TurboRVB in a nutshellΒΆ

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).

TurboRVB sets itself apart from other QMC codes through several unique features:

  • The program utilizes a resonating valence bond (RVB)-type wave function, such as the Jastrow Geminal/Jastrow Pfaffian. This wave function offers the ability to capture correlation effects extending beyond the scope of the commonly employed Jastrow-Slater wave function seen in other QMC codes.

  • Incorporating cutting-edge optimization algorithms, like stochastic reconfiguration and the linear method, TurboRVB ensures 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 assures a numerically stable diffusion quantum Monte Carlo calculation.

  • The integration of an adjoint algorithmic differentiation offers us the capability to efficiently differentiate many-body wave functions, facilitating structural optimizations and the calculation of molecular dynamics.

  • TurboGenius and TurboWorkflows allow us to realize high-throughput QMC calculations based on TurboRVB. Both TurboWorkflows and TurboGenius are implemented by Python 3 in the object-oriented fashion; thus, they are readily extended.

When you publish a paper using TurboRVB, please cite the following paper(s).