# Why the Monte Carlo method is so important today

@article{Kroese2014WhyTM, title={Why the Monte Carlo method is so important today}, author={Dirk P. Kroese and Tim J. Brereton and Thomas Taimre and Zdravko I. Botev}, journal={Wiley Interdisciplinary Reviews: Computational Statistics}, year={2014}, volume={6} }

Since the beginning of electronic computing, people have been interested in carrying out random experiments on a computer. Such Monte Carlo techniques are now an essential ingredient in many quantitative investigations. Why is the Monte Carlo method (MCM) so important today? This article explores the reasons why the MCM has evolved from a ‘last resort’ solution to a leading methodology that permeates much of contemporary science, finance, and engineering. WIREs Comput Stat 2014, 6:386–392. doi…

## 408 Citations

### Stitching Monte Carlo samples

- PhysicsThe European Physical Journal C
- 2022

Monte Carlo (MC) simulations are extensively used for various purposes in modern high-energy physics (HEP) experiments. Precision measurements of established Standard Model processes or searches for…

### The principle and application of Monte Carlo simulation in public health, finance, and physics

- PhysicsOther Conferences
- 2022

The Monte Carlo Simulation is a widely adopted measure to solve for complicated results using repeated simulations. Its application has extended to a plethora of subjects and different variants of…

### Monte Carlo Simulation of Neutrons Scattering in the Reactor

- Physics
- 2018

The significance of Monte Carlo simulation to engineer and scientist is now broadly stated and maximum undergraduates have a few training within the use of computers and feature get right of entry to…

### Adapting Hybrid Monte Carlo methods for solving complex problems in life and materials sciences

- Computer Science
- 2018

It is shown that equipping the Hybrid Monte Carlo algorithm with extra features makes it even a “smarter” sampler and, no doubts, a strong competitor to the wellestablished molecular simulation techniques such as molecular dynamics and Monte Carlo.

### Object kinetic Monte Carlo methods applied to modeling radiation effects in materials

- PhysicsComputational Materials Science
- 2019

### Approximation of the Monte Carlo Sampling Method for Reliability Analysis of Structures

- Computer Science
- 2016

A simple algorithm was proposed to estimate low failure probabilities using a small number of samples in conjunction with the Monte Carlo method, presented in a step-by-step flowchart, for the purpose of easy programming and implementation.

### Metropolis Monte Carlo simulation scheme for fast scattered X-ray photon calculation in CT.

- PhysicsOptics express
- 2019

This study develops a novel GPU-based Metropolis MC (gMMC) with a novel path-by-path simulation scheme and demonstrates its effectiveness in an example problem of scattered X-ray photon calculation in CT.

### Comparison of uncertainty analysis of the Montecarlo and Latin Hypercube algorithms in a camera calibration model

- Computer Science2018 IEEE 2nd Colombian Conference on Robotics and Automation (CCRA)
- 2018

The results show the advantages of the Latin Hypercube method over the Monte Carlo method, taking into account the number of executions of the model, maintaining a 95 percent confidence level and reducing the execution time considerably.

### Bayesian Probabilistic Numerical Integration with Tree-Based Models

- Computer ScienceNeurIPS
- 2020

A new Bayesian numerical integration algorithm based on Bayesian Additive Regression Trees (BART) priors, which this paper calls BART-Int, which is easy to tune and well-suited for discontinuous functions.

### Correlation effects in parallel tempering and the role of the swapping frequency.

- PhysicsPhysical chemistry chemical physics : PCCP
- 2020

This work shows that high frequency swaps can induce a systematic bias on the sampled REMD equilibrium distributions, and should serve as a monitor for using too frequent swapping attempts in parallel tempering simulations of generic Hamiltonians, including the ones used in atomistic simulations.

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