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

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...
Woodward–Hoffmann Selection Rules and Microscopic Reversibility01:34

Woodward–Hoffmann Selection Rules and Microscopic Reversibility

Electrocyclic reactions, cycloadditions, and sigmatropic rearrangements are concerted pericyclic reactions that proceed via a cyclic transition state. These reactions are stereospecific and regioselective. The stereochemistry of the products depends on the symmetry characteristics of the interacting orbitals and the reaction conditions. Accordingly, pericyclic reactions are classified as either symmetry-allowed or symmetry-forbidden. Woodward and Hoffmann presented the selection criteria for...
Mechanistic Models: Overview of Compartment Models01:21

Mechanistic Models: Overview of Compartment Models

Mechanistic models, a category encompassing both physiological and compartmental modeling, differ from empirical models' approaches to incorporating known factors about the systems being modeled. Empirical models describe data with minimal assumptions, while mechanistic models aim to provide a robust description of available data by specifying assumptions and integrating known factors about the system. Compartmental analysis is a key example of a mechanistic model in pharmacokinetics and...
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...
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
Modeling with Differential Equations01:25

Modeling with Differential Equations

Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...

You might also read

Related Articles

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

Sort by
Same author

Multiconfigurational Gaussian wavepacket simulations of exciton diffusion in semiconducting polymer chains: Efficient finite-temperature simulations with Langevin driving.

The Journal of chemical physics·2026
Same author

Spin-orbit coupling and beyond in chiral-induced spin selectivity.

Nanoscale·2026
Same author

Precise Quantum Chemistry calculations with few Slater Determinants.

Nature communications·2026
Same author

Excitation Energy Transfer in an Intermediate Regime: A Multiconfigurational Gaussian Wavepacket Study of a Light-Harvesting Supramolecular Dyad.

The journal of physical chemistry letters·2026
Same author

Reduced density matrices and phase-space distributions in thermofield dynamics.

The Journal of chemical physics·2026
Same author

A Haldane-Anderson Hamiltonian model for hyperthermal hydrogen scattering from a semiconductor surface.

The Journal of chemical physics·2026

Related Experiment Video

Updated: May 17, 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

Non-Markovian reduced dynamics based upon a hierarchical effective-mode representation.

Irene Burghardt1, Rocco Martinazzo, Keith H Hughes

  • 1Institute of Physical and Theoretical Chemistry, Goethe University Frankfurt, Max-von-Laue-Str. 7, 60438 Frankfurt, Germany. burghardt@theochem.uni-frankfurt.de

The Journal of Chemical Physics
|October 16, 2012
PubMed
Summary
This summary is machine-generated.

This study introduces a reduced dynamics approach for spin-boson systems, simplifying complex interactions. The method effectively models system-environment dynamics using truncated chains for enhanced correlation function calculations.

More Related Videos

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism
08:44

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

Published on: October 17, 2025

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

Related Experiment Videos

Last Updated: May 17, 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

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism
08:44

Dynamic Clamp Methods to Investigate Impaired Neuronal Excitability Associated with Autism

Published on: October 17, 2025

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
06:44

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

Area of Science:

  • Quantum mechanics
  • Condensed matter physics
  • Theoretical chemistry

Background:

  • Complex quantum systems often involve interactions between a central subsystem and a large environment (bath).
  • Accurately modeling these system-environment interactions is crucial for understanding quantum dynamics but computationally challenging.
  • Hierarchical, Mori-chain representations are common for bath dynamics but can become complex.

Purpose of the Study:

  • To develop a reduced dynamics representation tailored for hierarchical bath models.
  • To simplify the treatment of system-environment interactions in spin-boson systems.
  • To derive computationally tractable methods for calculating correlation functions.

Main Methods:

  • Introduced a reduced dynamics representation for a bath of harmonic oscillators coupled to a subsystem.
  • Constructed a single effective mode to absorb system-environment interactions.
  • Employed a cumulant expansion of the memory kernel to obtain correlation functions.
  • Approximated interactions using truncated chains and continued-fraction forms for spectral densities.

Main Results:

  • Developed a method to represent complex system-environment interactions through a single effective mode.
  • Obtained correlation functions for the primary mode via a cumulant expansion.
  • Derived reduced-dimensional bath correlation functions expressed as Fourier-Laplace transforms of spectral densities.
  • Re-expressed the memory kernel in local-in-time equations for a second-order master equation.

Conclusions:

  • The reduced dynamics approach offers a simplified yet accurate model for quantum system-environment interactions.
  • The method facilitates the calculation of correlation functions and spectral densities in truncated continued-fraction form.
  • This work provides a computationally efficient framework for studying quantum dynamics in complex systems.