Computational methods in science and technology II

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Aim of the course

This lecture addresses advanced numerical algorithms, and then shows how to build applications, which perform numerical simulations and use numerical libraries and computing packages.

Lecture programme

Examples of so-called "great challenges” and their solutions. Fast Fourier transform. Random numbers and Monte Carlo method. Minimization of function: the "natural solvers" approach (including simulated annealing). Numerical solution of ordinary differential equations. Numerical solution of partial differential equations. Principles and examples of numerical solutions of selected problems in science and technology

Overview of the course elements

The lecture is accompanied by laboratory classes. Content of the course consolidates and extends the knowledge taught at lectures. Students will be able to create and verify the applications designed to solve typical numerical problems in science and technology.

Reading list

1. T. Pang. Metody obliczeniowe w fizyce. PWN, 2001
2. M.T. Heath. Scientific Computing: An Introductory Survay, McGraw-Hill, 2002
3. D. Potter. Metody obliczeniowe fizyki. Fizyka komputerowa, PWN, wydania późniejsze niż 1978
4. W.H. Press, B.P. Flannery, S.A. Teukolsky, W.T. Vettering. Numerical Recipes. Cambridge Univ., 2007
5. Wybrane artykuły z J. Computational Science, materialy konferencji serii ICCS (www.iccsmeeting. org)

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