We analyze the performance of quantum annealing as a heuristic optimization method to find the absolute minimum of various continuous models, including landscapes with only two wells and also models with many competing minima and with disorder. The simulations performed using a projective quantum Monte Carlo (QMC) algorithm are compared with those based on the finite-temperature path-integral Q...

Atomic forces are calculated for first-row monohydrides and carbon monoxide within electronic quantum Monte Carlo (QMC). Accurate and efficient forces are achieved by using an improved method for moving variational parameters in variational QMC. Newton's method with singular value decomposition (SVD) is combined with steepest-descent (SD) updates along directions rejected by the SVD, after init...

Quantum Monte Carlo (QMC) methods such as variational Monte Carlo and fixed node diffusion Monte Carlo depend heavily on the quality of the trial wave function. Although Slater-Jastrow wave functions are the most commonly used variational ansatz in electronic structure, more sophisticated wave functions are critical to ascertaining new physics. One such wave function is the multi-Slater-Jastrow...

We present the first quantum Monte Carlo (QMC) calculations with chiral effective field theory (EFT) interactions. To achieve this, we remove all sources of nonlocality, which hamper the inclusion in QMC calculations, in nuclear forces to next-to-next-to-leading order. We perform auxiliary-field diffusion Monte Carlo (AFDMC) calculations for the neutron matter energy up to saturation density ba...

We are currently exploring the use of reconfigurable computing using Field Programmable Gate Arrays (FPGAs) to accelerate kernels of scientific applications. Here, we present a hardware architecture targeted towards the acceleration of two scientific kernels in a Quantum Monte Carlo (QMC) application applied to N-body systems. Quantum Monte Carlo methods enable us to determine the ground-state ...

The quantum Monte Carlo (QMC), CASINO code was run to calculate the ground state energy for the hydrogen molecule. The variational Monte Carlo (VMC) technique was used, employing the unrestricted Hartree-Fock (UHF) method, instead of the restricted Hartree-Fock (RHF) method. By altering the VMC steps in the input parameters of the CASINO code, the best ground state energy for the hydrogen molec...

We present a technique for using quantum Monte Carlo (QMC) to obtain high quality energy differences. We use generalized valence bond (GVB) wave functions, for an intuitive approach to capturing the important sources of static correlation, without needing to optimize the orbitals with QMC. Using our modifications to Walker branching and Jastrows, we can then reliably use diffusion quantum Monte...

Submitted for the MAR05 Meeting of The American Physical Society QMC with a Stochastic Poisson Solver: An application to realistic models of quantum dots DYUTIMAN DAS, JEONGNIM KIM, RICHARD MARTIN, L. ZHANG COLLABORATION, JP LEBURTON COLLABORATION, D. MELNIKOV COLLABORATION — Quantum Monte Carlo can be used to study interacting electrons in semiconductor quantum structures. We introduce a new a...

We generalize the imaginary-chemical-potential quantum Monte Carlo (QMC) method proposed by Dagotto [Phys. Rev. B 41, R811 (1990)] to systems without particle-hole symmetry. The generalized method is tested by comparing the results of the QMC simulations and exact diagonalization on small Hubbard molecules, such as tetrahedron and truncated tetrahedron. Results of the application of the method ...

A new algorithm is presented for the sparse representation and evaluation of Slater determinants in the quantum Monte Carlo (QMC) method. The approach, combined with the use of localized orbitals in a Slater-type orbital basis set, significantly extends the size molecule that can be treated with the QMC method. Application of the algorithm to systems containing up to 390 electrons confirms that...