ICFP NumPhys Paris: Difference between revisions
No edit summary |
|||
Line 22: | Line 22: | ||
* ENS, 24 rue Lhomond, room L367 | * ENS, 24 rue Lhomond, room L367 | ||
Here you find the schedule of | |||
[https://docs.google.com/spreadsheets/d/1NlHTj7ypYoVyy6c9jpq-93NxDryAfbvy1vnOgA3ucPE/edit#gid=245193379/pubhtml Lectures, Tutorials and Homeworks] | [https://docs.google.com/spreadsheets/d/1NlHTj7ypYoVyy6c9jpq-93NxDryAfbvy1vnOgA3ucPE/edit#gid=245193379/pubhtml Lectures, Tutorials and Homeworks] | ||
Revision as of 22:42, 28 August 2019
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.
Team
- Alberto ROSSO (LPTMS, CNRS et Université Paris-Sud, Orsay)
- Guillaume ROUX (LPTMS, CNRS et Université Paris-Sud, Orsay)
- Marcello CIVELLI (LPS, Université Paris-Sud, Orsay)
Schedule
- Lectures on Fridays: 13.45-15.45
- Tutorials on Fridays: 15.45-17.45
- ENS, 24 rue Lhomond, room L367
Here you find the schedule of Lectures, Tutorials and Homeworks
Language
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.
Grading
3 homeworks (30 points) + 1 MCQ (20 point), oral exam (50 points)
WIFI
The network "visiteurs.phys.ens.fr" is for the visitors.
The WIFI password for this networks is: PhysiqueENS
Then you can run a navigator (Firefox, Chrome, IE, Safari...)
Accept the certificat and enter the password available for the current week:
- XXXX
Forum
here it is please register
References
- SMAC W. Krauth Statistical Mechanics: Algorithms and Computations (Oxford: Oxford University Press) (2006)
- Other references are specified in each lectures