Quantum computing was so far mainly concerned with discrete problems. Recently, Novak and the author studied quantum algorithms for high dimensional integration and dealt with the question, what advantages quantum computing can bring over classical deterministic or randomized methods for this...

The stochastic method used to simulate the stationary transport in semiconductor devices is revised in terms of the numerical Monte Carlo theory. A mathematically based approach has been used to derive the basic simulation algorithms, previously devised from physical considerations. The approach...

We consider the convergency of the basic Monte Carlo (MC) algorithms for solving the Boltzmann transport equation (BTE). It is a linear kinetic equation describing a broad class of particle transport phenomena such as electron and neutron transport, radiative transfer, medium energy electron and...

We present applications of a new Monte Carlo algorithm for the calculation of excited state energies of multi-dimensional quantum systems. The method relies on computation of imaginary time correlation functions of appropriately chosen projection operators, followed by a numerical inverse...

In this paper, we consider Monte Carlo (MC) algorithms based on the use of the resolvent matrix for solving linear algebraic problems. Estimates for the speedup and efficiency of the algorithms are presented. Some numerical examples performed on cluster of workstations using MPI are given.

Digital (or mixed mode) circuit implementations of neural networks bring one major modification to their ideal, defectless models: quantization of the weights dynamics. Would this modification completely perturb the behavior of the network, it will never be possible to implement it on a digital...