This new and updated deals with all aspects of Monte Carlo simulation of
complex physical systems encountered in condensed-matter physics and statistical
mechanics as well as in related fields, for example polymer science,
lattice gauge theory and protein folding.
After briefly recalling essential background in statistical mechanics and probability
theory, the authors give a succinct overview of simple sampling methods.
The next several chapters develop the importance sampling method,
both for lattice models and for systems in continuum space....
At present, thickness measurement of materials based on effect of backscattering gamma-ray has been widely used in industry in our country. The report presented research in measuring thickness of some materials such as paper, plastic, aluminum and steel with using the dedicated system of MYO-101, having scintillation detector of YAP(Ce) and gamma-ray of 60 keV of Am-241 source, by Monte-Carlo simulation using the code of MCNP. The simulation was checked by experimental measurements.
Lecture Monte carlo simulations: Application to lattice models, part I - Basics. The main contents of this chapter include all of the following: Introduction, thermodynamics and statistical mechanics, phase transition, probability theory.
Lecture Monte carlo simulations: Application to lattice models, part II - Monte carlo simulation methods. The main contents of this chapter include all of the following: The spin models, boundary conditions, simple sampling monte carlo methods, importance sampling monte carlo methods.
Lecture Monte carlo simulations: Application to lattice models, part III - Finite size effects and reweighting methods. The main contents of this chapter include all of the following: Finite size effects, single histogram method, multiple histogram method, wang-Landau method, the applications.
The objective of this book is to introduce recent advances and state-of-the-art applications of
Monte Carlo Simulation (MCS) in various fields. MCS is a class of statistical methods for
performance analysis and decision making based on taking random samples from underly‐
ing systems or problems to draw inferences or estimations.
Let us make an analogy by using the structure of an umbrella to define and exemplify the
position of this book within the fields of science and engineering. Imagine that one can place
MCS at the centerpoint of an umbrella and define the...
The Texas Instrument TMS320VC5510 DSK’s calculation abilitiy with different program languages is investigated for minimum the DSP’s measurement time. The steps of Monte Carlo simulations embedded into the DSK’s flash through the DSK’s JTAG interface for optical parameters measurement including absorption coefficient µ a , scattering coefficient µ s and anisotropy g are presented. The obtained results for diluted milk standard samples are also reported.
Topic 8 - Multinat corp monte carlo simulations using excel and @risk. In this chapter, students will be able to understand: Apply Interest Rate Parity (IRP) and Unbiased Forward Rate (UFR) to forecast exchange rates; use Bloomberg forex quotes, forwards, volatilities and interest rates;...
Simulation and the Monte Carlo Method, Second Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the major topics that have emerged in Monte Carlo simulation since the publication of the classic First Edition over twenty-five years ago.
Trong công trình này, tác giả sử dụng hai chương trình mô phỏng Monte Carlo MCNP5 và GEANT4 để mô phỏng hệ đầu đò HPGe kí hiệu GMX35P4-70, sau đó nghiên cứu đặc trưng phổ và tính toán hiệu suất đỉnh. Kết quả cho thấy khi thay đổi bề dày lớp chết từ 1.8mm đến 2.2mm đáp ứng phổ mô phỏng và hiệu suất đỉnh phù hợp với thực nghiệm hơn.
Lecture Operations management - Chapter 13 supplement: Operational decision-making tools include all of the following contents: Monte Carlo simulation, computer simulation with excel, areas of simulation application. Inviting you refer.
In this chapter student will understand how VaR measures the risk of a portfolio; compute static portfolio VaR using formulas and normal distribution functions, a Monte Carlo simulation of a random walk model of asset returns, and @Risk; write VBA Macros using “For Loops” and the “Cells” objects.
Topic 13 - Option contracts and hedging, monte carlo valuation, and black-scholes. After completing this unit, you should be able to: Compute the payoffs and profits of plain vanilla option contracts, value options using monte carlo simulation and black-scholes models, computed hedged and unhedged cashflows using options and forwards, value arithmetic asian options, use @Risk to value options and compute position risk.
Topic 11 - Monte carlo simulations using excel and @risk: Hoffman mines. The main contents of the chapter consist of the following: Financial simulation process, hoffman gold mine financial statement simulation, distributions and correlations,.....
Topic 13 - Monte carlo simulations using excel and @risk: Retirement simulation. The main contents of the chapter consist of the following: Financial simulation process, retirement simulation, geometric brownian motion asset return model (random walk),...
This book provides an introduction to the theory and practice of Monte Carlo and
Simulation methods. It arises from a 20 hour course given simultaneously to two groups
of students. The first are final year Honours students in the School of Mathematics at the
University of Edinburgh and the second are students from Heriot Watt and Edinburgh
Universities taking the MSc in Financial Mathematics.
The intention is that this be a practical book that encourages readers to write and
experiment with actual simulation models.
Chương 1 - Mô phỏng monte carlo (monte carlo simulation). Sau khi học xong chương này người học có thể: Nắm vững các khái niệm dùng trong mô phỏng Monte Carlo (Monte Carlo Simulation, MCS), ứng dụng MCS một cách thích hợp trong quản lý dự án & quản lý xây dựng. Mời các bạn cùng tham khảo.
(BQ) Part 2 book "Business analytics" hass contents: Introduction to data mining, spreadsheet modeling and analysis, monte carlo simulation and risk analysis, linear optimization, applications of linear optimization, integer optimization, decision analysis.
In this chapter, students will be able to understand: Simulate portfolios with multiple periods, changing asset allocation, and contributions; create a personal financial planning model; use @Risk and macros to run Monte Carlo simulations, use @Risk goal seek.
This book presents and develops major numerical methods currently used for solving
problems arising in quantitative finance. Our presentation splits into two parts.
Part I is methodological, and offers a comprehensive toolkit on numerical methods
and algorithms. This includes Monte Carlo simulation, numerical schemes for
partial differential equations, stochastic optimization in discrete time, copula functions,
transform-based methods and quadrature techniques.
Part II is practical, and features a number of self-contained cases.