相关论文: McStas (i): Introduction, use, and basic principle…

Since the middle of the 1940's scientists have used Monte Carlo (MC) simulations to obtain information about physical processes. This has proved a accurate and and reliable method to obtain this information. Through out resent years…

Neutron imaging has gained significant importance as a material characterisation technique and is particularly useful to visualise hydrogenous materials in objects opaque to other radiations. Particular fields of application include…

Computational tools for normal mode analysis, which are widely used in physics and materials science problems, are designed here in a single package called NMscatt (Normal Modes & scattering) that allows arbitrarily large systems to be…

This paper gives an overview of the particle transport theory essentials, the basics of particle-material interaction simulation, physical quantities needed to simulate particle transport and interactions in materials, Monte Carlo…

Background induced by neutrons in deep underground laboratories is a critical issue for all experiments looking for rare events, such as dark matter interactions or neutrinoless 2-beta decay. Neutrons can be produced either by natural…

We propose a novel approach to intranuclear cascades which takes as input quantum MonteCarlo nuclear configurations and uses a semi-classical, impact-parameter based algorithm to modelthe propagation of protons and neutrons in the nuclear…

This book is divided into two parts. In the first part we give an elementary introduction to computational physics consisting of 21 simulations which originated from a formal course of lectures and laboratory simulations delivered since…

This paper examines the use of Monte Carlo simulations to understand statistical concepts in A/B testing and Randomized Controlled Trials (RCTs). We discuss the applicability of simulations in understanding false positive rates and estimate…

Theoretical predictions in high energy physics are routinely provided in the form of Monte Carlo generators. Comparisons of predictions from different programs and/or different initialization set-ups are often necessary. MC-TESTER can be…

Performance assessment is a key issue in the process of proposing new machine learning/statistical estimators. A possible method to complete such task is by using simulation studies, which can be defined as the procedure of estimating and…

A simple Monte Carlo procedure is described for simulating the multiple scattering and absorption of electrons with the incident energy in the range 1-50 keV moving through a slab of uniformly distributed material of given atomic number,…

Numerical relativity simulations are essential to study the last stages of the binary neutron star coalescence. Unfortunately, for stable simulations there is the need to add an artificial low-density atmosphere. Here we discuss a new…

We have developed MGGPOD, a user-friendly suite of Monte Carlo codes built around the widely used GEANT (Version 3.21) package. The MGGPOD Monte Carlo suite and documentation are publicly available for download. MGGPOD is an ideal tool for…

We derive a Markov Chain Monte Carlo sampler based on following ray paths in a medium where the refractive index $n(x)$ is a function of the desired likelihood $\mathcal{L}(x)$. The sampling method propagates rays at constant speed through…

We announce the forthcoming public release of Version 1.1 of MGGPOD, a user-friendly suite of Monte Carlo codes built around the widely used GEANT (Version 3.21) package. MGGPOD is capable of simulating ab initio the physical processes…

These lecture notes are intended to cover some introductory topics in stochastic simulation for scientific computing courses offered by the IT department at Uppsala University, as taught by the author. Basic concepts in probability theory…

Accretion physics studies the process of gravitational capture of ambient matter by massive stars. The background processes are very challenging to observe and measure due to the extreme conditions in these systems. Numerical simulations…

$clustertools$ is a Python package for analyzing star cluster simulations. The package is built around the $StarCluster$ class, which stores all data read in from the snapshot of a given model star cluster. The package contains functions…

This perspective paper deals with an overview of particle-in-cell / Monte Carlo collision models applied to different plasma-propulsion configurations and scenarios, from electrostatic (E x B and pulsed arc) devices to electromagnetic (RF…

Monte-Carlo simulation of physical processes is an important tool for detector development as it allows to predict signal pulse amplitude and timing, time resolution, efficiency ... Yet despite the fact they are very common, full…