We present an advanced algorithm for an extraction tool that computes inductances of interconnect structures. As already pointed out in [I] the pursued energy concept leads to a 6-fold integral which can also be evaluated by use of the Monte Carlo method. Classical implementation of the Monte Carlo method, where the whole geometry has to be hunted for the associated element loses efficiency. Ou...

Monte Carlo particle transport is often introduced primarily as a method to solve linear integral equations such as the Boltzmann transport equation. This paper discusses some common misconceptions about Monte Carlo methods that are often associated with an equation-based focus. Many of the misconceptions apply directly to standard Monte Carlo codes such as MCNP and some are worth noting so tha...

The study of dual-modality technology which combines microcomputed tomography (micro-CT) and fluorescence molecular tomography (FMT) has become one of the main focuses in FMT. However, because of the diversity of the optical properties and irregular geometry for small animals, a reconstruction method that can effectively utilize the high-resolution structural information of micro-CT for tissue ...

The properties of hydrogen-helium mixtures at high pressure are crucial to address important questions about the interior of Giant planets e.g. whether Jupiter has a rocky core and did it emerge via core accretion? Using path integral Monte Carlo simulations, we study the properties of these mixtures as a function of temperature, density and composition. The equation of state is calculated and ...

As opposed to Monte Carlo integration the quasi-Monte Carlo method does not allow for an error estimate from the samples used for the integral approximation and the deterministic error bound is not accessible in the setting of computer graphics, since usually the integrands are of unbounded variation. We investigate the application of randomized quasi-Monte Carlo integration to bidirectional pa...

Abstract A simple algorithm is described to sample permutations of identical particles in Path Integral Monte Carlo (PIMC) simulations of continuum many-body systems. The sampling strategy illustrated here is fairly general, and can be easily incorporated in any PIMC implementation based on the staging algorithm. Although it is similar in spirit to an existing prescription, it differs from it i...

Monte Carlo (MC) techniques are often used to estimate integrals of a multivariate function using randomly generated samples of the function. In light of the increasing interest in uncertainty quantification and robust design applications in aerospace engineering, the calculation of expected values of such functions (e.g. performance measures) becomes important. However, MC techniques often su ...

In inverse problems like tomography reconstruction we need to solve an over-determined linear system corrupted with noise. The MLEM algorithm finds the solution for Poisson noise as the fixed point of iterating a forward projection and a non-linear back projection. In tomography we have several hundred million equations and unknowns. The elements of the huge matrix are high-dimensional integral...

In this paper, we establish a deterministic error bound for estimating a functional of the solution of the integral transport equation via random walks that improves an earlier result of Chelson generalizing the Koksma-Hlawka inequality for nite dimensional quadrature. We solve such problems by simulation, using sequences that combine pseudorandom and quasirandom elements in the construction of...