Instructor: Simon DeDeo

Modeling complex systems is understandably difficult. One can incorporate too little detail and miss insights, or more frequently include too much and render the model fuzzy and meaningless. Complexity Explorer's newest tutorial offers a tool that can provide clarity in choosing modeling elements - renormalization. 

The Introduction to Renormalization tutorial is a survey of algorithm compression techniques and their uses. While typically reserved for statistical physics, Dr. DeDeo applies the techniques to information and file formatting, complex scaling problems and human decision making scenarios. Students will learn what details can scale, which can be simplified and why it matters. 



  1. Introduction to Renormalization
  2. Markov Chains
  3. Cellular Automata
  4. Ising Model
  5. Krohn-Rhodes Theorem
  6. A Classical Analogy for Renormalization in Quantum Electrodynamics
  7. Conclusion: The Future of Renormalization & Rate Distortion Theory
  8. Homework