Related papers: Particle identification with the cluster counting …
The paper reports a new electrostatic-confinement based fusion approach, where, a new non-equilibrium distribution function for an ion-beam, compressed by an external electric force, has been derived. This distribution function allows the…
This article proposes a new method to measure the proton detector efficiency for use in "beam" determinations of the free neutron lifetime. There is currently a 4{\sigma} disagreement between the "beam" and "storage" methods of measuring…
Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors…
This paper describes a new way to reconstruct and identify muons with high efficiency and high pion rejection. Since muons at the ILC are often produced with or in jets, for many of the physics channels of interest[1], an efficient…
Currently, density-based clustering algorithms are widely applied because they can detect clusters with arbitrary shapes. However, they perform poorly in measuring global density, determining reasonable cluster centers or structures,…
High-performance cluster-jet targets are ideally suited and applied since years in hadron and laser plasma physics. Therefore, the forthcoming MAGIX experiment at the future energy recovering electron accelerator MESA will use a cluster-jet…
Collider experiments, such as those at the Large Hadron Collider, use the Geant4 toolkit to simulate particle-detector interactions with high accuracy. However, these experiments increasingly require larger amounts of simulated data,…
We present a deep learning, computer vision algorithm constructed for the purposes of identifying and classifying charged particles in camera image sensors. We apply our algorithm to data collected by the Distributed Electronic Cosmic-ray…
The Electron-ion collider in China (EicC) is a proposed future electron-ion collider designed to achieve a high luminosity, with a center-of-mass energy ranging from 15 to 20 GeV. Excellent particle identification (PID) with extensive…
We describe 12 measurements in the 4th detector that yield particle identification information. Seven of these have been demonstrated with test beam data from the DREAM collaboration, one demonstrated in cosmic muon test data, one verified…
International Large Detector (ILD) adopts Particle Flow Algorithm (PFA) for precise measurement of multiple jets. The electromagnetic calorimeter (ECAL) of ILD has two candidates sensor technologies for PFA, which are pixelized silicon…
The goal of the international Muon Ionization Cooling Experiment (MICE) is to demonstrate muon beam ionization cooling for the first time. It constitutes a key part of the R&D towards a future neutrino factory or muon collider. The intended…
Photon-counting computed tomography (PCCT) with energy discrimination capabilities hold great potentials to improve the limitations of the conventional CT, including better signal-to-noise ratio (SNR), improved contrast-to-noise ratio…
Electrons and ions trapped with electromagnetic fields have long served as important high-precision metrological instruments, and more recently have also been proposed as a platform for quantum information processing. Here we point out that…
Contrary to other standard cameras, event cameras interpret the world in an entirely different manner; as a collection of asynchronous events. Despite event camera's unique data output, many event feature detection and tracking algorithms…
Timepix and Timepix3 are hybrid pixel detectors ($256\times 256$ pixels), capable of tracking ionizing particles as isolated clusters of pixels. To efficiently analyze such clusters at potentially high rates, we introduce multiple…
Quantum materials research requires co-design of theory with experiments and involves demanding simulations and the analysis of vast quantities of data, usually including pattern recognition and clustering. Artificial intelligence is a…
The integration of Deep Learning (DL) into experimental nuclear and particle physics has driven significant progress in simulation and reconstruction workflows. However, traditional simulation frameworks such as Geant4 remain…
We propose a novel method for the efficient and accurate iterative solution of frequency domain integral equations (IEs) that are used for large/multi-scale electromagnetic scattering problems. The proposed method uses a novel…
We propose DSC-Flow-Iter, a new community detection algorithm that is based on iterative extraction of dense subgraphs. Although DSC-Flow-Iter leaves many nodes unclustered, it is competitive with leading methods and has high-precision and…