The course is aimed at students of the 4th and 5th year of the master's degree (laurea magistrale). A basic knowledge of the C or C++ programming language is very welcome for Module B.
Programma del corso
The course consists of two modules. The first (Module A) focuses on particle physics and on physics underlying the functioning of particle detectors. The second (Module B) covers general aspects of data analysis in experimental high energy physics with simplified but realistic examples of physics measurements.
Module A (20 hours)
Cross section and mean free path. Surface Density Units. Energy loss of heavy charged particles by atomic collisions and the Bethe-Bloch formula. Minimum ionizing particles. Energy loss distribution (Landau distribution). Range of charged particles in matter. Cherenkov radiation and energy loss of electrons and positrons. Energy loss by radiation: bremsstrahlung. Critical energy and radiation Length. Range of electrons. Multiple scattering. The interaction of photons in matter: photoelectric effect, Compton scattering, pair production. Strong interactions of hadrons. Drift and diffusion in gases and Lorentz angle. Basic working principles of track detectors: multiwire proportional chambers, drift chambers and semiconductor track detectors. Calorimetry. Particle Identification: time-of-flight counters and identification by ionisation processes, and by using Cherenkov radiation. Momentum measurement and high precision tracking.
Module B (20 hours)
Fundamentals of probability and statistics for basic applications to data analysis in experimental particle physics: handling histograms and performing simple fits to data. A brief introduction on ROOT: an open-source data analysis framework used in high energy physics. Presentation of simplified but realistic physics measurements (branching ratio, lifetime, asymmetry, mixing and oscillations, search for rare signals) to be performed by analysing simulated data.
William R. Leo, Techniques for Nuclear and Particle Physics Experiments (Springer).
Glen Cowan, Statistical Data Analysis (Oxford).
Blum, Rolandi: Particle Detection with Drift Chambers (Springer).