Related papers: Antimatter Annihilation Vertex Reconstruction with…
The ALPHA-g experiment at CERN aims to perform the first-ever direct measurement of the effect of gravity on antimatter, determining its weight to within 1% precision. This measurement requires an accurate prediction of the vertical…
Antihydrogen is at the forefront of antimatter research at the CERN Antiproton Decelerator. Experiments aiming to test the fundamental CPT symmetry and antigravity effects require the efficient detection of antihydrogen annihilation events,…
The gravitational interaction of antimatter and matter has never been directly probed. ALPHA-g is a novel experiment that aims to perform the first measurement of the antihydrogen gravitational mass. A fundamental requirement for this new…
Liquid argon time projection chambers are often used in neutrino physics and dark-matter searches because of their high spatial resolution. The images generated by these detectors are extremely sparse, as the energy values detected by most…
Transverse position reconstruction in a Time Projection Chamber (TPC) is crucial for accurate particle tracking and classification, and is typically accomplished using machine learning techniques. However, these methods often exhibit biases…
A study of antiproton-nucleus annihilations at rest on a variety of thin solid targets using slow extracted antiprotons is being prepared. To detect the charged annihilation products, the experiment will employ seven Timepix4 ASICs coupled…
A deep learning method for the particle trajectory reconstruction with the DAMPE experiment is presented. The developed algorithms constitute the first fully machine-learned track reconstruction pipeline for space astroparticle missions.…
The purpose of this work is to examine the application of a deep learning model in event reconstruction of neutrino interactions. The challenges faced in event reconstruction include the placement of an accurate primary neutrino interaction…
Spectroscopy of antihydrogen has the potential to yield high-precision tests of the CPT theorem and shed light on the matter-antimatter imbalance in the Universe. The ALPHA antihydrogen trap at CERN's Antiproton Decelerator aims to prepare…
The PANDA (anti-Proton ANnihilation at DArmstadt) experiment at the Facility for Anti-proton and Ion Research is going to study strong interactions at the scale at which quarks are confined to form hadrons. A continuous beam of antiproton,…
This paper presents a graph neural network (GNN) technique for low-level reconstruction of neutrino interactions in a Liquid Argon Time Projection Chamber (LArTPC). GNNs are still a relatively novel technique, and have shown great promise…
Recent inroads in Computer Vision (CV) and Machine Learning (ML) have motivated a new approach to the analysis of particle imaging detector data. Unlike previous efforts which tackled isolated CV tasks, this paper introduces an end-to-end,…
In high-energy particle collisions, the reconstruction of secondary vertices from heavy-flavour hadron decays is crucial for identifying and studying jets initiated by $b$- or $c$-quarks. Traditional methods, while effective, require…
We develop and validate a new algorithm called \textit{primary track recovery} (\ptr) that effectively deconvolves known physics and detector effects from nuclear recoil tracks in gas time projection chambers (TPCs) with high-resolution…
We describe a method of reconstructing air showers induced by cosmic rays using deep learning techniques. We simulate an observatory consisting of ground-based particle detectors with fixed locations on a regular grid. The detector's…
Particle identification (PID) is essential for future particle physics experiments such as the Circular Electron-Positron Collider and the Future Circular Collider. A high-granularity Time Projection Chamber (TPC) not only provides precise…
Physical field reconstruction is highly desirable for the measurement and control of engineering systems. The reconstruction of the temperature field from limited observation plays a crucial role in thermal management for electronic…
In modern nuclear physics experiments, identifying events of interest is challenging for nuclear reaction studies with the active target Time Projection Chamber (TPC). In this work, machine learning techniques are employed to analyze the…
The task of reconstructing particles from low-level detector response data to predict the set of final state particles in collision events represents a set-to-set prediction task requiring the use of multiple features and their correlations…
The General AntiParticle Spectrometer (GAPS) is an Antarctic balloon-borne detector designed to measure low-energy cosmic antinuclei (< 0.25 GeV/n), with a specific focus on antideuterons, as a distinctive signal from dark matter…