The voltage V(x) and current i(x) are measured from the...
Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.
Debye–Huckel–Onsager Conductance Equation01:28

Debye–Huckel–Onsager Conductance Equation

The Debye-Hückel-Onsager equation is a cornerstone of physical chemistry, providing a method to determine the molar conductance (Λm) and molar conductance at infinite dilution (Λ°m) for uni-univalent electrolytes.Uni-univalent electrolytes are electrolytes that dissociate in solution to produce one cation with a +1 charge and one anion with a –1 charge per formula unit.This equation addresses two crucial phenomena: the asymmetry effect and the electrophoretic effect. According to this equation,...

You might also read

Related Articles

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

Sort by
Same author

Learning reduced-order models for cardiovascular simulations with graph neural networks.

Computers in biology and medicine·2023
Same author

Memory-Augmented Generative Adversarial Networks for Anomaly Detection.

IEEE transactions on neural networks and learning systems·2021
Same author

Circulating transcripts in maternal blood reflect a molecular signature of early-onset preeclampsia.

Science translational medicine·2020
Same author

Predicting Splicing from Primary Sequence with Deep Learning.

Cell·2019
Same author

Improved genome sequencing using an engineered transposase.

BMC biotechnology·2017
Same author

Computing the non-Markovian coarse-grained interactions derived from the Mori-Zwanzig formalism in molecular systems: Application to polymer melts.

The Journal of chemical physics·2017
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 Experiment Video

Updated: Jun 22, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

Computing generalized Langevin equations and generalized Fokker-Planck equations.

Eric Darve1, Jose Solomon, Amirali Kia

  • 1Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305, USA. darve@stanford.edu

Proceedings of the National Academy of Sciences of the United States of America
|June 25, 2009
PubMed
Summary

The Mori-Zwanzig formalism helps derive equations for system evolution. This study applies it to generalized Langevin and Fokker-Planck equations, extracting long time scales and metastable states with new numerical methods.

More Related Videos

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

Related Experiment Videos

Last Updated: Jun 22, 2026

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
11:03

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids

Published on: December 4, 2017

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

Area of Science:

  • Statistical Mechanics
  • Computational Physics
  • Dynamical Systems

Background:

  • The Mori-Zwanzig formalism is a powerful theoretical framework.
  • It enables the derivation of simplified equations for complex systems by focusing on a few key variables.
  • Its application to derive generalized Langevin equations (GLEs) and Fokker-Planck equations (FPEs) is crucial for understanding emergent dynamics.

Purpose of the Study:

  • To apply the Mori-Zwanzig formalism for deriving generalized Langevin equations and generalized non-Markovian Fokker-Planck equations.
  • To demonstrate the extraction of long time scale rates and metastable basins from these derived equations.
  • To develop and present efficient numerical algorithms for solving the resulting equations, particularly the high-dimensional orthogonal dynamics equation.

Main Methods:

  • Application of the Mori-Zwanzig projection formalism to derive generalized Langevin and Fokker-Planck equations.
  • Development of numerical algorithms for discretizing and solving these equations.
  • Implementation of efficient numerical methods for the high-dimensional orthogonal dynamics partial differential equation.
  • Extension of the Mori-Zwanzig formalism to discrete maps.

Main Results:

  • Successful derivation of generalized Langevin and Fokker-Planck equations using the Mori-Zwanzig formalism.
  • Demonstration of the ability to extract long time scale rates and identify metastable basins from the derived equations.
  • Proposal of efficient numerical techniques for solving the orthogonal dynamics equation, a key challenge in high-dimensional systems.
  • Adaptation of the formalism for discrete map systems.

Conclusions:

  • The Mori-Zwanzig formalism provides an effective pathway to simplified dynamical equations.
  • The developed numerical methods enable the efficient analysis of complex systems, including the extraction of important kinetic information.
  • The extended formalism is applicable to a broader range of systems, including discrete maps and Hamiltonian systems.