GitHub topics: monte-carlo-simulations
cdslaborg/paramonte
ParaMonte: Parallel Monte Carlo and Machine Learning Library for Python, MATLAB, Fortran, C++, C.
Language: Fortran - Size: 56.5 MB - Last synced at: 3 days ago - Pushed at: 5 months ago - Stars: 290 - Forks: 35
space-group-research/mpmc
A Monte Carlo molecular simulation software especially suited for materials simulations with polarizable models
Language: C - Size: 13 MB - Last synced at: 4 days ago - Pushed at: 6 months ago - Stars: 50 - Forks: 14
khavernathy/mcmd
Monte Carlo and Molecular Dynamics Simulation Package
Language: C++ - Size: 20.5 MB - Last synced at: 4 days ago - Pushed at: 10 months ago - Stars: 86 - Forks: 19
chicago-joe/Option-Pricing-via-Levy-Models-in-R
using the Inverse-Transform method to speed up options pricing simulations in R
Language: R - Size: 28.2 MB - Last synced at: about 21 hours ago - Pushed at: over 5 years ago - Stars: 28 - Forks: 11
Luigi-Ranno/LongLab_MMC
Repository for the code written for the MMC LongLab
Language: Python - Size: 5.14 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 1 - Forks: 1
rajeshrinet/compPhy
Assortment of code for model systems in computational physics. github.com/rajeshrinet/compPhy
Language: Jupyter Notebook - Size: 78.3 MB - Last synced at: about 1 month ago - Pushed at: over 2 years ago - Stars: 75 - Forks: 44
R-Lum/RLumCarlo
RLumCarlo - Modelling luminescence using Monte Carlo methods
Language: R - Size: 141 MB - Last synced at: about 1 month ago - Pushed at: 10 months ago - Stars: 3 - Forks: 0
barryyangtao/RNC
A Simple Algorithm for Converting Random Number Generator Outputs to Universal Distributions to Aid Teaching and Research in Modern Physical Chemistry
Language: MATLAB - Size: 404 KB - Last synced at: 11 months ago - Pushed at: 11 months ago - Stars: 0 - Forks: 0
amajji/Monte-Carlo
Monte Carlo overview and their applications
Language: Jupyter Notebook - Size: 701 KB - Last synced at: about 1 month ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 1
GunnerLab/MCCE_Benchmarking
For benchmarking MCCE experiments viz experimental pKas or viz other MCCE experiments (A/B testing)
Language: Smarty - Size: 43.2 MB - Last synced at: 12 months ago - Pushed at: 12 months ago - Stars: 0 - Forks: 0
SunilAnandatheertha/PXO
PXO (Poly-XTAL Operations). Generate, analyze and export complex 2D space partitions like metallic grain structures
Language: MATLAB - Size: 58.8 MB - Last synced at: 3 days ago - Pushed at: almost 4 years ago - Stars: 11 - Forks: 3
ORNL-CEES/Profugus
A set of radiation transport mini-applications used for performance optimization on HPC systems.
Language: C++ - Size: 6.06 MB - Last synced at: about 1 year ago - Pushed at: almost 7 years ago - Stars: 27 - Forks: 4
pjasmin1046/Thermodynamic-Simulations
Series of simulations analyzing common chemical engineering, thermodynamic, and kinetic phenomena
Language: Python - Size: 32.2 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
spiemonte/LeonardYM
Monte-Carlo simulations of four-dimensional Yang-Mills theories coupled to scalar and fermion fields
Language: C++ - Size: 1.02 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 7 - Forks: 3
vukics/cppqed
C++QED: a framework for simulating open quantum dynamics
Language: C++ - Size: 12.1 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 7 - Forks: 1
rsadykhov/stochastic-models
Python code of commonly used stochastic models for Monte-Carlo simulations
Language: Python - Size: 16.6 KB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 19 - Forks: 9
mieskolainen/graniitti
Monte Carlo Event Generator for High Energy Diffraction [arXiv:1910.06300] [arXiv:2304.06010]
Language: C++ - Size: 165 MB - Last synced at: about 1 year ago - Pushed at: almost 2 years ago - Stars: 3 - Forks: 2
ibarrond/DataSciencePortfolio
Data Science portfolio of ipython Notebooks with several Machine Learning algorithms. They follow a structured data science methodology to face various challenges
Language: Jupyter Notebook - Size: 11.2 MB - Last synced at: over 1 year ago - Pushed at: over 6 years ago - Stars: 6 - Forks: 3
sachu92/hard-sphere-mc
Hard sphere monte carlo simulations in C++
Language: C++ - Size: 7.81 KB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 0
wfjvdham/monte_carlo_simulations
Monte Carlo simulations in R
Language: R - Size: 17.6 KB - Last synced at: almost 2 years ago - Pushed at: over 6 years ago - Stars: 0 - Forks: 0
djape24394/gmphd_filter
The Gaussian Mixture Probability Hypothesis Density filter, GMPHD python implementation
Language: Python - Size: 6.23 MB - Last synced at: almost 2 years ago - Pushed at: almost 3 years ago - Stars: 13 - Forks: 5
lkeegan/longLCG
Pseudo-random number Linear Congruential Generator (LCG) with arbitrarily long integer arithmetic
Language: C++ - Size: 90.8 KB - Last synced at: about 2 months ago - Pushed at: over 7 years ago - Stars: 0 - Forks: 0
shivanshsinghal107/Investment-Portfolio
A student Investment portfolio web app built with various optimization techniques and screening parameters from core finance
Language: HTML - Size: 21.5 MB - Last synced at: about 2 years ago - Pushed at: almost 3 years ago - Stars: 10 - Forks: 5
owl-suite/OWL
Open-source/Oak-Ridge Wang-Landau (OWL): A suite for first-principles based Monte Carlo simulations
Language: C++ - Size: 1.32 MB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 12 - Forks: 8
patrickneugebauer/birthday-paradox
Monte Carlo Simulations in different languages
Language: TypeScript - Size: 217 KB - Last synced at: almost 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 2
shammill/Approximation-of-Pi
This was a first year University project I completed in 2013. It uses a Monte Carlo method to find an approximation to Pi. See Buffon's needle problem for related reading. Written in Python, and uses Turtle.
Language: Python - Size: 1.95 KB - Last synced at: about 2 years ago - Pushed at: about 7 years ago - Stars: 1 - Forks: 0
DavidCico/Study-of-a-buy-and-hold-investment
In this repository, a buy-and-hold investment is studied using Python and a Monte Carlo approach.
Language: Python - Size: 4.88 MB - Last synced at: about 2 years ago - Pushed at: about 6 years ago - Stars: 2 - Forks: 2
AShar97/Monte-Carlo-Simulation
Monte Carlo Simulation Course Assignments
Language: TeX - Size: 95.8 MB - Last synced at: 3 months ago - Pushed at: about 7 years ago - Stars: 1 - Forks: 0
marialymperaiou/The-ATLAS-experiment-at-CERN.-Diploma-Thesis-NTUA-
ATLAS is one of two general-purpose detectors at the Large Hadron Collider (LHC) at CERN. It investigates a wide range of physics, from the search for the Higgs boson to extra dimensions and particles that could make up dark matter. The ATLAS detector consists of a series of ever-larger concentric cylinders around the interaction point where the proton beams from the LHC collide. It can be divided into four major sections: Τhe Inner Detector, the innermost component, tracks the motion of charged particles as they move away from the interaction point. The tracks measured by recording particle/detector interactions at a multitude of discrete points, form the first step in identifying the unknown particles. The calorimeters measure the energy of both neutral and charged particles by interacting with them, resulting in creating cascades of secondary particles. The Muon Spectrometer, the outermost component of the detector, makes additional measurements of highly penetrating muons, which are capable of passing through the inner layers without interaction. Finally, the magnet systems bend charged particles in the Inner Detector and the Muon Spectrometer; their direction of motion and degree of curvature become indicative of their charge and momentum, respectively. The detector generates unmanageably large amounts of raw data: about 25 megabytes per event, multiplied by 40 million beam crossings per second in the center of the detector, producing a total of 1 petabyte of raw data per second. Thus, a trigger system is needed in order to select potentially interesting events for storage in real-time, so as to avoid being overwhelmed by background processes. The ATLAS trigger system uses simple information to identify the most interesting events to retain for detailed analysis. The data acquisition system receives and buffers the event data from the detector-specific readout electronics. Grid computing is being extensively used for event reconstruction, allowing the parallel use of computer networks throughout the world. A major problem at the ATLAS detector is the huge radiation background, coming from the collisions at the interaction point. This background causes several problems such as radiation damage to silicon detectors and readout electronics, ageing of the subdetectors, radiation deposits that disrupt electronic signals or destroy components, and background signals resulting in spurious and random triggers. For the limitation of these consequences, ATLAS uses almost 3000 tonnes of shielding in a multilayer design, taking advantage of the absorbing capacities of different materials.
Size: 8.49 MB - Last synced at: about 2 years ago - Pushed at: almost 8 years ago - Stars: 0 - Forks: 0
mocassin/MOCASSIN-2.0
MOCASSIN - MOnte CArlo SimulationS of Ionized Nebulae, Version 2.0
Language: Makefile - Size: 18.2 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 0 - Forks: 1
mocassin/MOCASSIN-3.0
MOCASSIN - MOnte CArlo SimulationS of Ionized Nebulae, Version 3.0
Language: Makefile - Size: 8.62 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 0 - Forks: 1
mocassin/MOCASSIN-Voronoi
MOCASSIN - MOnte CArlo SimulationS of Ionized Nebulae on Voronoi Meshes
Language: Makefile - Size: 5.87 MB - Last synced at: over 1 year ago - Pushed at: about 4 years ago - Stars: 0 - Forks: 0
MauroCE/Dissertation
Third year mathematics dissertation on variational, laplace and mcmc approximations of bayesian logistic regression
Language: Jupyter Notebook - Size: 50.5 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 2
puneat/Asset_Price_Modelling
An asset-pricing model using historical prices. Volatility of the asset is modeled as the random variable that changes over time and each iteration. For modelling the future price behavior, Monte Carlo simulations were performed.
Language: HTML - Size: 5.56 MB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0
QuantessentiallyMe/how_do_you_like_them_apps
Here I will be doing budget analysis with Plaid, creating a retirement plan with Monte Carlo simulations, and generating a financial report.
Language: Jupyter Notebook - Size: 530 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0
gitesei/faunus Fork of mlund/faunus
A Framework for Metropolis Monte Carlo Simulation of Molecular Systems http://mlund.github.io/faunus
Language: C++ - Size: 34.4 MB - Last synced at: about 2 years ago - Pushed at: about 4 years ago - Stars: 0 - Forks: 2
andriyka/Monte-Carlo-integral-estimation
Parallel and sequential versions of Monte Carlo integral estimation algorithm implemented in Scala
Language: Scala - Size: 1.95 KB - Last synced at: about 2 years ago - Pushed at: almost 7 years ago - Stars: 0 - Forks: 0
ankushbhatia2/monte-carlo-sim
A simple Monte Carlo Simulation for simulating chances of winning a gambler.
Language: Python - Size: 0 Bytes - Last synced at: about 2 years ago - Pushed at: over 8 years ago - Stars: 0 - Forks: 0
equib/MOCASSIN-2.0 Fork of mocassin/MOCASSIN-2.0
MOCASSIN - MOnte CArlo SimulationS of Ionized Nebulae, Version 2.0
Language: Makefile - Size: 18.2 MB - Last synced at: over 1 year ago - Pushed at: over 8 years ago - Stars: 0 - Forks: 0
