This information has also been entered into the syllabus. Please consult the syllabus for detailed information about lectures, exams, grading and many other matters related to the course. After introductory lectures on the basics of computing, the course proceeds toward modern methods of computational physics. In particular the data parallel paradigm and graphics rendering are illustrated through computationally intensive applications.
All of the techniques are presented in the context of specific projects. For some problems, students are asked to play the role of application scientists, working with the computer in an interactive manner to perform a variety of numerical experiments. For other problems, students are required to take an active part in designing the code that will be used for the solution. Emphasis in all cases will be on the importance that the proper formulation of a problem plays for its ultimate computational solution. Some simple operations are implemented by parallel algorithms on a two-dimensional array representing the intensity values of the pixels in a monochrome image.
A relationship is established between the operations performed by computer e. Advanced visualization software is presented.
Top and bottom left: the image before and after the blurring operation, which can be interpreted as a diffusion process. Various methods for solving Poisson's equation are evaluated in terms of their suitability for the data parallel paradigm. Students are asked to write the code for some basic iterative methods of solution on a parallel machine. Numerical experiments are used to demonstrate the occurrence of critical slowing down. Multigrid methods and other algorithms for overcoming critical slowing down are analyzed for implementation in a data parallel environment. The complex wave function is represented graphically by means of a color map whereby its phase is encoded by the color circle.
Here the student is provided with code and asked to use it as an application scientist, experimenting with a wide range of initial data. Stochastic algorithms Monte Carlo methods are introduced for the simulation of models, such as the Ising model and the N-state Potts model, which exhibit interesting thermodynamical behavior and phase transitions.
Programs for the implementation of such algorithms on a parallel machine are analyzed. Students then use these programs to perform large scale numerical experiments on phase transitions.
Particular attention is given to the management of the large base of data that the simulations generate and to developing the auxiliary programs required for the analysis and interpretation of the data. Students are asked to write serial code for the implementation of molecular dynamics simulations.
Following optimization and numerical experimentation with this code, the students and instructor collaborate to write highly efficient code for the simulation on a parallel machine.
List of unsolved problems in physics - Wikipedia
Performance for the serial and parallel modes of computation are compared and evaluated. Atlee Jackson.
Practical Relativity. Richard N. Physical Kinetics. States of Matter. David L. A Course in Theoretical Physics. John Shepherd. Theoretical Physics. The Spinning Magnet. Alanna Mitchell. Jim Al-Khalili. An Introduction to Statistical Thermodynamics.
Terrell L. Electrodynamics and Classical Theory of Fields and Particles. Special Relativity and Classical Field Theory. Leonard Susskind. Robert Piccioni. An Introduction to Continuum Mechanics. Our Seti Problem. Robert Stetson. Quantum Mechanics with Basic Field Theory. Bipin R. Topics in Advanced Quantum Mechanics. Barry R. Nikola Tesla. The God Blunder. Mike Hockney.
Modern physics course materials
Plasmon Resonances in Nanoparticles. Isaak D Mayergoyz. Classical Electricity and Magnetism. Wolfgang K. Thermodynamics and Statistical Mechanics. Peter T. The Expanding Universe. William D. Classical Electromagnetism in a Nutshell. Anupam Garg. Dennis M. Gregory H. Theory of Electromagnetic Wave Propagation. Charles Herach Papas. Thermal Physics. Ralph Baierlein. Elements of Vector Algebra.
Rishi Kumar Jha. Grounding and Shielding. Ralph Morrison. Problems in Quantum Mechanics.
Dielectric Materials for Wireless Communication. Mailadil T. Einstein in Matrix Form. Dhiraj Sinha. Special Relativity.
Fundamentals of the Theory of Metals. Enhanced Quantization. John R Klauder. Electromagnetics of Body Area Networks.