Studente DOMENICHETTI, LORENZO
Facoltà/Dipartimento Dipartimento di Fisica e Astronomia "Galileo Galilei" - DFA
Corso di studio PHYSICS OF DATA Laurea Magistrale (D.M. 270/2004)
Anno Accademico 2021
Titolo originale Advanced tracking techniques for Active Target Time Projection Chamber detectors in Nuclear Physics experiments
Titolo inglese Advanced tracking techniques for Active Target Time Projection Chamber detectors in Nuclear Physics experiments
Abstract in italiano Tracking detectors for low-energy nuclear physics experiments, acting at the same time as reaction targets, are very promising devices in a wide range of research topics. The ability to measure and reconstruct the trajectory of all of the reaction products with high efficiency and good geometrical resolution allows particle spectroscopy studies to be performed under experimental conditions below the sensitivity threshold of standard techniques. This is possible only if solid, efficient, and computationally fast reconstruction codes are implemented and validated. In the presented thesis project, reconstruction codes and classification techniques have been developed aimed at processing experimental data from the ACTAR Active Target. The purpose of such codes was to provide accurate information about track geometry, particle energy, and identification. In particular, the reaction $^{20}$O(d,$^3$He)$^{19}$N$^\star$ has been first analyzed using the Hough transform and RANSAC algorithms, comparing their efficiencies. In the second part, the results obtained applying machine learning techniques on the same data will be presented, with the aim of achieving a fast event classification employing for the first time on ACTAR these cutting-edge techniques.
Parola chiave Nuclear Physics
Tracking algorithms
Active Target
Relatore MARCHI, TOMMASO
Appare nelle tipologie: Lauree magistrali
File in questo prodotto:
File Dimensione Formato  
Domenichetti_Lorenzo_v2.pdf 4.48 MB Adobe PDF Visualizza/Apri

The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12608/35841