Monte Carlo Simulations

Module code: 865G1
Level 7 (Masters)
15 credits in spring semester
Teaching method: Lecture
Assessment modes: Dissertation

The module will cover topics including:

  • Introduction to R 
  • Pseudo-random number generation 
  • Generation of random variates 
  • Variance reduction 
  • Markov-chain Monte Carlo and its foundations 
  • How to analyse Monte Carlo simulations 
  • Application to physics: the Ising model 
  • Application to statistics: goodness-of-fit tests

Module learning outcomes

  • Demonstrate advanced knowledge of Monte Carlo methods.
  • Design and create programs for uniform and non-uniform random deviates.
  • Investigate problems by using Markov-chain Monte Carlo simulations.
  • Critically evaluate the output of Markov-chain Monte Carlo simulations.