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…mehr
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.
Shinil Cho attended Rikkyo University in Tokyo, Japan, for his BS; Seoul National University in Seoul, Korea, for his MS; and The Ohio State University in Ohio, USA, for his PhD. He held post-doctoral fellowships at The Ohio State University and University of Florida, and he was also a visiting professor at the University of South Carolina. He has been at La Roche University since 1995. Currently has been a professor at La Roche since 1995. He has conducted research in cryogenic magnetic resonance spectroscopy below 1K and biometric fingerprint authentication. His current research interests include quantum computation, biometrics, and physics education. Other than physics, he has many publications and has done many presentations on biometrics in London, Tokyo, Hong Kong, Singapore, and several cities in the United States.
Inhaltsangabe
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.
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.
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.
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.
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