Level of Education
One year of college
ECTS
4 credits
Training Structure
College of Sciences
Description
Instruction takes the form of projects led by pairs of students, supplemented along the way by online sessions that allow students to apply concepts from physics and chemistry on a computer.
Depending on the needs, a few more traditional classes are scheduled to supplement the students' training.
Tentative schedule:
1. Preliminaries: Visualization of scalar and vector fields: gradient, divergence, rotator, Laplacian, contour lines, surface and volume integrals, numerical solutions to point mechanics problems
2. Supervised projects offered to students: These projects involve the collection, processing, and interpretation of data. The general theme we have chosen is to train students to understand the concepts of “statistical field theory,” that is, the concept of probability applied to functions. This theme is ubiquitous in modern science: image processing and analysis, AI, statistical physics, dynamical systems and stochastic processes, sequencing, epidemiology, economics, observational cosmology..., and the combination of an approach that integrates numerical methods, mathematical ideas, and modeling seems to emerge naturally (examples of projects, list provided for illustrative purposes only: sand-grain statistics, the Poisson and Gaussian distributions, connection to the Beer-Lambert law via the concept of effective cross-section; observational data in cosmology: matter/radiation distribution on the scale of the universe; epidemiological statistics and dynamics; microscopy and analysis of Brownian motion; etc.)
3. Additional Topics in Chemistry: Slater’s effective theory for atoms (effective screening potential), molecular orbitals, fragment approach
Knowledge Assessment
Continuous assessment, through oral defenses and presentations of project results.
Written exams for supplementary coursework.