Cho, Shinil.
Monte Carlo Simulations Using Microsoft EXCEL® [electronic resource] / by Shinil Cho. - 1st ed. 2023. - IX, 159 p. 134 illus., 106 illus. in color. online resource. - Synthesis Lectures on Mathematics & Statistics, 1938-1751 . - Synthesis Lectures on Mathematics & Statistics, .
Probability distribution functions -- Idea of Monte Carlo simulations -- Brownian motion and diffusion equation -- Quantum Diffusion Monte Carlo Method -- Metropolis-Hastings algorithm for Ising model -- Chaos and fractal -- Appendix.
This book offers step-by-step descriptions of various random systems and explores the world of computer simulations. In addition, this book offers a working introduction to those who want to learn how to create and run Monte Carlo simulations. Monte Carlo simulation has been a powerful computational tool for physics models, and when combined with the programming language Excel, this book is a valuable resource for readers who wish to acquire knowledge that can be applied to more complex systems. Visualization of the simulation results via the Visual Basic built in Microsoft EXCEL is presented as the first step towards the subject. Prior experience with the Excel add-in VBA is kept to a minimum. In addition, a chapter on quantum optimization simulation utilizing Python is added to explore the quantum computation. Readers will gain a fundamental knowledge and techniques of simulation physics, which can be extended to STEM projects and other research projects. In addition, this book: Includes a step-by-step guide to Monte Carlo simulations using Microsoft EXCEL for the analysis and visualization; Provides fundamental knowledge and techniques of simulation physics, which can be extended to STEM projects; Features a working introduction for those who want to learn how to create and run Monte Carlo simulations.
9783031338861
10.1007/978-3-031-33886-1 doi
Mathematical physics.
Computer simulation.
Mathematics--Data processing.
Computational Physics and Simulations.
Computational Mathematics and Numerical Analysis.
Mathematical Physics.
QC19.2-20.85
530.10285
Monte Carlo Simulations Using Microsoft EXCEL® [electronic resource] / by Shinil Cho. - 1st ed. 2023. - IX, 159 p. 134 illus., 106 illus. in color. online resource. - Synthesis Lectures on Mathematics & Statistics, 1938-1751 . - Synthesis Lectures on Mathematics & Statistics, .
Probability distribution functions -- Idea of Monte Carlo simulations -- Brownian motion and diffusion equation -- Quantum Diffusion Monte Carlo Method -- Metropolis-Hastings algorithm for Ising model -- Chaos and fractal -- Appendix.
This book offers step-by-step descriptions of various random systems and explores the world of computer simulations. In addition, this book offers a working introduction to those who want to learn how to create and run Monte Carlo simulations. Monte Carlo simulation has been a powerful computational tool for physics models, and when combined with the programming language Excel, this book is a valuable resource for readers who wish to acquire knowledge that can be applied to more complex systems. Visualization of the simulation results via the Visual Basic built in Microsoft EXCEL is presented as the first step towards the subject. Prior experience with the Excel add-in VBA is kept to a minimum. In addition, a chapter on quantum optimization simulation utilizing Python is added to explore the quantum computation. Readers will gain a fundamental knowledge and techniques of simulation physics, which can be extended to STEM projects and other research projects. In addition, this book: Includes a step-by-step guide to Monte Carlo simulations using Microsoft EXCEL for the analysis and visualization; Provides fundamental knowledge and techniques of simulation physics, which can be extended to STEM projects; Features a working introduction for those who want to learn how to create and run Monte Carlo simulations.
9783031338861
10.1007/978-3-031-33886-1 doi
Mathematical physics.
Computer simulation.
Mathematics--Data processing.
Computational Physics and Simulations.
Computational Mathematics and Numerical Analysis.
Mathematical Physics.
QC19.2-20.85
530.10285