Related papers: Direct Photon Identification with Artificial Neura…
We study the photon detection efficiency and position resolution of the electromagnetic calorimeter (EMC) of the BESIII experiment. The control sample of the initial-state-radiation (ISR) process of $e^+e^-\rightarrow \gamma \mu^+\mu^-$ is…
We present the results for direct photon and neutral pion production obtained from proton-proton and lead-lead collisions in the ALICE experiment. Measurement of neutral pions in pp collisions allows to test the validity of QCD-inspired…
Artificial neural networks are efficient computing platforms inspired by the brain. Such platforms can tackle a vast area of real-life tasks ranging from image processing to language translation. Silicon photonic integrated chips (PICs), by…
At high pT, direct photons produced in Compton and annihilation QCD leading order processes are associated to a jet in the opposite direction. Such processes are tagged experimentally by identifying leading isolated photons and their…
The Alpha Magnetic Spectrometer (AMS) is a high-precision particle detector onboard the International Space Station containing six different subdetectors. The Transition Radiation Detector and Electromagnetic Calorimeter (ECAL) are used to…
The identification of light sources represents a task of utmost importance for the development of multiple photonic technologies. Over the last decades, the identification of light sources as diverse as sunlight, laser radiation and…
The production of light neutral mesons in different collision systems is interesting for a variety of reasons: In nucleus-nucleus (AA) collisions the measurements provide important information on the energy loss of partons traversing the…
The ALICE experiment at the LHC measures properties of the strongly interacting matter formed in ultrarelativistic heavy-ion collisions. Such studies require accurate particle identification (PID). ALICE provides PID information via several…
Measurement of the ultra-rare $K^+\to\pi^+\nu\bar\nu$ decay at the NA62 experiment at CERN requires high-performance particle identification to distinguish muons from pions. Calorimetric identification currently in use, based on a boosted…
We present two methods for determining the absolute detection efficiency of photon-counting detectors directly from their singles rates under illumination from a nonclassical light source. One method is based on a continuous variable…
Measurements of azimuthal distribution of inclusive photons using the fine granularity preshower photon multiplicity detector (PMD) at CERN SPS are used to obtain anisotropy in the azimuthal distributions. These results are used to estimate…
A Bayesian approach is proposed for pulse shape discrimination of photons and neutrons in liquid organic scinitillators. Instead of drawing a decision boundary, each pulse is assigned a photon or neutron confidence probability. This allows…
Organic scintillators are important in advancing nuclear detection and particle physics experiments. Achieving a high signal-to-noise ratio necessitates efficient pulse shape discrimination techniques to accurately distinguish between…
We apply convolutional neural networks (CNN) to the problem of image orientation detection in the context of determining the correct orientation (from 0, 90, 180, and 270 degrees) of a consumer photo. The problem is especially important for…
Relevant information about physical properties of the surface of airless bodies such as porosity, particle size, or roughness can be inferred knowing the dependence of the brightness with illumination and observing geometry. Additionally,…
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 production of direct photons, not coming from hadron decays, at large transverse momentum pT > 2 GeV/c in proton-proton collisions at the LHC, is an interesting process to test the predictions of perturbative Quantum Chromodynamics at…
The use of Artificial Neural Networks (ANNs) as a classifier of digital spectra is investigated. Using both simulated and real data, it is shown that neural networks can be trained to discriminate between the spectra of different classes of…
Dark photon is a massive vector particle which couples to the physical photon through the kinetic mixing term. Such particles, if exist, are produced in photon beams and, in particular, in laser radiation. Due to the oscillations between…
The efficiency of the photon identification criteria in the ATLAS detector is measured using 36.1 fb$^{-1}$ to 36.7 fb$^{-1}$ of $pp$ collision data at $\sqrt{s}$ = 13 TeV collected in 2015 and 2016. The efficiencies are measured separately…