Abstract: A search for flavour-changing neutral interactions involving the top quark, the Higgs boson and an up-type quark q ( q = c, u) is presented. The proton-proton collision data set used, with an integrated luminosity of 139 fb(-1), was collected at root s = 13TeV by the ATLAS experiment at the Large Hadron Collider. Both the decay process t -> qH in tt production and the production process pp. tH, with the Higgs boson decaying into two photons, are investigated. No significant excess is observed and upper limits are set on the t. cH and the t. uH branching ratios of 4.3x10(-4) and 3.8x10(-4), respectively, at the 95% confidence level, while the expected limits in the absence of signal are 4.7x10(-4) and 3.9x10(-4). Combining this search with ATLAS searches in the H. t+ t- and H. b <overline> b final states yields observed (expected) upper limits on the t -> cH branching ratio of 5.8 x 10(-4) (3.0 x 10(-4)) at the 95% confidence level. The corresponding observed (expected) upper limit on the t -> uH branching ratio is 4.0 x 10(-4) (2.4 x 10(-4)).

Abstract: Silicon Photomultipliers find applications across various fields. One potential Silicon Photomultiplier application domain is neutrino telescopes, where they may enhance the angular resolution. However, the elevated dark count rate associated with Silicon Photomultipliers represents a significant challenge to their widespread utilization. To address this issue, it is proposed to use Silicon Photomultipliers and Photomultiplier Tubes together. The Photomultiplier Tube signals serve as a trigger to mitigate the dark count rate, thereby preventing undue saturation of the available bandwidth. This paper presents an investigation into a fast and resource-efficient method for filtering the Silicon Photomultiplier dark count rate. A low-resource and fast coincident filter has been developed, which removes the Silicon Photomultiplier dark count rate by using as a trigger the Photomultiplier Tube input signals. The architecture of the coincidence filter, together with the first results obtained, which validate the effectiveness of this method, is presented.

Abstract: We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method, called Gradient-Annihilated PINNs (GA-PINNs), introduces a modified loss function that forces the model to partially ignore high-gradients in the physical variables, achieved by introducing a suitable weighting function. The method relies on a set of hyperparameters that control how gradients are treated in the physical loss. The performance of our methodology is demonstrated by solving Riemann problems in special relativistic hydrodynamics, extending earlier studies with PINNs in the context of the classical Euler equations. The solutions obtained with the GA-PINN model correctly describe the propagation speeds of discontinuities and sharply capture the associated jumps. We use the relative l(2) error to compare our results with the exact solution of special relativistic Riemann problems, used as the reference ''ground truth'', and with the corresponding error obtained with a second-order, central, shock-capturing scheme. In all problems investigated, the accuracy reached by the GA-PINN model is comparable to that obtained with a shock-capturing scheme, achieving a performance superior to that of the baseline PINN algorithm in general. An additional benefit worth stressing is that our PINN-based approach sidesteps the costly recovery of the primitive variables from the state vector of conserved variables, a well-known drawback of grid-based solutions of the relativistic hydrodynamics equations. Due to its inherent generality and its ability to handle steep gradients, the GA-PINN methodology discussed in this paper could be a valuable tool to model relativistic flows in astrophysics and particle physics, characterized by the prevalence of discontinuous solutions.

Abstract: The response of pions and protons in the energy range of 20-180 GeV, produced at CERN's SPS H8 test-beam line in the ATLAS iron-scintillator Tile hadron calorimeter, has been measured. The test-beam configuration allowed the measurement of the longitudinal shower development for pions and protons up to 20 nuclear interaction lengths. It was found that pions penetrate deeper in the calorimeter than protons. However, protons induce showers that are wider laterally to the direction of the impinging particle. Including the measured total energy response, the pion-to-proton energy ratio and the resolution, all observations are consistent with a higher electromagnetic energy fraction in pion-induced showers. The data are compared with GEANT4 simulations using several hadronic physics lists. The measured longitudinal shower profiles are described by an analytical shower parametrization within an accuracy of 5-10%. The amount of energy leaking out behind the calorimeter is determined and parametrized as a function of the beam energy and the calorimeter depth. This allows for a leakage correction of test-beam results in the standard projective geometry.

Abstract: In the harsh environment of the Large Hadron Collider at CERN (design luminosity of 10(34) cm(-2) s(-1)) efficient reconstruction of vertices is crucial for many physics analyses. Described in this paper is the expected performance of the vertex reconstruction used in the ATLAS experiment. The algorithms for the reconstruction of primary and secondary vertices as well as for finding photon conversions and vertex reconstruction in jets are described. The implementation of vertex algorithms which follows a very modular design based on object-oriented C++ is presented. A user-friendly concept allows event reconstruction and physics analyses to compare and optimize their choice among different vertex reconstruction strategies. The performance of implemented algorithms has been studied on a variety of Monte Carlo samples and results are presented.