Markov processes and error analysis (60' lecture)

David Ceperley

Link to Presentation slides (in PDF) format:

Introduction

• Curse of Dimensionality
• What is Monte Carlo?

Random walks/Markov process

• Definition and examples
• Discussion of convergence and ergodicity
• Detailed balance
• Metropolis Monte Carlo and rejection technique
• Example of classical Monte Carlo
• Example of permutation sampling

Error analysis

• Central limit theorem
• Finite variance
• Derivation of fundamental formula for errors
• Practical rules for errors estimation

Comments

prerequisite reading.