Sequential Monte Carlo (SMC) samplers are an alternative to MCMC for Bayesian computation. However, their performance depends strongly on the Markov kernels used rejuvenate particles. We discuss how calibrate automatically (using current particles) Hamiltonian within SMC. To do so, we build upon adaptive SMC approach of Fearnhead and Taylor (2013), also suggest methods. illustrate advantages us...

Kinetic Monte Carlo simulation was applied to investigation of kinetics and mechanism of oxalic acid degradation by direct and heterogeneous catalytic ozonation. La-containing perovskites including LaFeO3, LaNiO3, LaCoO3 and LaMnO3 was studied as catalyst for oxalic acid ozonation. The reaction kinetic mechanisms of each abovementioned catalytic systems has been achieved. The rate constants val...

The determination of gyration radius is a strong research for configuration of a Macromolecule. Italso reflects molecular compactness shape. In this work, to characterize the behavior of theprotein, we observe quantities such as the radius of gyration and the average energy. We studiedthe changes of these factors as a function of temperature for Acetylcholine receptor protein in gasphase with n...

introduction: in recent decades, several monte carlo codes have been introduced for research and medical applications. these methods provide both accurate and detailed calculation of particle transport from linear accelerators. the main drawback of monte carlo techniques is the extremely long computing time that is required in order to obtain a dose distribution with good statistical accuracy. ...

medical linear accelerators are one of the most widespread methods for cancer treatment. despite their advantages, unwanted photoneutrons are produced by high energy linacs. this photoneutrons are as undesired doses to patients and a significant problem for radiation protection of the staffs and patients. photoneutrons radiological risk must be evaluated because of their high let and range.in o...

Monte Carlo is one of the most versatile and widely used numerical methods. Its convergence rate, O(N~^), is independent of dimension, which shows Monte Carlo to be very robust but also slow. This article presents an introduction to Monte Carlo methods for integration problems, including convergence theory, sampling methods and variance reduction techniques. Accelerated convergence for Monte Ca...