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JUNO is a multi-purpose neutrino experiment currently under construction in Jiangmen, China. It is primary aiming to determine the neutrino mass ordering. Moreover, its 20\,kt target mass makes it an ideal detector to study neutrinos from…

Instrumentation and Detectors · Physics 2021-02-03 Livia Ludhova , Henning Rebber , Björn Soenke Wonsak , Yu Xu

This paper introduces supervised learning techniques for real-time selection (triggering) of hadronically decaying tau leptons in proton-proton colliders. By implementing classic machine learning decision trees and advanced deep learning…

High Energy Physics - Experiment · Physics 2024-04-23 Maayan Yaary , Uriel Barron , Luis Pascual Domínguez , Boping Chen , Liron Barak , Erez Etzion , Raja Giryes

In complex plasmas, the behavior of freely floating micrometer sized particles is studied. The particles can be directly visualized and recorded by digital video cameras. To analyze the dynamics of single particles, reliable algorithms are…

Plasma Physics · Physics 2018-02-14 Daniel P. Mohr , Christina A. Knapek , Peter Huber , Erich Zaehringer

The thesis arises in the context of deep learning applications to particle physics. The dissertation follows two main parallel streams: the development of hardware-accelerated tools for event simulation in high-energy collider physics, and…

High Energy Physics - Phenomenology · Physics 2023-02-08 Marco Rossi

A particle flow event-reconstruction algorithm has been successfully deployed in the CMS experiment and is nowadays used by most of the analyses. It aims at identifying and reconstructing individually each particle arising from the LHC…

High Energy Physics - Experiment · Physics 2014-02-03 Florian Beaudette

We aimed to evaluate computer-aided diagnosis (CADx) system for lung nodule classification focusing on (i) usefulness of gradient tree boosting (XGBoost) and (ii) effectiveness of parameter optimization using Bayesian optimization (Tree…

Computer Vision and Pattern Recognition · Computer Science 2020-06-02 Mizuho Nishio , Mitsuo Nishizawa , Osamu Sugiyama , Ryosuke Kojima , Masahiro Yakami , Tomohiro Kuroda , Kaori Togashi

The LHC will deliver unexplored energy regimes for proton-proton and heavy-ion collisions. As shown by the RHIC experiments, particle identification over a large momentum range is essential to disentangle physics processes, especially in…

Nuclear Experiment · Physics 2008-11-26 D. Di Bari , A. Mastroserio , L. Molnar , E. Nappi , D. Perrino , G. Volpe

Laser cutting is a widely adopted technology in material processing across various industries, but it generates a significant amount of dust, smoke, and aerosols during operation, posing a risk to both the environment and workers' health.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-21 Mohamed Abdallah Salem , Hamdy Ahmed Ashur , Ahmed Elshinnawy

A new approach to jet-shape identification based on linear regression is discussed. It is designed for searches for new particles at the TeV scale decaying hadronically with strongly collimated jets. We illustrate the method using a Monte…

High Energy Physics - Phenomenology · Physics 2010-12-23 S. Chekanov , C. Levy , J. Proudfoot , R. Yoshida

Mechanical exfoliation of graphene and its identification by optical inspection is one of the milestones in condensed matter physics that sparked the field of 2D materials. Finding regions of interest from the entire sample space and…

Materials Science · Physics 2022-09-19 Woon Hyung Cho , Jiseon Shin , Young Duck Kim , George J. Jung

Power systems are prone to a variety of events (e.g. line trips and generation loss) and real-time identification of such events is crucial in terms of situational awareness, reliability, and security. Using measurements from multiple…

Systems and Control · Electrical Eng. & Systems 2023-01-18 Nima T. Bazargani , Gautam Dasarathy , Lalitha Sankar , Oliver Kosut

In this work we consider the problem of determining the identity of hadrons at high energies based on the topology of their energy depositions in dense matter, along with the time of the interactions. Using GEANT4 simulations of a…

Many Partial Differential Equations (PDEs) do not have analytical solution, and can only be solved by numerical methods. In this context, Physics-Informed Neural Networks (PINN) have become important in the last decades, since it uses a…

Numerical Analysis · Mathematics 2022-11-18 Lawson Oliveira Lima , Julien Rosenberger , Esteban Antier , Frederic Magoules

Decision trees are a widely used method for classification, both by themselves and as the building blocks of multiple different ensemble learning methods. The Max-Cut decision tree involves novel modifications to a standard, baseline model…

Machine Learning · Computer Science 2020-06-26 Jonathan Bodine , Dorit S. Hochbaum

The CALICE Semi-Digital Hadronic CALorimeter (SDHCAL) prototype using Glass Resistive Plate Chambers as a sensitive medium is the first technological prototype of a family of high-granularity calorimeters developed by the CALICE…

We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the…

High Energy Physics - Phenomenology · Physics 2023-04-05 Kyle Lee , James Mulligan , Mateusz Płoskoń , Felix Ringer , Feng Yuan

We have adapted a set of classification algorithms, also known as Machine Learning, to the identification of fluid and gel domains close to the main transition of dipalmitoyl-phosphatidylcholine (DPPC) bilayers. Using atomistic molecular…

Soft Condensed Matter · Physics 2023-07-19 Viven Walter , Céline Ruscher , Olivier Benzerara , Carlos M. Marques , Fabrice Thalmann

Thin film processing by means of sputter deposition inherently depends on the interaction of energetic particles with a target surface and the subsequent particle transport. The length and time scales of the underlying physical phenomena…

Plasma Physics · Physics 2023-06-13 Florian Krüger , Tobias Gergs , Jan Trieschmann

Particle identification is an important feature of the future SPD experiment at the NICA collider. In particular, identification of particles with momenta up to a few GeV/c by their time-of-flight will facilitate reconstruction of events of…

High Energy Physics - Experiment · Physics 2023-05-09 Semyon Yurchenko , Mikhail Zhabitsky

A novel technique to identify and split clusters created by multiple charged particles in the ATLAS pixel detector using a set of artificial neural networks is presented. Such merged clusters are a common feature of tracks originating from…

High Energy Physics - Experiment · Physics 2014-09-23 ATLAS collaboration