Why the Monte Carlo method is so important today

2014/06/20 by Dirk P. Kroese, Tim Brereton, Thomas Taimre +1 · 3 citations
Physics and Astronomy · Mathematics · #Scientific Research and Discoveries #Mathematical Approximation and Integration #Markov Chains and Monte Carlo Methods #Markov chain Monte Carlo #Monte Carlo method #Computer science #Monte Carlo method in statistical physics #Monte Carlo molecular modeling #Hybrid Monte Carlo #Statistical physics #Mathematics #Statistics #Physics

paper · doi:10.1002/wics.1314

openalex publication_date 2014/06/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/31

Abstract

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: 10.1002/wics.1314 This article is categorized under: Statistical and Graphical Methods of Data Analysis > Markov Chain Monte Carlo (MCMC) Statistical Models > Simulation Models

Citations

• MCMC using Hamiltonian dynamics
• A general method for numerically simulating the stochastic time evolution of coupled chemical reactions
• Equation of State Calculations by Fast Computing Machines
• Probabilistic roadmaps for path planning in high-dimensional configuration spaces

Cited by

• BranchBench: Aligning Database Branching with Agentic Demands
• Law of large numbers [wikipedia]
• Monte Carlo method [wikipedia]

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• The Convergence of Markov chain Monte Carlo Methods: From the Metropolis method to Hamiltonian Monte Carlo
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