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

Diffusion Monte Carlo method with lattice regularization.

Michele Casula1, Claudia Filippi, Sandro Sorella

  • 1International School for Advanced Studies (SISSA), Trieste, Italy.

Physical Review Letters
|October 4, 2005
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

QMCkl: A kernel library for quantum Monte Carlo applications.

The Journal of chemical physics·2026
Same author

Dual quantum locking: Dynamic coupling of H<sub>2</sub> and H<sub>2</sub>O sublattices in hydrogen-filled ice.

Proceedings of the National Academy of Sciences of the United States of America·2026
Same author

Structure and dynamics of sulfur vacancies in monolayer MoS2 studied by DFT-based machine learning potentials.

The Journal of chemical physics·2025
Same author

Monte Carlo methods, 70 years after "Equation of state calculations by fast computing machines" by Nicholas Metropolis, Arianna Rosenbluth, Marshall Rosenbluth, Augusta Teller, and Edward Teller (1953).

The Journal of chemical physics·2025
Same author

Load-balanced diffusion Monte Carlo method with lattice regularization.

The Journal of chemical physics·2025
Same author

Self-Consistency Error Correction for Accurate Machine Learning Potentials from Variational Monte Carlo.

Journal of chemical theory and computation·2025
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

We developed a new lattice regularization scheme for quantum Monte Carlo simulations. This method improves accuracy for electronic systems by efficiently handling different length scales and nonlocal potentials.

Area of Science:

  • Computational Physics
  • Quantum Chemistry
  • Materials Science

Background:

  • Accurate simulation of realistic electronic systems is crucial for understanding material properties.
  • Existing quantum Monte Carlo methods face challenges with computational efficiency and accuracy, particularly for systems with nonlocal potentials.

Purpose of the Study:

  • To introduce an efficient lattice regularization scheme for quantum Monte Carlo calculations.
  • To improve the accuracy and applicability of quantum Monte Carlo methods for realistic electronic systems.

Main Methods:

  • Discretization of the kinetic term using a finite difference Laplacian with two mesh sizes (a and a').
  • Development of a regularized Hamiltonian that approaches the continuous limit as mesh size approaches zero.

Related Experiment Videos

  • Inclusion of nonlocal potentials within a consistent variational scheme.

    • Main Results:

    • The proposed scheme allows electrons to diffuse in a configuration space practically indistinguishable from the continuum.
    • Efficient accounting for different length scales within the electronic system.
    • Substantial accuracy improvement compared to previous nonvariational approaches.

    Conclusions:

    • The novel lattice regularization scheme offers an efficient and accurate method for quantum Monte Carlo calculations.
    • This approach enhances the capability to simulate complex electronic systems, including those with nonlocal potentials.
    • The method provides a pathway to more reliable predictions in condensed matter physics and quantum chemistry.