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Latest update : 3 September 2014.

Articles in this section

  • Advanced Math. for Physics

    These lectures allow to acquire familiarity and operational knowledge of the mathematics of symmetry groups, as a transversal and structuring notion of modern Physics, from condensed matter to particle physics.
    Syllabus : " Advanced Mathematics for Physics "
    - Lectures 20 hours, Tutorials 10 hours (2nd Semester) -
    (Robin Zegers)
    Chapter 1: General Group theory (definitions and main theorems)
    Chapter 2: Finite and discrete groups Examples include reflection groups and lattices in (...)

  • Computing Tools

    Syllabus : " Computing Tools "
    (Olivier Brand-Foissac)
    [mandatory course]
    A survival kit/toolkit for working with computers:
    * Basics of computers : structure, hardware, interfaces, networks/internet
    * Operating systems, Linux, environment, compiling
    * Reminds of programming languages: low level, high level, scripts, shell [examples from C, Python, Perl...]
    * Numerical algorithms for physics, programming tips and strategies [useful libraries and softwares], parallel programming
    * (...)

  • Sensors, Meas. and Signal Processing

    This course introduces the measurement process, the sources of uncertainties and the method to handle them. Basic signal processing techniques and linear filtering will also be presented. The principles of operation of some sensors, such as light detectors will be discussed as well.
    Syllabus : " Sensors, Measurements and Signal Processing "
    - Lectures 12 hours, Tutorials 12 hours, Laboratory Work 6 hours (1st Semester) -
    (Réza Ansari, Zoé Mokhtari)
    Chapter 1: Sensors and measurements (...)

  • Mathematical and Statistical Methods

    This tool course teaches how to extract relevant scientific information from experimental and simulated data; Modern statistical methods to handle and analyze big data flows (data mining, multivariate analysis) will be discussed.
    Syllabus : " Mathematical and Statistical Methods "
    - Lectures 20 hours, Tutorials 10 hours (1st Semester) -
    (Pierre Désesquelles)
    Chapter 1: Statistical tools From probabilities to statistics Distribution, pdf, distribution function Characterization Matrix (...)


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