Graph neural network for track reconstruction in space experiments

Development of tracking algorithm with deep learning techniques A range of models inspired by computer vision applications were investigated, which operated on data from tracking detectors in a format resembling images [A deep learning method for the trajectory reconstruction of cosmic rays with the DAMPE mission, Andrii Tykhonov et al,Astroparticle Physics 146, April 2023, 102795 102795]. Although these approaches demonstrated potential, image-based methods encountered difficulties in adapting to the scale of realistic data, primarily due to the high dimensionality and sparsity of the data. Tracking data are naturally represented as graph by identifying hits as nodes and tracks segments as (in general) directed edges. So that, we have explored the use of geometric deep learning techniques. Specifically, we have developed an algorithm that leverages the Graph Neural Network approach, which is a subset of geometric deep learning. This approach has been applied to the task of track reconstruction in a simplified model of space experiments. The details of our toy model simulations, the algorithm's development process, and the preliminary results are described in the accompanying slides

The Tracking performance for the IDEA drift chamber

The IDEA detector concept for a future e$^{+}$e$^{-}$ collider adopts an ultra-low mass drift chamber as a central tracking system. The He-based ultra-low mass drift chamber is designed to provide efficient tracking, a high-precision momentum measurement, and excellent particle identification by exploiting the cluster counting technique. This paper describes the expected tracking performance, obtained with full and fast simulation, for track reconstruction on detailed simulated physics events. Moreover, the details of the construction parameters of the drift chamber, including the inspection of new material for the wires, new techniques for soldering the wires, the development of an improved schema for the drift cell, and the choice of a gas mixture, will be described

Kidney transplantation in systemic sclerosis: Advances in graft, disease, and patient outcome

Systemic sclerosis (SSc) is an immune-mediated rheumatic disease characterized by vascular abnormalities, tissue fibrosis, and inflammation. Renal disease occurring in patients with SSc may have a variable clinicopathological picture. However, the most specific renal condition associated with this disease is the scleroderma renal crisis (SRC), characterized by acute onset of renal failure and severe hypertension. SRC develops in about 20% of cases of SSc, especially in those patients with diffuse cutaneous disease. The prognosis of this condition is often negative, with a rapid progression to end-stage renal disease (ESRD). The advent of the antihypertensive angiotensin-converting enzyme inhibitors in 1980 was associated with a significant improvement in patients’ survival and recovery of renal function. However, the prognosis of these patients can still be improved. The dialytic condition is associated with early death, and mortality is significantly higher than among patients undergoing renal replacement therapy (RRT) due to other conditions. Patients with SRC who show no signs of renal functional recovery despite timely blood pressure control are candidates for kidney transplantation (KT). In this review, we reported the most recent advances in KT in patients with ESRD due to SSc, with a particular overview of the risk of disease recurrence after transplantation and the evolution of other disease manifestations

Particle identification with the cluster counting technique for the IDEA drift chamber

IDEA (Innovative Detector for an Electron-positron Accelerator) is a general-purpose detector concept, designed to study electron-positron collisions in a wide energy range from a very large circular leptonic collider. Its drift chamber is designed to provide an efficient tracking, a high precision momentum measurement and an excellent particle identification by exploiting the application of the cluster counting technique. To investigate the potential of the cluster counting techniques on physics events, a simulation of the ionization clusters generation is needed, therefore we developed an algorithm which can use the energy deposit information provided by Geant4 toolkit to reproduce, in a fast and convenient way, the clusters number distribution and the cluster size distribution. The results obtained confirm that the cluster counting technique allows to reach a resolution 2 times better than the traditional dE/dx method. A beam test has been performed during November 2021 at CERN on the H8 to validate the simulations results, to define the limiting effects for a fully efficient cluster counting and to count the number of electron clusters released by an ionizing track at a fixed $\beta\gamma$ as a function of the track angle. The simulation and the beam test results will be described briefly in this issue.Comment: 2 pages, 4 figures, Proceedings of: PM202

Artificial intelligence for tracking in space experiments

This is the slides presented at the spoke3 general meeting about the developent of AI tracking algorithm for space experiment. We discussed a novel GNN approach for particle reconstruction in space experiments. Specifically, by using the Geant4 toolkit, we simulated the response of 4 scintillating fiber tracking layers, aiming to mimic the setup employed during a beam test at CERN, which utilized a 10 GeV/c negative pion beam. Our approach involves training and evaluating different node-classifying GNN algorithms to distinguish between noise and signal hits in the simulated detector data. These GNN algorithms utilize techniques such as message passing and graph convolution to iteratively aggregate information from neighboring hits and learn discriminative features for classification tasks. We compared the performances of these GNN algorithms with those of traditional analytical tracking approaches, highlighting the advantages of leveraging deep learning techniques for particle reconstruction in space experiments

A proposal of a He based Drift Chamber as central tracker for the IDEA detector concept for a future e+e- collider

none10noThe IDEA detector concept for a future e+e− collider adopts an ultra-low mass drift chamber as the central tracking system. It is a He based, 4 m long and 4 m diameter, fully stereo drift chamber with a total material budget of ∼0.016X0 in the barrel part and ∼0.05X0 in the end-caps. It will be instrumented with a readout electronics implementing the Cluster Counting/Timing techniques, allowing for a larger than 3 σ π/κ separation over most of the momentum range of interest.restrictedCuna, Federica; chiarello, gianluigi; Corvaglia, Alessandro; Filippis, Nicola De; Gorini, Edoardo; Grancagnolo, Francesco; Miccoli, Alessandro; Primavera, Margherita; Tassielli, Giovanni Francesco; Ventura, AndreaCuna, Federica; Chiarello, Gianluigi; Corvaglia, Alessandro; Filippis, Nicola De; Gorini, Edoardo; Grancagnolo, Francesco; Miccoli, Alessandro; Primavera, Margherita; Tassielli, Giovanni Francesco; Ventura, Andre

Molecular and functional bases of self-antigen recognition in long-term persistent melanocyte-specific CD8+ T cells in one vitiligo patient

Vitiligo patients possess high frequencies of circulating CD8(+) T lymphocytes specific for the melanocyte differentiation antigen Melan-A/MART-1. These self-specific T cells exhibit intact functional properties and their T cell receptors are selected for a narrow range of high affinities of antigen recognition, suggesting their important role in the pathogenesis of vitiligo. In order to understand the molecular base for this unexpected, optimal T cell receptor recognition of a self-antigen, a tetramer-guided ex vivo analysis of the T cell receptor repertoire specific for the Melan-A antigen in a patient affected by vitiligo is reported. All T cell receptors sequenced corresponded to different clonotypes, excluding extensive clonal expansions and revealing a large repertoire of circulating Melan-A-specific T lymphocytes. A certain degree of T cell receptor structural conservation was noticed, however, as a single AV segment contributed to the alpha chain rearrangement in 100% of clones and a conserved amino acid sequence was found in the beta chain complementarity determining region 3 of various high affinity cells. We suggest that the conserved alpha chain confers self-antigen recognition, necessary for intrathymic selection and peripheral homeostasis, to many synonymous T cell receptors, whereas the beta chain fine tunes the T cell receptor affinity of the specific cells. In addition, we demonstrate that many high avidity T cell clones from this patient were capable of specifically lysing normal, HLA-matched melanocytes. These autoreactive clones persisted for more than 3 y in the patient's peripheral blood. These data, together with the skin-homing potential of the clones, directly point to the in vivo pathogenic role of melanocyte-specific cytotoxic T lymphocytes in vitiligo