ICFP NumPhys Paris: Difference between revisions
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* Tutorials on Fridays: 15.45-17.45 | * Tutorials on Fridays: 15.45-17.45 | ||
* ENS, 24 rue Lhomond, room L367 | * ENS, 24 rue Lhomond, room L367 | ||
==== Schedule with notes and tutorials ==== | |||
[https://docs.google.com/spreadsheets/d/e/2PACX-1vS0bnp7cPVTnbxd77_y-QRiuMzLGKq7DOIKsI-LpoXZvOk43ykDL_glD6RlPd9ubz-9RL12Xh_a9igE/pubhtml?gid=245193379&single=true&widget=true&headers=false Schedule] | |||
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==== Course description ==== | ==== Course description ==== | ||
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* [http://www.lps.ens.fr/~krauth/index.php/SMAC SMAC W. Krauth Statistical Mechanics: Algorithms and Computations (Oxford: Oxford University Press) (2006)] | * [http://www.lps.ens.fr/~krauth/index.php/SMAC SMAC W. Krauth Statistical Mechanics: Algorithms and Computations (Oxford: Oxford University Press) (2006)] | ||
* Other references are specified in each lectures | * Other references are specified in each lectures | ||
===== Thesis advertisement ===== | ===== Thesis advertisement ===== |
Revision as of 14:42, 4 September 2018
Numerical Physics 2018
This is the official web page of the course, which is part of Master ICFP (International Center for fundamental physics)
Prerequisites
The program language that we use is Python 3. No previous experience in programming is required.
Grading
3 homeworks (30 points) + 1 MCQ (20 point), oral exam (50 points)
Schedule and Location
- Lectures on Fridays: 13.45-15.45
- Tutorials on Fridays: 15.45-17.45
- ENS, 24 rue Lhomond, room L367
Schedule with notes and tutorials
Course description
NumPhysParis is a general course in Computational Physics, with applications in statistical physics, atomic and condensed-matter.
We will cover the many numerical algothims used in modern many-body problems: Monte Carlo (classical and quantum), molecular dynamics, stochastic computation, exact diagonalization, optmization in complex landscapes. Implications to computer science problems 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)
Language
The working language for this course is English.
Programming Language: Python 3.
You need first of all to have Python installed with at least modules NumPy, SciPy and matplotlib.
References
- SMAC W. Krauth Statistical Mechanics: Algorithms and Computations (Oxford: Oxford University Press) (2006)
- Other references are specified in each lectures
Thesis advertisement
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