ICFP Stat Physics 2016 infos

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'''Lectures''': room '''L357/359''', third floor '''Lectures''': room '''L357/359''', third floor
'''Tutorials''': room '''L357/359''' and '''L369''', both third floor '''Tutorials''': room '''L357/359''' and '''L369''', both third floor
 +'''Tutorial 16 november 2016''': room '''L357/359''' and '''L361''', both third floor
==Prerequisites== ==Prerequisites==

Revision as of 11:35, 16 September 2016

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 Wednesday morning, from 7 September 2016 through 14 December 2016 (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: 22 January 2017 8:30 - 12:30

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 useful.

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.

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