ICFP Stat Physics 2017 infos
From Werner KRAUTH
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'''Further infos for the ICFP course''' | '''Further infos for the ICFP course''' |
Revision as of 09:19, 30 August 2017
Go back to ICFP Statistical Physics main page
Further infos for the ICFP course
Contents |
Title of the course
Statistical Physics: Concepts and applications
Scope of the course
This lecture course on statistical mechanics will take students from the foundations of probability theory and statistical inference to the important models and the central concepts and techniques of statistical mechanics. The main focus will be on equilibrium and on classical systems, but we will also treat transport and dissipation, and discuss quantum statistical mechanics for Boson systems and quantum spin models.
Organization, grading
There will be 15 lectures and tutorial sessions, 8 graded homeworks (50% of the grade), and a written final exam (50%, also).
Planning
Lectures (CM) and tutorials (TD): Each Monday morning, from 4 September 2017 through 11 December 2017 (Lectures: 8:30 - 9:25 am, 9:35 - 10:30 am; tutorials: 10:45 - 11:40 am, 11:50 am - 12:45 pm).
Final exam: Wednesday, XXX 2017 9:00 - 12:00 in room L357/359, third floor of 24 rue Lhomond.
For your information, you can study here the exam I gave to the 2015/16 class. Subjects of this exam were: Basic statistics: MLE (Gaussians, German tank problem), Correlation lengths, Bose-Einstein condensation, and Jamming. See for yourself!
Localization
The course will take place at the Physics Department of Ecole normale supérieure, 24 rue Lhomond, 75005 Paris. Lectures: room L357/359, third floor Tutorials: room L357/359 and L369, both third floor Tutorial 16 november 2016: room L357/359 and L361, both third floor
Prerequisites
This course will be self-contained. Some prior exposure to elementary statistical or thermal physics on the undergraduate level may be helpful.
Computing requirements
Probability, statistics, and statistical physics are today closely linked to computing. Students should be able to download, run and modify elementary Python programs. Many such programs will be provided, and some will have to be written for the homework sessions.