- Time and location: MW 2:30-3:45 pm, PS 121
- Instructor: Alexander Khanov
- No formal textbook is required. Course work will be based on materials provided by instructor.

Particle detector techniques | |
---|---|

Particles: overview |
Lecture 1 Lecture 2 |

Methods of particle detection | Lecture 3 |

Passage of particles through matter |
Lecture 4 Lecture 5 Lecture 6 |

Detector types |
Lecture 7 Lecture 8 Lecture 9 |

Mathematical methods for data analysis | |

Error analysis: probability distributions, statistical and systematic uncertainties, error propagation |
Lecture 1 Lecture 2 Lecture 3 Lecture 4 |

Statistics: fitting, likelihood, parameter estimation, Bayesian vs frequentist approach, confidence level |
Lecture 5 Lecture 6 Lecture 7 Lecture 8 Lecture 9 |

Numerical solutions: integration, differentiation, roots |
Lecture 1 Lecture 2 |

Random numbers and Monte Carlo techniques |
Lecture 3 Lecture 4 Lecture 5 Lecture 6 |

Review of modern HEP detectors | |

Tevatron and LHC experiments |
CDF+D0 ATLAS+CMS |

Other HEP experiments and techniques |
Neutrino Acelerators Dark Matter |

- Homework 1, due 9/13
- Homework 2, due 9/20
- Homework 3, due 9/27
- Homework 4, due 10/18
- Homework 5, due 11/2
- Homework 6, due 11/8

Final project presentations

Alexander Khanov