TAILIEUCHUNG - Fundamentals of Monte Carlo Particle Transport

Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. This course provides a balanced approach to the theory and practice of Monte Carlo simulation codes, with lectures on transport, random number generation, random sampling, computational geometry, collision physics, tallies, statistics, eigenvalue calculations, variance reduction, and parallel algorithms. | LA-UR-05-4983 Approved for public release; distribution is unlimited. Title: Author(s): Submitted to: FUNDAMENTALS OF MONTE CARLO PARTICLE TRANSPORT FORREST B. BROWN Lecture notes for Monte Carlo course Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is operated by the University of California for the . Department of Energy under contract W-7405-ENG-36. By acceptance of this article, the publisher recognizes that the . Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or to allow others to do so, for . Government purposes. Los Alamos National Laboratory requests that the publisher identify this article as work performed under the auspices of the . Department of Energy. Los Alamos National Laboratory strongly supports academic freedom and a researcher’s right to publish; as an institution, however, the Laboratory does not endorse the viewpoint of a publication or guarantee its technical correctness. Form 836 (8/00) Fundamentals of Monte Carlo Particle Transport Lecture 1 Fundamentals of Monte Carlo Particle Transport Forrest B. Brown Monte Carlo Group (X-3) Los Alamos National Laboratory 1 -1 LA-UR-04–8817 Abstract Fundamentals of Monte Carlo Particle Transport Solving particle transport problems with the Monte Carlo method is simple just simulate the particle behavior. The devil is in the details, however. This course provides a balanced approach to the theory and practice of Monte Carlo simulation codes, with lectures on transport, random number generation, random sampling, computational geometry, collision physics, tallies, statistics, eigenvalue calculations, variance reduction, and parallel algorithms. This is not a course in how to use MCNP or any other code, but rather provides in-depth coverage of the fundamental methods used in all modern Monte Carlo particle transport codes. The course content is suitable for beginners and code

• Vật lý
• Random Number Generation
• Random Sampling
• Computational Geometry
• Collision Physics
• Tallies & Statistics
• Data security
• Lecture Data security and encryption
• Mã hóa dữ liệu
• Bảo mật dữ liệu
• Stream Ciphers
• Math Library Functions
• Function Definitions
• Function Prototypes
• Storage Classes
• Functions with Empty Parameter Lists
• Simulation methods
• Econometrics for Finance
• Introductory Econometrics for Finance
• Financial data
• Financial modelling
• Data security and encryption
• Network security
• Symmetric ciphers
• Asymmetric ciphers
• Cryptographic data integrity algorithms
• Mutual trust
• Regression model
• Purpose of econometrics