We demonstrate that the quantum Monte Carlo (QMC) methodology (i) provides barrier heights and heats of formation within !0.05 eV of experimental values, (ii) confirms recent measurements for the ring inversion of cyclo-octatetraene, and (iii) enables us to predict quantities not yet measured. Density functional methods show a mixed performance in achieving the accuracy required for predictive ...

In the past few years the development of exascale computing technology necessitated to obtain an estimate for the energy consumption when large-scale problems are solved with different high-performance computing (HPC) systems. In this paper we study the energy efficiency of a class of Monte Carlo (MC) and Quasi-Monte Carlo (QMC) algorithms for a given integral equation using hybrid HPC systems....

The quasi-Monte Carlo (QMC) integration method can asymptotically provide a rate of convergence O(N−1), while the rate of convergence of the standard Monte Carlo (MC) method is only O(N−1/2). For a sufficiently large number of sampled points N, QMC should always outperform MC. However, for high dimensional problems such a large number of points can be infeasible. Many numerical experiments demo...

In Monte Carlo (MC) sampling the sample averages of random quantities are used to estimate the corresponding expectations. The justification is through the law of large numbers. In quasi-Monte Carlo (QMC) sampling we are able to get a law of large numbers with deterministic inputs instead of random ones. Naturally we seek deterministic inputs that make the answer converge as quickly as possible...

The electronic properties of paramagnetic V2O3 are investigated by the computational scheme LDA+DMFT(QMC). This approach merges the local density approximation (LDA) with dynamical mean-field theory (DMFT) and uses quantum Monte Carlo simulations (QMC) to solve the effective Anderson impurity model of DMFT. Starting with the crystal structure of metallic V2O3 and insulating (V0.962Cr0.038)2O3 w...

In a recent Letter [T. Dornheim et al., Phys. Rev. Lett. 117, 156403 (2016)PRLTAO0031-900710.1103/PhysRevLett.117.156403], we presented the first quantum Monte Carlo (QMC) results for the warm dense electron gas in the thermodynamic limit. However, a complete parametrization of the exchange-correlation free energy with respect to density, temperature, and spin polarization remained out of reach...

We obtain the phase diagram of spin-imbalanced interacting Fermi gases from measurements of density profiles of Li atoms in a harmonic trap. These results agree with, and extend, previous experimental measurements. Measurements of the critical polarization at which the balanced superfluid core vanishes generally agree with previous experimental results and with quantum Monte Carlo (QMC) calcula...

One of the core problems in materials science is how the interactions between electrons in a solid give rise to properties like ∗This work was partially supported by the National Science Foundation under Grant 0313390, and Department of Energy, Office of Science, SciDAC grant DEFC02 06ER25793. Wenbin Chen was also supported in part by the China Basic Research Program under the grant 2005CB32170...

In this paper, we consider an enhanced quasi-Monte Carlo (QMC) method for pricing derivative securities when the underlying asset price follows an exponential Lévy process. In particular, we focus on a special family of the Lévy process known as the Meixner process. The enhanced QMC is based on a generalization of the linear transformation (LT) method of Imai and Tan (2006). The generalized LT ...

With advances in algorithms and the changing landscape of high performance computers (HPC), the quantum Monte Carlo method has become a leading contender for high accuracy calculations for the electronic structure of realistic systems. QMC, being statistical, is naturally scalable to a large number of processors. We discuss QMC implementations to overcome the important efficiency and scalabilit...