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 Experiment Videos

An efficient sampling algorithm for variational Monte Carlo.

Anthony Scemama1, Tony Lelièvre, Gabriel Stoltz

  • 1CERMICS and INRIA Project Micmac, Ecole Nationale des Ponts et Chaussées, 6 et 8 Avenue Blaise Pascal, Cité Descartes-Champs sur Marne, 77455 Marne la Vallée Cedex 2, France. scemam@cermics.enpc.fr

The Journal of Chemical Physics
|September 27, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

A Mathematical Analysis of IPT-DMFT.

Communications in mathematical physics·2026
Same author

Efficient Monte Carlo sampling of metastable systems using nonlocal collective variable updates.

The Journal of chemical physics·2026
Same author

QMCkl: A kernel library for quantum Monte Carlo applications.

The Journal of chemical physics·2026
Same author

Electron-Induced Fragmentation Dynamics of 1-Methylpyrene (C<sub>17</sub>H<sub>12</sub>) Dications and Trications: C<sub>2</sub>H<sub><i>x</i></sub><sup><i>q</i>+</sup> Release Pathways.

The journal of physical chemistry. A·2026
Same author

Critical point search and linear response theory for computing electronic excitation energies of molecular systems. I. General framework, application to Hartree-Fock and DFT.

The Journal of chemical physics·2026
Same author

Reproducibility of fixed-node diffusion Monte Carlo across diverse community codes: The case of water-methane dimer.

The Journal of chemical physics·2025
Same journal

Quantum simulation of alignment dependent differential cross sections in co-propagating molecular beams at cold collision energies.

The Journal of chemical physics·2026
Same journal

Non-additive ion effects on the coil-globule equilibrium of a generic polymer in aqueous salt solutions.

The Journal of chemical physics·2026
Same journal

Insights into the unexpected small reduction of the temperature of maximum density of water by lithium chloride addition.

The Journal of chemical physics·2026
Same journal

Optical frequency comb double-resonance spectroscopy of the 9030-9175 cm-1 states of ethylene.

The Journal of chemical physics·2026
Same journal

Time reversal breaking of colloidal particles in cells.

The Journal of chemical physics·2026
Same journal

Photodynamics of amino acids under UV excitation: Extraterrestrial amino acids.

The Journal of chemical physics·2026
See all related articles

We developed a new variational Monte Carlo algorithm for improved N-body density sampling. This method enhances accuracy over standard biased random walk techniques for atomic and molecular simulations.

Area of Science:

  • Computational Physics
  • Quantum Chemistry
  • Statistical Mechanics

Background:

  • Variational Monte Carlo (VMC) is a key quantum mechanical method.
  • Efficient sampling of the N-body probability density is crucial for VMC accuracy.
  • Existing sampling methods, like importance sampling, can be inefficient.

Purpose of the Study:

  • To introduce a novel algorithm for sampling the N-body density in VMC.
  • To enhance the efficiency and accuracy of quantum system simulations.
  • To provide a superior alternative to standard sampling techniques.

Main Methods:

  • A modified Ricci-Ciccotti discretization of Langevin dynamics in phase space (R,P).
  • Integration of a Metropolis-Hastings accept/reject step for improved sampling.

Related Experiment Videos

  • Application to representative systems: lithium, fluorine, copper atoms, and phenol molecule.

    • Main Results:

    • The proposed algorithm demonstrates superior performance compared to the standard biased random walk (importance sampling).
    • Numerical examples show significant improvements in sampling efficiency and accuracy.
    • The method is effective for both atomic and molecular systems.

    Conclusions:

    • The new algorithm offers a more efficient and accurate approach to N-body density sampling in VMC.
    • This advancement has implications for high-precision quantum mechanical calculations.
    • The method is validated by successful application to diverse chemical systems.