This was my thesis project for my bachelor degree in physics, at the Università degli studi di Padova, during the academic year 2018/2019, under the direction of professor Marco Zanetti. The repository contains the code, written in Python, the results of the data analysis and the thesis file written in Latex.

Abstract:

A re-scaled and revisited version of the CMS drift tubes muon chambers has been designed to be used at beam tests and for tomography applications. A set of chambers of this type have been produced at the INFN Legnaro Laboratory in 2018 and 2019. An important feature of those detectors is their handiness, i.e. they can be arranged to best fit the experimental needs. It is therefore important to develop a reconstruction algorithm flexible enough to address multiple geometrical configurations; at the same time, dedicated suites have to be deployed to allow a fast determination of alignment and calibration constants. Furthermore, the readout of those detectors do not require a trigger signal, i.e. (zero-suppressed) data are continuously sampled from the front-ends. In view of an online analysis running on the unfiltered data, the track reconstruction must be fast, little sensitive to noise and developed with software tools that can best fit in an online environment. The thesis work will focus on the development of algorithms which satisfy the requirements listed above.