Quantum Monte Carlo (QMC) methods such as Variational Monte Carlo, Diffusion Monte Carlo or Path Integral Monte Carlo are the most accurate and general methods for computing total electronic energies. We will review methods we have developed to perform QMC for the electrons coupled to another MC simulation for the ions. In this method, one estimates the Born-Oppenheimer energy E(Z) where Z repr...

Contemporary scientific studies often rely on the understanding of complex quantum systems via computer simulation. This paper initiates the statistical study of quantum simulation and proposes a Monte Carlo method for estimating analytically intractable quantities. We derive the bias and variance for the proposed Monte Carlo quantum simulation estimator and establish the asymptotic theory for ...

Monte Carlo sampling has become a major vehicle for approximate inference in Bayesian networks. In this paper, we investigate a fam­ ily of related simulation approaches, known collectively as quasi-Monte Carlo methods based on deterministic low-discrepancy se­ quences. We first outline several theoreti­ cal aspects of deterministic low-discrepancy sequences, show three examples of such se­ que...

The problem for simulation ultra-fast carrier transport in nano-electronics devices is a large scale computational problem and requires HPC and/or Grid computing resources. The most widely used techniques for modeling this carrier transport are Monte Carlo methods. In this work we consider a set of stochastic algorithms for solving quantum kinetic equations describing quantum effects during the...

Approximate Bayesian computation (ABC) is a popular approach to address inference problems where the likelihood function is intractable, or expensive to calculate. To improve over Markov chain Monte Carlo (MCMC) implementations of ABC, the use of sequential Monte Carlo (SMC) methods has recently been suggested. Effective SMC algorithms that are currently available for ABC have a computational c...

background: one of the main problems of dedicated iort accelerators is to determine dosimetric characteristics of the electron beams. monte carlo simulation of iort accelerator head and produced beam will be useful to improve the accuracy of beam dosimetry. materials and methods: liac accelerator head was modeled using the beamnrcmonte carlo simulation system. phase-space files were generated a...

deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. in this paper, generation reliability is considered, and a method for its assessment using intelligent systems is proposed. also, because of power market and generators’ forced outages stochastic behavior, monte carlo simulation is used for reliability evaluation. generation r...

in this paper, we examine the effect of the energy difference between the l- and the -valleys in compound semiconductor materials, carrier effective mass, and the scattering processes on the electron transport characteristics in mesfets. to do this, we use the monte carlo simulation to demonstrate the superiority of the ingaas mesfet, made on a semi-insulating inp substrate, over both inp and ...

this paper proposes a method for ranking decision making units (dmus) using some of the multiple criteria decision making / multiple attribute decision making          (mcdm /madm) techniques, namely, interval analytic hierarchy process (iahp)          and the technique for order preference by similarity to an ideal solution (topsis).          since the efficiency score of unity is assigned to ...

this paper aims to evaluate inventory cost of a two-echelon serial supply chain system under vendor managed inventory program with stochastic demand, and examine the effect of environmental factors on the cost of overall system. for this purpose, we consider a two-echelon serial supply chain with a manufacturer and a retailer. under vendor managed inventory program, the decision on inventory le...