We propose improved versions of the standard diffusion Monte Carlo (DMC) and the lattice regularized diffusion Monte Carlo (LRDMC) algorithms. For the DMC method, we refine a scheme recently devised to treat nonlocal pseudopotential in a variational way. We show that such scheme—when applied to large enough systems—maintains its effectiveness only at correspondingly small enough time-steps, and we present two simple upgrades of the method which guarantee the variational property in a size-consistent manner. For the LRDMC method, which is size-consistent and variational by construction, we enhance the computational efficiency by introducing: (i) an improved definition of the effective lattice Hamiltonian which remains size-consistent and ent...
diffusion-influenced reactions attract increasing attention. It is well-known that diffusion-influen...
summary:Many low-discrepancy sets are suitable for quasi-Monte Carlo integration. Skriganov showed t...
This paper investigates the behaviour of the random walk Metropolis algorithm in high-dimensional pr...
We propose improved versions of the standard diffusion Monte Carlo (DMC) and the lattice regular...
We propose improved versions of the standard diffusion Monte Carlo (DMC) and the lattice regular...
We introduce an efficient lattice regularization scheme for quantum Monte Carlo calculations of real...
We introduce an efficient lattice regularization scheme for quantum Monte Carlo calculations of real...
We review the basic outline of the highly successful diffusion Monte Carlo technique com-monly used ...
International audienceWe are interested in Monte Carlo (MC) methods for solving the diffusion equati...
One of the most significant drawbacks of the all-electron ab initio diffusion Monte Carlo (DMC) is t...
AbstractRecently we have developed a Monte Carlo algorithm for lattice spin systems that relies excl...
We investigate the portability of standard norm-conserving pseudopotentials outside the density func...
In this paper we analyze the numerical approximation of diffusion problems over polyhedral domains i...
International audienceWe are interested in Monte Carlo (MC) methods for solving the diffusion equati...
I first discuss the current theory of getting dimension independent convergence in approximating hig...
diffusion-influenced reactions attract increasing attention. It is well-known that diffusion-influen...
summary:Many low-discrepancy sets are suitable for quasi-Monte Carlo integration. Skriganov showed t...
This paper investigates the behaviour of the random walk Metropolis algorithm in high-dimensional pr...
We propose improved versions of the standard diffusion Monte Carlo (DMC) and the lattice regular...
We propose improved versions of the standard diffusion Monte Carlo (DMC) and the lattice regular...
We introduce an efficient lattice regularization scheme for quantum Monte Carlo calculations of real...
We introduce an efficient lattice regularization scheme for quantum Monte Carlo calculations of real...
We review the basic outline of the highly successful diffusion Monte Carlo technique com-monly used ...
International audienceWe are interested in Monte Carlo (MC) methods for solving the diffusion equati...
One of the most significant drawbacks of the all-electron ab initio diffusion Monte Carlo (DMC) is t...
AbstractRecently we have developed a Monte Carlo algorithm for lattice spin systems that relies excl...
We investigate the portability of standard norm-conserving pseudopotentials outside the density func...
In this paper we analyze the numerical approximation of diffusion problems over polyhedral domains i...
International audienceWe are interested in Monte Carlo (MC) methods for solving the diffusion equati...
I first discuss the current theory of getting dimension independent convergence in approximating hig...
diffusion-influenced reactions attract increasing attention. It is well-known that diffusion-influen...
summary:Many low-discrepancy sets are suitable for quasi-Monte Carlo integration. Skriganov showed t...
This paper investigates the behaviour of the random walk Metropolis algorithm in high-dimensional pr...