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Lecture

Numerical Methods for Physics: Iterative Solutions and Mesh Convergence

In course

PHYS-203: Computational physics I

Aborder, formuler et résoudre des problèmes de physique en utilisant des méthodes numériques simples. Comprendre les avantages et les limites de ces méthodes (stabilité, convergence). Illustrer différents sujets de physique traités dans d'autres cours. ...

Description

This lecture covers the application of finite differences to solve linear algebraic systems arising from partial differential equations, focusing on iterative methods like Jacobi and Gauss-Seidel. It also explores the convergence criteria related to the number of iterations and mesh size, illustrated with exercises on singularities in physical systems.

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Instructor

Laurent Villard

Originaire de Vauffelin (BE), Laurent Villard est né en 1961. Après avoir obtenu le diplôme d'ingénieur physicien de l'EPFL en 1983, il est assistant au CRPP où il entame une thèse. Ses études portent sur l'étude théorique du chauffage des plasmas par ondes radiofréquences, développant pour cela un code de calcul numérique sous contrat avec le Joint European Torus (JET, Angleterre). Il obtient en 1987 le doctorat ès sciences. En 1988, il est engagé en tant que chargé de cours à l'Université d'Addis Abeba, enseignant l'électromagnétisme et l'électrodynamique. En 1989 et 1990, il rejoint le Polytechnic Education Development Centre de l'Institute of Technology of Bandung (ITB, Indonésie). Ses activités contribuent à la formation et au soutien du personnel enseignant des dix-sept écoles polytechniques nouvellement créées en Indonésie. A la fin 1990, il revient au CRPP en tant que collaborateur scientifique. En 1993 il est nommé professeur assistant. En 1999, il est nommé maître d'enseignement et de recherche, puis, en 2005, professeur titulaire. En collaboration avec JET et General Atomics (USA) il étudie les instabilités qui peuvent être provoquées par les particules énergétiques issues du processus de fusion nucléaire. Avec des scientifiques du Keldysh Institute (Moscou), il s'intéresse au calcul de l'équilibre et de la stabilité de configurations du type tokamak. Enfin, en collaboration notamment avec le Max-Planck Institute fuer Plasma Physik, ses recherches portent sur la simulation numérique, par calcul à haute performance (HPC), de la turbulence dans les plasmas magnétisés.

Official source

Ontological neighbourhood

Mathematics

Analysis: Numerical analysis

Related concepts (32)

Finite difference

A finite difference is a mathematical expression of the form f (x + b) − f (x + a). If a finite difference is divided by b − a, one gets a difference quotient. The approximation of derivatives by finite differences plays a central role in finite difference methods for the numerical solution of differential equations, especially boundary value problems. The difference operator, commonly denoted is the operator that maps a function f to the function defined by A difference equation is a functional equation that involves the finite difference operator in the same way as a differential equation involves derivatives.

Partial differential equation

In mathematics, a partial differential equation (PDE) is an equation which computes a function between various partial derivatives of a multivariable function. The function is often thought of as an "unknown" to be solved for, similar to how x is thought of as an unknown number to be solved for in an algebraic equation like x2 − 3x + 2 = 0. However, it is usually impossible to write down explicit formulas for solutions of partial differential equations.

Finite difference method

In numerical analysis, finite-difference methods (FDM) are a class of numerical techniques for solving differential equations by approximating derivatives with finite differences. Both the spatial domain and time interval (if applicable) are discretized, or broken into a finite number of steps, and the value of the solution at these discrete points is approximated by solving algebraic equations containing finite differences and values from nearby points.

Iterative method

In computational mathematics, an iterative method is a mathematical procedure that uses an initial value to generate a sequence of improving approximate solutions for a class of problems, in which the n-th approximation is derived from the previous ones. A specific implementation with termination criteria for a given iterative method like gradient descent, hill climbing, Newton's method, or quasi-Newton methods like BFGS, is an algorithm of the iterative method.

Differential equation

In mathematics, a differential equation is an equation that relates one or more unknown functions and their derivatives. In applications, the functions generally represent physical quantities, the derivatives represent their rates of change, and the differential equation defines a relationship between the two. Such relations are common; therefore, differential equations play a prominent role in many disciplines including engineering, physics, economics, and biology.

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