Luca Lista – författare

This third edition expands on the original material. Large portions of the text have been reviewed and clarified. More emphasis is devoted to machine learning including more modern concepts and examples. This book provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP).It starts with an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. Following, the author discusses Monte Carlo methods with emphasis on techniques like Markov Chain Monte Carlo, and the combination of measurements, introducing the best linear unbiased estimator. More advanced concepts and applications are gradually presented, including unfolding and regularization procedures, culminating in the chapter devoted to discoveries and upper limits.The reader learns through many applications in HEP where the hypothesis testing plays a major role and calculations of look-elsewhere effect are also presented. Many worked-out examples help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical concepts to actual data.

This book presents the fundamental aspects of classical electrodynamics and special relativity, focusing on the mathematical framework that underpins a coherent theory of electromagnetism. It prioritizes theoretical consistency while summarizing foundational and phenomenological aspects concisely, leaving more detailed discussions to introductory texts. The book provides a set of mathematical tools essential for addressing and solving common problems in the field.It begins with a review of key mathematical techniques, including vector calculus, Green’s theorem, and Dirac delta functions. The discussion then moves to electrostatics, covering Poisson’s equation, Green’s functions, the method of images, and multipole expansions. Solutions to Laplace’s equation are explored in Cartesian, spherical, and cylindrical coordinates, both analytically and numerically. The treatment of electric currents and magnetostatics follows, introducing Ampère’s law, the vector potential, and magnetic multipoles.Maxwell’s equations are then derived and applied to wave propagation, energy and momentum conservation, and gauge transformations. The final sections introduce special relativity, covering Lorentz transformations, four-vectors, and the covariant formulation of electrodynamics, concluding with an introduction to relativistic Lagrangian dynamics.Each chapter includes exercises designed to reinforce students’ understanding. This book is intended for advanced undergraduate and graduate students in physics. Readers are expected to have prior knowledge of algebra and electromagnetism.

This concise set of course-based notes provides the reader with the main concepts and tools to perform statistical analysis of experimental data, in particular in the field of high-energy physics (HEP). First, an introduction to probability theory and basic statistics is given, mainly as reminder from advanced undergraduate studies, yet also in view to clearly distinguish the Frequentist versus Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on upper limits as many applications in HEP concern hypothesis testing, where often the main goal is to provide better and better limits so as to be able to distinguish eventually between competing hypotheses or to rule out some of them altogether. Many worked examples will help newcomers to the field and graduate students to understand the pitfalls in applying theoretical concepts to actual data.