ICFP NumPhys Paris: Difference between revisions

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==== Course description ====  
==== Course description ====  


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NumPhysParis is a general course in Computational Physics, with applications in statistical physics, atomic and condensed-matter. <br>
NumPhysParis is a general course in Computational Physics, with applications in statistical physics, atomic and condensed-matter. <br>
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.
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.
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==== Team ====
==== Team ====

Revision as of 11:48, 3 July 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

Course description

<div style="style-align:justify"> NumPhysParis is a general course in Computational Physics, with applications in statistical physics, atomic and condensed-matter. <br> 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. </div>

Team

Language

The working language for this course is English. Programming Language The programming language that we use is Python 3. You need first of all to have Python installed with at least modules NumPy, SciPy and matplotlib.


References

  • W. Krauth Statistical Mechanics: Algorithms and Computations (Oxford: Oxford University Press) (2006), see SMAC
  • Other references are specified in each lectures

Time Schedule

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