Related papers: Convolutional Neural Network-Based Neutron and Gam…
The basic principles of detection of fast neutrons with liquid scintillator detectors are reviewed, together with a real example in the form of the Neutron Wall array. Two of the challenges in neutron detection, discrimination of neutrons…
The next generation of very-short-baseline reactor experiments will require compact detectors operating at surface level and close to a nuclear reactor. This paper presents a new detector concept based on a composite solid scintillator…
Particle detectors record the interactions of subatomic particles and their passage through matter. The identification of these particles is necessary for in-depth physics analysis. While particles can be identified by their individual…
The application of deep learning techniques using convolutional neural networks to the classification of particle collisions in High Energy Physics is explored. An intuitive approach to transform physical variables, like momenta of…
Detailed characterization of the newly available plastic scintillator (EJ-299-33A) having the pulse shape discrimination (PSD) property has been carried out in case of a large-sized detector (5 in.$\times$5 in.). The pulse height response…
The ability to discover new transients via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine Learning techniques such as…
Cosmic Ray and neutrino oscillation physics can be studied by using atmospheric neutrinos. JUNO (Jiangmen Underground Neutrino Observatory) is a large liquid scintillator detector with low energy detection threshold and excellent energy…
An essential metric for the quality of a particle-identification experiment is its statistical power to discriminate between signal and background. Pulse shape discrimination (PSD) is a basic method for this purpose in many nuclear,…
We propose a new method for the discrimination of sub-micron nuclear recoil tracks from an instrumental background in fine-grain nuclear emulsions used in the directional dark matter search. The proposed method uses a 3D Convolutional…
The tracks recorded by a gaseous detector provide a possibility for charged particle identification. For searching the neutrinoless double beta decay events of 136Xe in the PandaX-III experiment, we optimized the convolutional neural…
A novel algorithm for the discrimination of neutron and {\gamma}-ray with wavelet transform modulus maximum (WTMM) in an organic scintillation has been investigated. Voltage pulses arising from a BC501A organic liquid scintillation detector…
Gamma-ray emission from special nuclear material (SNM) is relatively easy to shield from detection using modest amounts of high-Z material. In contrast, fast-neutrons are much more penetrating and can escape relatively thick high-Z…
Scintillators with pulse-shape discrimination (PSD) capability are of great interest to many fields in the scientific community. The ability to discern a gamma ray from a neutron using PSD varies between different types of scintillator…
Organic scintillators exhibit fast timing, high detection efficiency for fast neutrons and pulse shape discrimination (PSD) capability. PSD is essential in mixed radiation fields, where different types of radiation need to be detected and…
The reliable detection of neutrons in a harsh gamma-ray environment is an important aspect of establishing non-destructive methods for the characterization of spent nuclear fuel. In this study, we present results from extended in-situ…
We present a study of the potential for Convolutional Neural Networks (CNNs) to enable separation of astrophysical transients from image artifacts, a task known as "real-bogus" classification without requiring a template subtracted (or…
We present a detailed characterization of the thermal neutron sensitive transparent glass scintillator SG101, benchmarked against the conventional LiF ZnS(Ag)based scintillator EJ426. The detection efficiency, energy resolution, and pulse…
Current synoptic sky surveys monitor large areas of the sky to find variable and transient astronomical sources. As the number of detections per night at a single telescope easily exceeds several thousand, current detection pipelines make…
This paper presents studies on application of convolutional neural network (CNN) to GEANT4 optical simulation data generated with a scintillator detector subdivided into 1 cubic cm, which is designed for the long-baseline neutrino…
(Gd,La)$_2$Si$_2$O$_7$:Ce (La-GPS:Ce) is a new scintillator material with high light output, high energy resolution, and fast decay time. Moreover, the scintillator has a good light output even at high temperature (up to 150$^\circ$C) and…