Related papers: Particle identification with the Belle II calorime…

A neural network method is developed to discriminate direct photons from the neutral pion background in the PHOS spectrometer of the ALICE experiment at the LHC collider. The neural net has been trained to distinguish different classes of…

We introduce a time-embedded convolutional neural network (TCNN) for modeling spatiotemporal heat transport in plasmas, particularly under strongly nonlocal conditions. In our earlier work, the LMV-Informed Neural Network (LINN) (Luo et…

In this work, we present results for discrimination of neutron and $\gamma$ events using a plastic scintillator detector with pulse shape discrimination capabilities. Machine learning (ML) algorithms are used to improve the discriminatory…

The iron calorimeter (ICAL) detector at the India-based Neutrino Observatory (INO) will be used to measure neutrino mass hierarchy. The magnet in the ICAL detector will be used to distinguish the {\mu^-} and {\mu^+} events induced by…

Monte Carlo simulations have been performed in order to evaluate the efficiencies of several light ions identification techniques. The detection system was composed with layers of scintillating material to measure either the deposited…

Holograms of colloidal particles can be analyzed with the Lorenz-Mie theory of light scattering to measure individual particles' three-dimensional positions with nanometer precision while simultaneously estimating their sizes and refractive…

The adaptability of the convolutional neural network (CNN) technique for aerodynamic meta-modeling tasks is probed in this work. The primary objective is to develop suitable CNN architecture for variable flow conditions and object geometry,…

We contrasted the performance of deep neural networks - Convolutional Neural Network (CNN) and Graph Neural Network (GNN) - to current state of the art energy regression methods in a finely 3D-segmented calorimeter simulated by GEANT4. This…

The Muon Ionization Cooling Experiment (MICE) collaboration seeks to demonstrate the feasibility of ionization cooling, the technique by which it is proposed to cool the muon beam at a future neutrino factory or muon collider. The emittance…

This paper presents a method to identify electrons using the Cherenkov light emitted when a charged particle travels in air and photons are detected with a Silicon PhotoMultiplier (SiPM). The analysis is based on a photon-counting approach…

Deep convolutional neural networks (CNNs) are indispensable to state-of-the-art computer vision algorithms. However, they are still rarely deployed on battery-powered mobile devices, such as smartphones and wearable gadgets, where vision…

A concept to search for a neutron electric dipole moment (nEDM) is presented, which employs a pulsed neutron beam instead of the nowadays established use of storable ultracold neutrons (UCN). The technique takes advantage of the high peak…

Aiming to reduce the computational cost of numerical simulations, a convolutional neural network (CNN) and a multi-layer perceptron (MLP) are introduced to build a surrogate model to approximate radiative heat transfer solutions in a 2-D…

Classification and identification of wild animals for tracking and protection purposes has become increasingly important with the deterioration of the environment, and technology is the agent of change which augments this process with novel…

Rock classification plays an important role in rock mechanics, petrology, mining engineering, magmatic processes, and numerous other fields pertaining to geosciences. This study proposes a concatenated convolutional neural network (Con-CNN)…

Pulse shape discrimination plays a key role in improving the signal-to-background ratio in NEOS analysis by removing fast neutrons. Identifying particles by looking at the tail of the waveform has been an effective and plausible approach…

The ALICE TPC provides excellent charged particle tracking for the study of pp and Pb-Pb collisions at LHC. The TPC also allows particle identification via the measurement of the specific ionisation dE/dx. At high pT (pT > 3 GeV/c) this is…

Position-sensitive detectors for cold and ultra-cold neutrons (UCN) are in use in fundamental research. In particular, measuring the properties of the quantum states of bouncing neutrons requires micro-metric spatial resolution. To this…

Mid-level visual element discovery aims to find clusters of image patches that are both representative and discriminative. In this work, we study this problem from the prospective of pattern mining while relying on the recently popularized…

A new technique is developed to identify dielectrons (e$^+$e$^-$) with Lorentz boost $\gamma_\mathrm{L}$ $\gt$ 20 that produce one single merged cluster in the electromagnetic calorimeter of the CMS detector. The identification uses two…