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Related papers: AlfaMC: a fast alpha particle transport Monte Carl…

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A Monte Carlo code, known as AASI, is developed for simulating energy spectra in alpha spectrometry. The code documented here is a comprehensive package where all the major processes affecting the spectrum are included. A unique feature of…

Nuclear Experiment · Physics 2009-11-11 T. Siiskonen , R. Pollanen

We present the Monte Carlo with Absorbing Markov Chains (MCAMC) method for extremely long kinetic Monte Carlo simulations. The MCAMC algorithm does not modify the system dynamics. It is extremely useful for models with discrete state spaces…

Materials Science · Physics 2007-05-23 M. A. Novotny , Shannon M. Wheeler

We describe CPMC-Lab, a Matlab program for the constrained-path and phaseless auxiliary-field Monte Carlo methods. These methods have allowed applications ranging from the study of strongly correlated models, such as the Hubbard model, to…

Strongly Correlated Electrons · Physics 2014-10-14 Huy Nguyen , Hao Shi , Jie Xu , Shiwei Zhang

The simulation of diffusion-based molecular communication systems with absorbing receivers often requires a high computational complexity to produce accurate results. In this work, a new a priori Monte Carlo (APMC) algorithm is proposed to…

Emerging Technologies · Computer Science 2018-03-14 Yiran Wang , Adam Noel , Nan Yang

We use an auxiliary-field Monte Carlo (AFMC) method to calculate thermodynamic properties (spin susceptibility and heat capacity) of ultra-small metallic grains in the presence of pairing correlations. This method allows us to study the…

Mesoscale and Nanoscale Physics · Physics 2007-05-23 Y. Alhassid , L. Fang , S. Schmidt

The basic idea of fast Monte Carlo (MC) simulations is to perform particle-based MC simulations with the excluded-volume interactions modeled by "soft" repulsive potentials that allow particle overlapping. This gives much faster system…

Soft Condensed Matter · Physics 2012-01-24 Qiang Wang

Accurately and efficiently estimating system performance under uncertainty is paramount in power system planning and operation. Monte Carlo simulation is often used for this purpose, but convergence may be slow, especially when detailed…

Computation · Statistics 2020-10-23 Simon Tindemans , Goran Strbac

A simple Monte Carlo (MC) algorithm for the simulation of the passage of low-energy gamma rays and electrons through any material medium is presented. The algorithm includes several approximations that accelerate the simulation while…

Accelerator Physics · Physics 2023-10-25 Víctor Moya , Jaime Rosado , Fernando Arqueros

A novel a priori Monte Carlo (APMC) algorithm is proposed to accurately simulate the molecules absorbed at spherical receiver(s) with low computational complexity in diffusion-based molecular communication (MC) systems. It is demonstrated…

Emerging Technologies · Computer Science 2018-12-18 Yiran Wang , Adam Noel , Nan Yang

Monte Carlo (MC) simulations of lattice models are a widely used way to compute thermodynamic properties of substitutional alloys. A limitation to their more widespread use is the difficulty of driving a MC simulation in order to obtain the…

Statistical Mechanics · Physics 2009-11-07 A. van de Walle , M. Asta

Monte Carlo (MC) method has been recognized the most accurate dose calculation method for radiotherapy. However, its extremely long computation time impedes clinical applications. Recently, a lot of efforts have been made to realize fast MC…

Medical Physics · Physics 2017-02-08 Zhen Tian , Feng Shi , Michael Folkerts , Nan Qin , Steve B. Jiang , Xun Jia

The MeMC is an open-source software package for monte-carlo simulation of elastic shells. It is designed as a tool to interpret the force-distance data generated by indentation of biological nano-vesicles by atomic force microscopes. The…

Computational Physics · Physics 2022-06-28 Vipin Agrawal , Vikash Pandey , Hanna Kylhammar , Apurba Dev , Dhrubaditya Mitra

Hamiltonian Monte Carlo (HMC) is a popular Markov chain Monte Carlo (MCMC) algorithm that generates proposals for a Metropolis-Hastings algorithm by simulating the dynamics of a Hamiltonian system. However, HMC is sensitive to large time…

Machine Learning · Statistics 2016-09-15 Xiaoyu Lu , Valerio Perrone , Leonard Hasenclever , Yee Whye Teh , Sebastian J. Vollmer

Monte Carlo statistical ray-tracing methods are commonly employed to simulate carrier transport in nanostructured materials. In the case of a large degree of nanostructuring and under linear response (small driving fields), these…

Mesoscale and Nanoscale Physics · Physics 2023-02-09 Pankaj Priyadarshi , Neophytos Neophytou

Monte Carlo particle transport codes are well established on classical hardware and are considered as the reference tool for nuclear applications. In a growing number of domains, the design of algorithms is progressively shifting towards…

Quantum Physics · Physics 2024-10-28 Noé Olivier , Michel Nowak

The auxiliary-field quantum Monte Carlo (AFMC) method is a powerful and widely used technique for ground-state and finite-temperature simulations of quantum many-body systems. We introduce several algorithmic improvements for…

Computational Physics · Physics 2021-03-18 C. N. Gilbreth , S. Jensen , Y. Alhassid

We present a novel implementation of a Monte Carlo particle-following code for solving the distribution function of minority species in fusion plasmas, called ASCOT5, and verify it using theoretical results for neoclassical transport. The…

We discuss the current development of MC/DC (Monte Carlo Dynamic Code). MC/DC is primarily designed to serve as an exploratory Python-based MC transport code. However, it seeks to offer improved performance, massive scalability, and backend…

Computational Physics · Physics 2023-05-15 Ilham Variansyah , J. P. Morgan , Jordan Northrop , Kyle E. Niemeyer , Ryan G. McClarren

We study the multi-dimensional radiative transfer phenomena using the ISMC scheme, in both gray and multi-frequency problems. Implicit Monte-Carlo (IMC) schemes have been in use for five decades. The basic algorithm yields teleportation…

Computational Physics · Physics 2022-01-06 Elad Steinberg , Shay I. Heizler
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