Analysis of the clustering algorithm of the micro strip detector in the FOOT experiment

Hadrontherapy is a medical treatment which employs high energy beams of charged particles to treat deep tumours in the body. The particular depth-dose profile is characterized by the release of the dose almost near the path end of the particle: the Bragg peak. This minimize the damage to surrounding healthy tissue. However, nuclear interactions can occur between the particle beam and the human body generating beam fragments releasing dose beyond the Bragg peak and target fragments which release dose in healthy tissue. The lack of experimental cross section data is a problem in order to study the effects of these interactions. These effects are a important also for radioprotection in space: long-term space missions are going to be planned in next years and risks on space radiation exposure for astronauts and electronics need to be studied. To fill these gaps in data, the FOOT (FragmentatiOn Of Target) experiment was proposed with the aim of measure double differential cross sections both in angle and kinetic energy with an uncertainty lower than 5\%. In order to do that, it is composed by different sub detectors to detect, track and identify charged fragments produced in charged particle beam collisions with different targets. In this thesis, one of the subdetector of FOOT is analyzed: the Micro Strip Detector (MSD). In particular, an analysis of the clustering algorithm is made to reduce the signal loss between readout strips: a first part dedicated to software changes and a second part focused on the application of the eta correction. The analysis is performed with data from GSI 2021 campaign of 16O at 400 MeV/u and from CNAO 2022 campaign of 12C at 200-300 MeV/u.