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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)

Additional stuff