Introduction to Stochastic Processes


  • Basic Information
    • Instructor : Siva Athreya .
    • Email : athreya@isibang.ac.in or athreya@icts.res.in
    • Scoring : Final Exam: 50%, Midterm Exam: 25%, Homework: 25%.

  • Syllabus:
  • F rom B.Math. (Hons.) III Year students-Brochure
    • DISCRETE-TIME MARKOV CHAINS: Classification of states, Stationary distribution, reversibility and convergence. Random walks and electr ical networks. Collision and recurrence.
    • DISCRETE-TIME MARTINGALES: Optional Stopping theorem, Martingale convergence theorem, Doob’s inequality and convergence.
    • BRANCHING PROCESSES: Model definition. Connection with martingales. Probability of survival. Mean and variance of number of individuals.
    • BASIC PROBABILISTIC INEQUALITIES AND APPLICATIONS: First and Second Moment methods. Applications to Longest increasing subsequences, Random k-Sat problem and connectivity threshold for Erdos-Renyi graphs. Chernoff bounds and Johnson-Lindenstrauss lemma.

  • References and Texts
  • Classes:
  • Day and Time : Wednesday : 2:00-3:00pm, 3:10pm-4:10pm, 4:10pm-5:10pm, 5:10pm-6:10pm at ISI Bangalore Centre

  • Homework:
  • There will be regular Homework assignments given during the course. The problems given there will be a small selection so please do try other problems for practice from the texts. You are encouraged to work together on solving the problems but please write up solutions without consulting anyone else. All Homeworks should be either uploaded onto the respective Moodle platform by 6:30pm on the due date or as mentioned in class.



Week # Notes in Each Week Homework
(Due Dates)
Topics
1 Week-1 Notes
Homework 1
July 30th, 2025.
  • Chapter 1 by [LHdHGVZ] Finite length Random walks
2 Week-2 Notes
Homework 2
August 6th, 2025.
  • Chapter 1 by [LHdHGVZ] Stopping times, Reflection Principle and Last visit to Origin
3 Week-3 Notes:
Random walks,Markov Chains
Homework 3
August 13th, 2025.
  • Chapter 1 by [LHdHGVZ] Last visit to Origin, Infinite Length Random walk
  • Markov Chain: state space, transition matrix and initial distribution.
4 Week-4 Notes Homework 4
August 20th, 2025.
  • Markov Chain: Communicating Classes, periodicity, stationary distribution, hitting times.
5 Week-5 Notes Homework 5
August 28th, 2025.
  • Markov Chain: Hitting times, Recurrence and Transience
6 Week-6 Notes Homework 6
September 3rd, 2025.
  • Markov Chain: Lyapunov Function, Stationary Distribution and Convergence of finite state space Markov Chains.
7 Week-7 Notes Homework 7
September 10th, 2025.
  • Markov Chain: Recurrence for random walk on weighted graphs and general convergence theorem.
Midterm-Solution --
  • Midterm Week
8 Week 8 : Notes Homework 8
September 25th, 2025.
  • First and Second moment method.
  • Chernoff Bounds.
9 Week 9 : Worksheet(s) : Instructions, Worksheet 1, Worksheet 2, Worksheet 3 Homework 9
October 1st, 2025.
  • Reversibility
  • Generate uniformly from a large finite set $S$.
  • Generating a Uniform Spanning tree.
10 Week 10 : Notes Homework 10
October 8th, 2025.
  • Conditional Expectation
  • Tower Property
  • Discrete time Martingales (Section 7.6.1 and Section 7.6.3 of [G])
11 Week 11 : Notes Homework 11
October 15th, 2025.
  • Tower Property
  • Stopping times and Stopped processes. (Section 7.6.4 of [G])
12 Week 12 : Notes Homework 12
October 22nd, 2025.
  • Optional Sampling Theorem
  • Kolmogorov Maximal Inequalities
13 Week 13 : Notes Homework 13
October 29th, 2025.
  • Martingale Convergence Theorem
  • Wald's Identity
14 Week 14 notes Homework 14
  • Monkey Typing "ISP IS BORING"
  • Erdos-Renyi Connectivity Threshold
Last Modified: 24th October, 2025. ISI Courses Page