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

Quantum Numbers02:43

Quantum Numbers

50.8K
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.
50.8K
Orthogonal Trajectories01:26

Orthogonal Trajectories

70
Orthogonal trajectories describe the geometric relationship between two families of curves that intersect each other at right angles. One illustrative case involves a family of parabolas that open sideways along the x-axis. These curves share a common shape but differ by a scaling parameter, resulting in a set of curves that all pass through the origin and widen at different rates.Determining Orthogonal TrajectoriesTo identify the orthogonal trajectories for these parabolas, the first step...
70
The Quantum-Mechanical Model of an Atom02:45

The Quantum-Mechanical Model of an Atom

58.4K
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.
58.4K
Classical Conditioning01:18

Classical Conditioning

2.3K
Associative learning, a core principle in behavioral psychology, involves forming connections between events and facilitating learned responses. This concept is vividly illustrated by classical conditioning, a process extensively studied by the Russian physiologist Ivan Pavlov. Pavlov's pioneering research on dogs' digestive systems led to the discovery that behaviors can be learned through association, laying the groundwork for classical conditioning.
Ivan Pavlov observed that dogs...
2.3K
Trial and Error and Algorithm01:12

Trial and Error and Algorithm

424
A problem-solving strategy is a plan of action used to find a solution. Different strategies have distinct action plans. Trial and error involves trying different solutions until one works. For instance, to fix a broken printer, you might check ink levels, ensure the paper tray isn't jammed, and verify the printer's connection to your laptop. This method can be time-consuming but is commonly used. Thomas Edison, for example, used trial and error to find a suitable filament for the light...
424
Principles of Classical Conditioning01:23

Principles of Classical Conditioning

1.9K
Classical conditioning, as described by Ivan Pavlov, is a foundational concept in associative learning, where a neutral stimulus becomes capable of eliciting a conditioned response through association with an unconditioned stimulus. The process of acquisition, where this learning occurs, and the subsequent phenomena of contiguity, contingency, generalization, discrimination, extinction, and spontaneous recovery are crucial for a comprehensive understanding of classical conditioning.
During the...
1.9K

You might also read

Related Articles

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

Sort by
Same author

Correction to "Capturing the Elusive Curve-Crossing in Low-Lying States of Butadiene With Dressed TDDFT".

The journal of physical chemistry letters·2026
Same author

A Coupled-Trajectory Strategy for Decoherence, Frustrated Hops and Internal Consistency in Surface Hopping.

Journal of chemical theory and computation·2026
Same author

Perspective on Many-Body Methods for Molecular Polaritonic Systems.

Journal of chemical theory and computation·2025
Same author

Excited-State Densities from Time-Dependent Density Functional Response Theory.

Journal of chemical theory and computation·2025
Same author

Quantum Dynamics Predicts Coherent Oscillations in the Early Times of a Biological Photoisomerization.

The journal of physical chemistry letters·2025
Same author

Roadmap for Molecular Benchmarks in Nonadiabatic Dynamics.

The journal of physical chemistry. A·2025

Related Experiment Video

Updated: Feb 7, 2026

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source
12:19

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source

Published on: April 4, 2017

8.9K

Coupled-Trajectory Mixed Quantum-Classical Algorithm: A Deconstruction.

Graeme H Gossel1, Federica Agostini2, Neepa T Maitra1,3

  • 1Department of Physics and Astronomy , Hunter College and the City University of New York , 695 Park Avenue , New York , New York 10065 , United States.

Journal of Chemical Theory and Computation
|August 1, 2018
PubMed
Summary
This summary is machine-generated.

This study analyzes a mixed quantum-classical algorithm, revealing the crucial role of electronic coupled-trajectory terms in accurate quantum dynamics and decoherence. Nuclear terms show minimal impact, aiding in understanding nonadiabatic processes.

More Related Videos

Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

13.2K
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

9.7K

Related Experiment Videos

Last Updated: Feb 7, 2026

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source
12:19

Measurement of Quantum Interference in a Silicon Ring Resonator Photon Source

Published on: April 4, 2017

8.9K
Gradient Echo Quantum Memory in Warm Atomic Vapor
10:00

Gradient Echo Quantum Memory in Warm Atomic Vapor

Published on: November 11, 2013

13.2K
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

9.7K

Area of Science:

  • Quantum mechanics
  • Chemical physics
  • Computational chemistry

Background:

  • Mixed quantum-classical algorithms are essential for simulating complex chemical dynamics.
  • The exact factorization equations provide a rigorous framework for quantum-classical descriptions.
  • Understanding decoherence and wavepacket branching is key to accurate simulations.

Purpose of the Study:

  • To analyze the role of different terms in a mixed quantum-classical algorithm derived from exact factorization equations.
  • To elucidate the contributions of electronic and nuclear coupled-trajectory terms to decoherence and wavepacket branching.
  • To compare the decoherence time with other established methods like surface-hopping.

Main Methods:

  • Analysis of a mixed quantum-classical algorithm based on Ehrenfest equations with coupled-trajectory terms.
  • Investigation of nonadiabatic terms within both electronic and nuclear equations.
  • Extraction and comparison of decoherence times using Tully model systems.

Main Results:

  • The coupled-trajectory term in the electronic equation is critical for accurate dynamics.
  • The coupled-trajectory term in the nuclear equation has a minor effect on the dynamics.
  • Decoherence times derived from the electronic equations were compared to augmented fewest-switches surface-hopping.

Conclusions:

  • The electronic coupled-trajectory term is essential for capturing decoherence and wavepacket branching accurately.
  • The nuclear coupled-trajectory term plays a less significant role in these nonadiabatic processes.
  • The analysis provides insights into the performance and components of mixed quantum-classical algorithms for chemical dynamics.