Course Identification

Information Theory
20241182

Lecturers and Teaching Assistants

Prof. Gregory Falkovich, Prof. Massimo Vergassola
Gadi Trocki Reibstein

Course Schedule and Location

2024
Second Semester
Tuesday, 11:15 - 13:00, Weissman, Seminar Rm A
Wednesday, 14:15 - 16:00, Weissman, Seminar Rm A

Tutorials
Tuesday, 14:00 - 15:00,
09/04/2024
10/07/2024

Field of Study, Course Type and Credit Points

Physical Sciences: 3.00 points
Chemical Sciences: Lecture; Elective; Regular; 3.00 points

Comments

This course will be held by frontal learning only
The tutorials will take place at Drori.

17.04-FGS room A
03.07-FGS room A

Additional sessions will be held on the following days:

1- Thursday, 18.04.24- 11:00-13:00- Physics Seminar Room B
2- Thursday, 23.05.24- 11:00-13:00- Physics Seminar Room B
3- Monday, 10.06.24- 14:00-16:00- Physics Seminar Room B

Prerequisites

Elementary statistical physics.

Restrictions

60

Language of Instruction

English

Attendance and participation

Obligatory

Grade Type

Numerical (out of 100)

Grade Breakdown (in %)

50%
50%

Evaluation Type

Take-home exam

Scheduled date 1

N/A
N/A
-
N/A

Estimated Weekly Independent Workload (in hours)

4

Syllabus

Syllabus

Brief reminder: Thermodynamics on one foot. Statistical physics on another foot.

Kinetics and Boltzmann equation.

Dynamics of irreversibility: phase space evolution, Lyapunov exponents, and mixing.

Statistical physics as information theory. The triviality of the second law of thermodynamics.

Mutual information, measurements as communications, data compression.

Renormalization group – the right way to forget information.

Applications to biology and brain research.

Quantum information.

Learning Outcomes

Familiarity with the main tools of modern information theory as applied in physics, biology and engineering.

Reading List

N/A

Website

N/A