background: accurate small radiation field dosimetry is essential in modern radiotherapy techniques such as stereotactic radiosurgery (srs) and intensity modulated radiotherapy (imrt). precise measurement of dosimetric parameters such as beam profile, percentage depth doses and output factor of these beams are complicated due to the electron disequilibrium and the steep dose gradients. in the p...

Objective: The aim of the present study is to simulate 6 MV and 18 MV photon beam energies of a Siemens Primus Plus medical linear accelerator (Linac) and to verify the simulation by comparing the results with the measured data.Methods: The main components of the head of Siemens Primus Plus linac were simulated using MCNPX Monte Carlo (MC) code. To verify the results, experimental data of perce...

What happens when one sets up a computer simulation using Importance Sampling theory and then, during the simulation, knowingly or unknowingly, generates the simulation uncertainty (e.g. channel noise) with statistics other than those assumed in the simulation setup? By exploring this simple question, we nd some interesting aspects of Importance Sampling that provide insight into its properties...

A Monte Carlo (MC) technique is employed to investigate stationary electron transport in lead telluride (PbTe). Results for electron mobility as a function of lattice temperature, free carrier concentration, and electric field are compared with experimental data and the few available other Monte Carlo simulation results.

The reduction of the computational cost of statistical circuit analysis, such as Monte Carlo (MC) simulation, is a challenging problem. In this paper, we propose to build macromodels capable of reproducing the statistical behavior of all repeated MC simulations in a single simulation run. The parameter space is sampled similarly to the MC method and the resulting nonlinear models are reduced si...

In Monte Carlo (MC) simulations of semiconductor devices it is necessary to enhance the statistics in sparsely populated regions of interest. In this work the Monte Carlo method for stationary carrier transport, known as the Single-Particle MC method, is considered. It gives a solution to the stationary boundary value problem defined by the semi-classical Boltzmann equation (BE). Using a formal...

In this work, we present a new three-dimensional Monte Carlo (MC) method which naturally recovers the realspace carrier-impurity Coulomb interaction by mesh-based resolution of Poisson’s equation. This method necessitates no additional modifications to the conventional MC simulator, thus simplifying the implementation process. The new method has been validated through the reproduction of the do...

Monte Carlo (MC) sampling methods are widely applied in Bayesian inference, system simulation and optimization problems. The Markov Chain Monte Carlo (MCMC) algorithms are a well-known class of MC methods which generate a Markov chain with the desired invariant distribution. In this document, we focus on the Metropolis-Hastings (MH) sampler, which can be considered as the atom of the MCMC techn...

Nanostructures have considerably higher surface areas than their bulk counterparts; thereforesurfaces often play important, sometimes even dominant, roles in the nanostructure properties. Thenanocrystalline and nanotubes have low band gaps and high carrier mobility, thus offeringappealing potential as absorption gas. Interaction between methanol molecules and carbonnanotube is investigated usin...

Recent developments in modeling stream of variation in multistage manufacturing system along with the urgent need for yield enhancement in the semiconductor industry has led to complex large scale simulation problems in design and performance prediction, thus challenging current Monte Carlo (MC) based simulation techniques. MC method prevails in statistical simulation approaches for multi-dimen...