Related papers: Deep learning techniques for energy clustering in …
We present results on the reconstruction of electromagnetic (EM) activity from photons produced in charged current $\nu_{\mu}$ interactions with final state $\pi^0$s. We employ a fully-automated reconstruction chain capable of identifying…
Knowledge of the mass composition of ultra-high-energy cosmic rays is crucial to understanding their origins; however, current approaches have limited event-by-event resolution. With fluorescence telescope measurements of the longitudinal…
An innovative path for the detectors at future colliders to achieve higher performances is to use a Particle Flow approach, which requires highly granular calorimeters to image individual showers. The silicon-tungsten electromagnetic…
The increase in demand for scalable and energy efficient artificial neural networks has put the focus on novel hardware solutions. Integrated photonics offers a compact, parallel and ultra-fast information processing platform, specially…
High granularity calorimeters have become increasingly crucial in modern particle physics experiments, and their importance is set to grow even further in the future. The CLUstering of Energy (CLUE) algorithm has shown excellent performance…
Experimental High-Energy Physics (HEP), especially the Large Hadron Collider (LHC) programme at the European Organization for Nuclear Research (CERN), is one of the most computationally intensive activities in the world. This demand is set…
This article presents the reconstruction of the electromagnetic activity from electrons and photons (showers) used in the MicroBooNE deep learning-based low energy electron search. The reconstruction algorithm uses a combination of…
A novel combination of data analysis techniques is proposed for the reconstruction of all tracks of primary charged particles, as well as of daughters of displaced vertices (decays, photon conversions, nuclear interactions), created in high…
Photons emitted from high-energy electron beam interactions with high-field systems, such as the upcoming FACET-II experiments at SLAC National Accelerator Laboratory, may provide deep insight into the electron beam's underlying dynamics at…
We address the identification of grain-corresponding Laue reflections in energy dispersive Laue diffraction (EDLD) experiments by formulating it as a clustering problem solvable through unsupervised machine learning (ML). To achieve…
The Belle II experiment is presently in phase-2 operation at the SuperKEKB electron-positron collider in KEK (Tsukuba, Japan). The detector is an upgrade of the Belle experiment at the KEKB collider and it is optimized for the study of rare…
A ubiquitous approach to obtain transferable machine learning-based models of potential energy surfaces for atomistic systems is to decompose the total energy into a sum of local atom-centred contributions. However, in many systems…
Algorithms based on the particle flow approach are becoming increasingly utilized in collider experiments due to their superior jet energy and missing energy resolution compared to the traditional calorimeter-based measurements. Such…
Calorimeters operating in high-radiation environments are susceptible to damage, leading to increased noise that can significantly degrade energy resolution. A common way to mitigate noise is to apply a higher energy threshold on the cells,…
This note discusses methods of particle reconstruction in the forward region detectors of future e+e- linear colliders such as ILC or CLIC. At the nominal luminosity the innermost electromagnetic calorimeters undergo high particle fluxes…
This paper addresses poor cluster formation and frequent Cluster Head (CH) failure issues of underwater sensor networks by proposing an energy-efficient hierarchical topology-aware clustering routing (EEHTAC) protocol. In this paper,…
Clustering is one of the most frequent problems in many domains, in particular, in particle physics where jet reconstruction is central in experimental analyses. Jet clustering at the CERN's Large Hadron Collider (LHC) is computationally…
A high-energy e+e- collider, such as the ILC or CLIC, is arguably the best option to complement and extend the LHC physics programme. A lepton collider will allow for exploration of Standard Model Physics, such as precise measurements of…
The precise measurement of photon or electron impact position is the prerequisite to reconstruct the origin of two photons events from decay of {\pi}0 and {\eta} mesons or the di-electron channel from quarkonia decay. To facilitate such a…
We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predicting cluster assignments or object-centric variables, the method learns a latent representation in…