Instructor: Gasper Tkacik

Teaching Assistants: Anna Andersson, Jan Humplik

The course assumes introductory knowledge of physics, and familiarity with a programming language (Matlab, Mathematica, C, etc) that supports numerical computation. We will cover one topic per week, and have one problem set per week that will require working with real or simulated data (analysis plus some programming); the homework load is substantial. This is a very hands-on course that should provide useful practical experience.

100% grade based on 6 problem sets, 2 weeks time for the completion of each. At each recitation: (i) TAs will help with the currently outstanding homework (from the lecture 1 week back), and (ii) TAs will discuss the results from the homework that was due (from 2 weeks back).

3 ECTS

Date | Topic | Location | Other |
---|---|---|---|

Nov 28 | Correlation functions, spectral estimation, and filtering | Mondi 3 | |

Dec 5 | Random numbers, Gillespie (SSA) simulation | Mondi 3 | |

Dec 12 | Monte Carlo and entropic sampling | Mondi 3 | |

Dec 19 | Working with probability distributions, kernel density estimation, maxent models | Mondi 3 | |

2015 | topics to be announced |

File | Due Date |
---|---|

Homework 1 | |

Homework 2 | |

Homework 3 | |

Homework 4 |

Files (Matlab format) or files (text format), both including relevant chapters from Numerical Recipes.

Chapters from Numerical Recipes.