Related papers: Anti-electron Neutrino Event Selection from Backgr…
We present a conceptual design for an active neutron veto, based on boron-loaded liquid scintillator, for use in direct-detection dark matter experiments. The simulated efficiency of a 1 meter thick veto, after including the effects of…
Atmospheric neutrinos play a vital role in generating irreducible backgrounds in liquid-scintillator (LS) detectors via their neutral-current (NC) interactions with $^{12}$C nuclei. These interactions may affect a wide range of research…
A large-volume liquid scintillator can be used as a tracking detector to measure high-energy neutrino events, like atmospheric neutrinos and neutrino beams. The lepton flavor recognition is almost absolute above 1 GeV. The energy resolution…
Neutron-induced nuclear recoil background is critical to the dark matter searches in the PandaX-4T liquid xenon experiment. This paper studies the feature of neutron background in liquid xenon and evaluates their contribution in the single…
This study developed a novel method for detecting hypernuclear events recorded in nuclear emulsion sheets using machine learning techniques. The artificial neural network-based object detection model was trained on surrogate images created…
A future large-volume liquid scintillator detector would provide a high-statistics measurement of terrestrial antineutrinos originating from $\beta$-decays of the uranium and thorium chains. In addition, the forward displacement of the…
Liquid-scintillator-based detectors are a robust technology that scales well to large volumes. For this reason, they are attractive for experiments searching for neutrinoless double-beta decay. A combination of improved photo-detection…
Scintillator doped with a high neutron-capture cross-section material can be used to detect neutrons via their resulting gamma rays. Examples of such detectors using liquid scintillator have been successfully used in high-energy physics…
The electron antineutrino spectrum in the Stereo reactor experiment (ILL Grenoble) is measured via the inverse beta decay signals in an organic liquid scintillator. The six target cells of the Stereo detector are filled with about 1800…
Machine learning has emerged as a powerful tool in materials discovery, enabling the rapid design of novel materials with tailored properties for countless applications, including in the context of energy and sustainability. To ensure the…
In CLEAN (Cryogenic Low Energy Astrophysics with Noble gases), a proposed neutrino and dark matter detector, background discrimination is possible if one can determine the location of an ionizing radiation event with high accuracy. We…
We carried out a study of neutrino detection at the experimental fast reactor JOYO using a 0.76 tons gadolinium loaded liquid scintillator detector. The detector was set up on the ground level at 24.3m from the JOYO reactor core of 140MW…
A method for reconstructing the direction of a fast neutron source using a segmented organic scintillator-based detector and deep learning model is proposed and analyzed. The model is based on recurrent neural network, which can be trained…
The paper explores the feasibility of using machine learning techniques, in particular neural networks, for classification of the experimental data from the joint $^\text{nat}$C(n,p) and $^\text{nat}$C(n,d) reaction cross section…
Gadolinium-loading of large water Cherenkov detectors is a prime method for the detection of the Diffuse Supernova Neutrino Background (DSNB). While the enhanced neutron tagging capability greatly reduces single-event backgrounds,…
The ability to detect liquid argon scintillation light from within a densely packed high-purity germanium detector array allowed the GERDA experiment to reach an exceptionally low background rate in the search for neutrinoless double beta…
Liquid scintillators are a common choice for neutrino physics experiments, but their capabilities to perform background rejection by scintillation pulse shape discrimination is generally limited in large detectors. This paper describes a…
Recent discoveries by neutrino telescopes, such as the IceCube Neutrino Observatory, relied extensively on machine learning (ML) tools to infer physical quantities from the raw photon hits detected. Neutrino telescope reconstruction…
In the paper, it is discussed by using Monte-Carlo simulation that the Bayesian Neural Network(BNN) is applied to determine neutrino incoming direction in reactor neutrino experiments and supernova explosion location by scintillator…
The direction of individual $^8$B solar neutrinos has been reconstructed using the SNO+ liquid scintillator detector. Prompt, directional Cherenkov light was separated from the slower, isotropic scintillation light using time information,…