LEARNING OUTCOMES

The student will acquire the necessary knowledge for understanding the study of physics of the fundamental interactions at collider experiments, for interpreting the collected data in terms of physics measurements, and for steering herself/himself on the possible future experiments and research outputs.

AIMS AND LEARNING OUTCOMES

The course aims to provide the conceptual, theoretical and methodological tools for a clear understanding of the experimental results in fundamental interactions physics, with particular emphasis on those produced by the experiments operating at colliders. To achieve this goal, students will learn how to use the collected data to reconstruct and identify the particles produced in the collisions, and how to combine this information to investigate the content of data in terms of physics observables.
At the end of the course, the student will be able to:

• qualitatively design a hypothetical project for an accelerator and corresponding experimental apparatus for the study of various categories of processes;
• understand and critically analyze a generic scientific paper concerning experimental particle physics (in particular those concerning collider physics);
• independently develop each step of a data analysis producing a new physical result, from the characterization of the adopted tools, to the statistical treatment of the results and their comparison with theoretical predictions (preliminary work for any Master's thesis work in the field).

PREREQUISITES

The following prerequisites on the knowledge of particle physics and statistical treatment of data are required to effectively acquire the key teaching contents of this course:

• basic understanding of the key elements of the Standard Model, including: particle classification, composition of hadrons according to the quark model, electroweak interactions and their mediators;
• description of the interactions between elementary particles through Feynman diagrams and their use to qualitatively estimate their properties;
• interaction of radiation with matter;
• estimation of the different possible errors on a measurement and related propagation techniques;
• fundamentals of programming languages commonly used in physics experiments at colliders (e.g. C ++, Python).

If deemed useful or necessary, the course will feature a summary of the contents, among those listed above, which have not been covered by previous compulsory courses.

TEACHING METHODS

The course is mainly based on lectures and specific activities, in the form of a short series of seminars on selected topics. Attending lectures and seminars is strongly recommended.
Lectures are carried out with the help of multimedia presentations and the use of the blackboard.
Computer-based practice exercises will also be proposed, focussing on the reconstruction of data and the consequent analysis of physics processes at colliders, using simulated data and data recorded by the real experiments. Attending the practice exercises is compulsory in order to take the exam.

SYLLABUS/CONTENT

Key characteristics of a physics experiment of fundamental interactions at colliders.
Introduction to the most common types of experimental measurements: cross sections, angular distributions, lifetimes, oscillation phenomena.
Collider design elements, depending on the phenomena under study, with a brief discussion of tracking systems, calorimetry, particle identification, and real-time selections (trigger).
Reconstruction of physics observables in the products of a collision, definition and measurement of the final state.
Real-data calibration techniques for reconstruction and analysis tools.
Interpretation of data collected in terms of physics measurements.
Non-ideality of the analysis process: characterization of reconstruction and identification efficiency, presence of false candidates (fakes) and estimation of the resolution for reconstructed observables.
Experimental methods to obtain a reliable estimate of physical and instrumental backgrounds: studies based on simulations or on real data (data-driven techniques), definition of control regions and control samples.
Statistical interpretation of the results obtained: treatment of statistical and systematic errors, measurement processes or limit setting, unfolding techniques.
Techniques for the optimization of scientific results, for example in terms of signal-to-background maximization: traditional and innovative approaches, from the application of cuts on individual observables to the use of machine learning techniques.
Examples of key measurements in the Standard Model: CP violation, asymptotic freedom of QCD, spontaneous symmetry breaking through the Higgs mechanism.
Development of searches for physical phenomena not foreseen by the Standard Model, both in terms of data analysis and in terms of designing future accelerators and detectors.
Practical exercises on relevant measurements in the field, based on the analysis of simulated and real data.

RECOMMENDED READING/BIBLIOGRAPHY

The slides used for the lectures will be available on AulaWeb by the end of each cycle of lessons, together with any further information and other bibliographic material, all provided in PDF format.
The guidelines for the practical exercises will be provided, again on AulaWeb and in PDF format, reasonably in advance with respect to the preparation of the exercises themselves.
In addition, the following list of textbooks is provided, to be intended as supporting material for more in-depth studies. The textbooks are available at the M.F.N. library.

• C. Grupen, B. Schwartz - Particle Detectors, 2nd ed., Cambridge University Press - 2008
• D. Griffith - Introduction to Elementary Particles, 2nd, Revised Edition, J. Wiley - 2008
• G. Bohm, G. Zech - Introduction to Statistics and Data Analysis for Physicists, DESY - 2010
• F. Halzen, A. Martin - Quarks and leptons, J. Wiley - 1984
• S. Braibant, G. Giacomelli, M. Spurio - Particles and fundamental interactions, Springer - 2009
• Particle Data Group - Particle detectors at accelerators - 2017