Level of education
Master's degree
ECTS
4 credits
Training structure
Faculty of Science
Description
During this course, students will learn about the main numerical methods used in scientific software, particularly in theoretical chemistry programs.
Hourly volumes:
CM: 21
TD: 9
Objectives
- working independently: setting priorities, managing your time
- develop digital tools for chemistry
- use the Linux system
- express various numerical methods in the form of algorithms
- convert an algorithm into a programming language
- know which of these methods and tools are used in other fields outside chemistry
- Independently design and develop IT tools, from the initial specifications to the final product.
Teaching hours
- Numerical Methods for Theoretical Chemistry - LectureLecture9 p.m.
- Numerical Methods for Theoretical Chemistry - TutorialTutorials9 a.m.
Mandatory prerequisites
Fundamentals of imperative and procedural programming, programming language for scientific computing (Fortran 95, for example).
Knowledge assessment
Continuous assessment (3 projects).
Syllabus
- Interpolation, Extrapolation
- a) Global interpolation (Lagrange polynomials, quotient polynomial, trigonometric)
and general by an analytic function)
- b) Local interpolation (natural splines)
- c) Multidimensional interpolation (bilinear and bicubic, splines) - Integration
(quadratures, analytical, multidimensional)
- Integration and derivation of a function
- a) Simple methods
- b) Quadrature method
- c) Multidimensional integrals
- d) Digital derivation
- Linear Systems, Roots, and Extremes
- a) Solving linear systems (tridiagonal matrix, LU decomposition, method
Gauss-Seidel iterative)
- b) Roots (bisection method, Newton-Raphson method)
- c) Extrema (one-dimensional, Powell method, simulated annealing, genetic algorithms)
- Diagonalization: Properties of Eigenvalue Equations
- a) Householder reduction
- b) Diagonalization of a tridiagonal matrix (QL algorithm, bisection)
- c) Eigenvectors by inverse iteration
- d) Lanczos method
- e) Davidson method
- Model Adjustment
- a) Least squares principle
- b) General linear method
- c) Singular value decomposition
- d) Nonlinear model (Levenberg-Marquardt)
- Spectral and Pseudo-spectral Methods
- a) Fourier transform (discrete transform, FFT)
- b) Pseudo-spectral methods
Additional information
Administrative contact(s):
Master's Program in Chemistry Secretariat
https://master-chimie.edu.umontpellier.fr/