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News

  • K. Nakano, et al. have published a paper titled ‘Beyond Single-Reference Fixed-Node Approximation in Ab Initio Diffusion Monte Carlo Using Antisymmetrized Geminal Power Applied to Systems with Hundreds of Electrons’ in J. Chem. Theory Comput. in press (2024).
  • K. Nakano et al. have published a paper titled ‘Efficient calculation of unbiased atomic forces in ab initio variational Monte Carlo’ in Phys. Rev. B 109, 205151 (2024).
  • R. Taureau et al. have published a paper titled ‘Quantum symmetrization transition in superconducting sulfur hydride from quantum Monte Carlo and path integral molecular dynamics’ in Npj Comput. Mater. 10, 56 (2024).
  • K. Nakano et al. have published a paper titled ‘TurboGenius: Python suite for high-throughput calculations of ab initio quantum Monte Carlo methods’ in J. Chem. Phys. 159, 224801 (2023).
  • TurboRVB is now an open-source project! ver.1.0.0 !!
  • A. Raghav et al. have published a paper titled ‘Toward Chemical Accuracy Using the Jastrow Correlated Antisymmetrized Geminal Power Ansatz’ in J. Chem. Theory Comput. 19, 2222-2229 (2023).
  • L. Monacelli et al. have published a paper titled ‘Quantum phase diagram of high-pressure hydrogen’ in Nat. Phys. 19, 845–850 (2023).
  • A. Tirelli et al. have published a paper titled ‘High pressure hydrogen by machine learning and quantum Monte Carlo’ in Phys. Rev. B, 106, L041105 (2022).
  • K. Nakano et al. have published a paper titled ‘Space-warp coordinate transformation for efficient ionic force calculations in quantum Monte Carlo’ in J. Chem. Phys. 156, 034101 (2022).
  • K. Nakano et al. have published a paper titled ‘Atomic forces by quantum Monte Carlo: Application to phonon dispersion calculations’ in Phys. Rev. B 103, L121110 (2021).
    This paper has been selected as an Editors’ Suggestion.

Features

TurboRVB is a computational package for ab initio Quantum Monte Carlo (QMC) simulations of both molecular and bulk electronic systems. The code was initially launched by Prof. Sandro Sorella and Prof. Michele Casula and has been continuously developed by many contributors for over 20 years. The code implements two types of well established QMC algorithms: Variational Monte Carlo (VMC), and Diffusion Monte Carlo in its robust and efficient lattice regularized variant (LRDMC).

The source codes of TurboRVB and other associated packages are available from Source codes.

TurboRVB is distinguishable from other QMC codes in the following features:

  • The code employs a resonating valence bond (RVB)-type wave function, such as the Jastrow Geminal/Jastrow Pfaffian. This wave function includes the correlation effect beyond the Jastrow-Slater wave function, which is commonly used in other QMC codes.

  • Implemented state-of-art optimization algorithms, such as the stochastic reconfiguration and the linear method, realize a stable optimization of the amplitude and nodal surface of many-body wave functions at the variational quantum Monte Carlo level.

  • The code implements the so-called lattice regularized diffusion Monte Carlo method, which provides a numerically stable diffusion quantum Monte Carlo calculation.

  • The implementation of an adjoint algorithmic differentiation allows us to differentiate many-body wave functions efficiently and to perform structural optimizations and calculate molecular dynamics.

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