The need for a microscopic description of scintillation light generation in liquid argon becomes increasingly desirable with the upcoming operation of large scale LArTPCs in the next decade. While a detailed mathematical account of the process is still to be achieved, a phenomenological model for simultaneously treating ionization and scintillation, LArQL, has been successfully employed to describe the range of electric fields from 0 to 0.75 kV/cm and dE/dx from 2 to 40 MeV/cm providing the anti-correlation between the free ionization charge and scintillation light. A reanalysis of the original model parameter values has been performed within a global fit procedure and is presented.

The physics studies at heavy-ion nucleus-nucleus collision experiments demand reliable detectors at high particle flux. Therefore, Gas Electron Multipliers (GEM) detectors, which show resilience to extreme radiation, are one of the prime choices for the upcoming Compressed Baryonic Matter (CBM) experiment at the Facility of Antiproton and Ion Research, Germany. However, operating them under these demanding conditions requires a systemic study at the highest incident particle flux. To this end, we have conducted extensive tests on a real-size triple GEM detector module with the high-intensity gamma flux using the Cs-137 source at the upgraded Gamma Irradiation Facility (GIF++) at Conseil Europ\'een pour la Recherche Nucl\'eaire (CERN). The detector response, particularly regarding the gain and efficiency of muon detection, was studied extensively with and without a gamma source in a free-streaming mode using self-triggered electronics. This configuration will be necessary for the CBM experiment since it will observe unprecedented event rates of about 10 MHz for Au-Au collisions. The analysis reveals an alignment between the expected and observed value of gain and efficiency with an increasing intensity of gamma flux at the operating voltage. The test results demonstrate that the large-size GEM detector prototype can handle elevated gamma rates of approximately 17.25 MHz/cm2 without significantly impacting its performance or suffering irreversible damage.

Radio detection is now an established technique for the study of ultra-high-energy (UHE) cosmic rays with energies above $\sim10^{17}$ eV. The next-generation of radio experiments aims to extend this technique to the observation of UHE earth-skimming neutrinos, which requires the detection of very inclined extensive air showers (EAS). In this article we present a new reconstruction method for the arrival direction and the energy of EAS. It combines a point-source-like description of the radio wavefront with a phenomenological model: the Angular Distribution Function (ADF). The ADF describes the angular distribution of the radio signal amplitude in the 50-200 MHz frequency range, with a particular focus on the Cherenkov angle, a crucial feature of the radio amplitude pattern. The method is applicable to showers with zenith angles larger than $60^\circ$, and in principle up to neutrino-induced showers with up-going trajectories. It is tested here on a simulated data set of EAS induced by cosmic rays. A resolution better than 4 arc-minutes ($0.07^\circ$) is achieved on arrival direction, as well as an intrinsic resolution of 5% on the electromagnetic energy, and around 15% on the primary energy.

Studies of heavy-quark (charm and beauty) production in hadronic and nuclear collisions provide excellent testing grounds for the theory of strong interaction, quantum chromodynamics. Heavy-quarks are produced predominantly in the initial hard partonic interactions, allowing them to witness the entire evolution process. The charm hadrons are produced in two ways. Firstly, the prompt charm hadrons which are formed from the charm quark hadronization which are produced directly from the initial hard-scatterings or the decay of other excited charm states. Secondly, the nonprompt charm hadrons which are produced from the decay of beauty hadrons. The produced charm hadrons then usually decay to light-flavor hadrons or leptons via two or three body decay. The reconstruction of charm hadrons is challenging due to the large combinatorial background as well as the difficulty of distinguishing between prompt and non-prompt charm hadrons. In this work, we use machine learning models--XGboost and Deep Neural Network--to reconstruct $\Lambda_c^{+} (udc)$ hadrons via its three body final state decay channel, $\Lambda_c^{+} \rightarrow pK^0_s$ and $K^0_s \rightarrow \pi^{+}\pi^{-}$. Using several experimentally available features of the decay daughters, these models can separate signal from background and identify prompt and nonprompt candidates with nearly 99\% accuracy. This method performs an unbinned track-level reconstruction since the $\Lambda_c$ candidates are tagged directly from their decay daughters. The necessary data for this study are simulated in pp collisions at $\sqrt{s}=13.6$~TeV using PYTHIA8 (Monash) model.

Studying heavy-flavor jets in pp collision is important since they can test pQCD calculations and be used as a reference for heavy-ion collisions. Jets in this analysis are reconstructed from charged particles using the anti-$k_{\mathrm{T}}$ algorithm with a resolution parameter $R=$ 0.4 and with pseudorapidity $|\eta|<$ 0.5. Beauty jets are tagged using a machine learning model that uses a convolutional neural network trained on information extracted from the jet, tracks, and secondary vertices. The results show that this model is superior compared to other traditional tagging methods.