Study of cold nuclear matter effects in fixed-target collisions and charged hadron identification performance at the LHCb experiment

The investigation of charged-particle production in hadronic collisions is crucial for under- standing strong interactions governed by Quantum Chromodynamics (QCD). While perturbative QCD effectively describes hard interactions, the soft regime remains less understood. This work presents the measurement of single and double ratios of charged light-hadron production in PbNe and pNe collisions, collected by the LHCb experiment in Run 2 at a centre of mass energy of 69 GeV per nucleon. Significant enhancements have been observed in baryon-meson ratios in PbNe data, suggesting the potential onset of the Cronin Effect for pT > 1 GeV/c. The results are compared with EPOS simulations, revealing substantial differences. These findings can provide inputs for simulation tuning, enhancing the current understanding of Cold Nuclear Matter effects and related QCD phenomena. One of the main challenges of the analysis is related to charged-hadron identification performance, which primarily relies on the LHCb Ring Imaging Cherenkov system. The LHCb upgrade, designed to operate at an instantaneous luminosity in- creased by a factor of five compared to previous data-taking, introduces several enhancements in particle identification performance with upgraded RICH detectors. This improvement can ex- tend the possibilities for fixed-target and heavy-ion measurements at LHCb, allowing for future studies in higher centrality and a broader kinematic region. In this context, the development of calibration tools plays a central role in optimising the performance of the upgraded LHCb detector. A software framework has been developed to comprehensively study the particle identification (PID) performance. The results of charged-hadron identification performance with early Run 3 pp data are presented, and the first study on PID performance for fixed-target and heavy-ion collisions is also included. Despite the excellent early performance of the RICH systems, there is room for optimisation to attain the ultimate PID performance. In this regard, online monitoring of the PID performance curves serves as a crucial metric for fine-tuning RICH detectors across various settings. A dedicated section of this work focuses on projections and the requirements for the implementation of online monitoring for PID performance.