E2 334, Spring 2021

Topics in Computation over Networks

Lectures

Homework

Grading Policy

Scribe : 50
Project: 50

Course Syllabus

Content will be a subset of the following topics:

  • Statistical physics:
    • Boltzmann distributions, Thermodynamic potentials and limit, Ferromagnets and Ising models
  • Probability:
    • Stochastic ordering, large deviations, Gibbs free energy, Monte Carlo method, simulated annealing
  • Independence:
    • Random energy model, random code ensemble, number partitioning, replica theory
  • Graph models:
    • Random factor graphs, Random K-SAT, LDPC codes
  • Phase transitions:
    • Erdos Renyi random graph
  • Short-range correlations:
    • Belief propagation, Ising models on random graphs
  • Long range correlations:
    • Cavity method

Course Description

A large number of local microscopic interactions can lead to many interesting macroscopic physical phenomena.
These effects have been observed in physical systems, and statistical physics presents models that can describe such effects.
In this course, we will learn the techniques from statistical physics to describe complex network behaviors.

Prerequisite

First graduate course in probability from any engineering or math department.
Familiarity with information and coding theory is desired, though not necessary to attend the course.

Teams/GitHub Information

Teams

We will use Microsoft Teams for all the course related communication.
Please do not send any email regarding the course.
Students can signup for Microsoft Teams Computation-Networks-2021 using their iisc.ac.in email.
To be on the course team, you have to be formally registered for the course.
If you registered recently and wish to join the course team, please send a direct message on the Teams.

GitHub

All the students in the class have read/write access to Stastistical-Physics public repository on GitHub.
Please follow the guidelines in the sample lecture.
The source file for the sample lecture is in the repository.
It is recommended you save it with another name in your local repository for creating a new lecture.
A good book for Git is here and a simple tutorial here.

Instructor

Parimal Parag
Office: EC 2.17
Hours: By appointment.

Time and Location

Classroom: EC 1.07, Main ECE Building
Hours: Tue/Thu 08:30-10:00am.

References

Textbooks