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Numerical Physics and Machine Learning

Course description

NumPhys is a general course in Computational Physics, with applications in Statistical Physics and Condensed Matter. We cover the many algorithms used in modern many-body problems: molecular dynamics, Monte Carlo (classical and quantum), exact diagonalization and optmization in complex landscapes. Implications to computer science are also discussed. We focus on algorithms and physics, not on programming and heavy numerics. The theoretical lecture is followed by a tutorial introducing many concrete numerical exercises. You will have to hand in 3 homeworks.



  • Lectures on Fridays: 14.0-16.00
  • Tutorials on Fridays: 16h00-18.00
  • ENS, 24 rue Lhomond, room Conf IV (2nd floor)

Here you find the scheduling of Lectures, Tutorials and Homeworks


The working language for this course is English.
Programming Language: Python 3. See Memento Python
No previous experience in programming is required.
You need first of all to have Python installed with at least modules NumPy, SciPy and matplotlib.


3 homeworks (10 points each) + 1 MCQ (20 points) + 1 oral exam (50 points)


The WIFI network is: PHYS-GUEST

The WIFI password for this networks is: PhysiqueENS

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Accept the certificat and enter the password:


here it is please register