# MA933 - OLD Module Resources 2014

Lecturer: Stefan Grosskinsky (email)

TA: Mike Maitland (email)

Lectures: Tue 11-1 and Fri 10-12 in D1.07

Classes: Tue 2-4 and Fri 2-4 in D1.07

## Assessment

• Written class test (about 1.5 hours) on Tue 28.10. at 2pm in D1.07, counts 25/100.
No books allowed, please only come with writing material and have your student ID number ready to put on the exam booklet.
• Viva/oral examination on Fri 31.10. in B1.12, 20 minutes per student, counts 50/100.
Current viva timetable, and list of topics for viva and class test.
• homework counts 25/100 marks

## Notes

• regularly updated version of the course notes: notes_ma933.pdf (final version, updated 24.10.)
• the first part of notes for the previous module CO905 Stochastic models of complex systems provide a slightly more complete introduction to Markov chains and might be useful for background reading

## Problem sheets

• NEW: solution to sheet 2 by Jacopo Credi (pdf)
• sheet2: Birth-death chains, contact process, random networks
corrected mistakes in this version:
- Q1.4(c) and 1.5(c) use the adjacency matrix A instead of the graph Laplacian
- Q1.4(b) expression for k_nn (k) corrected
- Q1.4(a) do not measure power law exponent, but compare to the theoretical value -2-k0 /m
• sheet1: Simple random walk, generators and eigenvalues, Toom's model
(sign error in eigenvalues in Q1.3b and c corrected)

## Hand-outs

• hand-out3: random sequential update, Gillespie algorithm
• hand-out2: generating functions, Poisson processes
• hand-out1: linear algebra

## Classes

• classwork_21_10.m: stuff from classes including errorbars and semicircle
• prefattach.m: Matlab file to generate a generalized preferential attachment network
• matrixFun.m: Matlab file for matrix manipulations (produces a lot of output, comment out irrelevant section when running it)
• randomWalk.m: Matlab file for random walk
• contact.zip: zip file with c code and random number generator for the contact process
• er.m: demonstrates giant cluster phase transition in ER networks (written by Thomas House)