Related papers: Interpretable machine learning approach for electr…
Experiments searching for rare processes like neutrinoless double beta decay heavily rely on the identification of background events to reduce their background level and increase their sensitivity. We present a novel machine learning based…
We present an application of machine-learning (ML) techniques to source selection in the optical transient survey data with Hyper Suprime-Cam (HSC) on the Subaru telescope. Our goal is to select real transient events accurately and in a…
The existence of the coherent neutrino-nucleus scattering reaction requires to evaluate, for any detector devoted to WIMP searches, the irreducible background due to conventional neutrino sources and at same time, it gives a unique chance…
As a green and secure wireless transmission way, secure spatial modulation (SM) is becoming a hot research area. Its basic idea is to exploit both the index of activated transmit antenna and amplitude phase modulation (APM) signal to carry…
Pulse shape discrimination (PSD) is widely used in particle and nuclear physics. Specifically in liquid scintillator detectors, PSD facilitates the classification of different particle types based on their energy deposition patterns. This…
Numerous phenomenological nuclear models have been proposed to describe specific observables within different regions of the nuclear chart. However, developing a unified model that describes the complex behavior of all nuclei remains an…
In neutrino oscillation experiments, neutrino interactions at the detector are simulated using event generators which attempt to reflect our understanding of nuclear physics. We study the impact of different neutrino interactions and…
We apply machine learning to the searches of heavy neutrino mixing in the inverse seesaw in the framework of left-right symmetric model at the high-energy hadron colliders. The Majorana nature of heavy neutrinos can induce the processes $pp…
First results from the JUNO reactor neutrino experiment already determine with world-leading precision the small neutrino squared-mass splitting $\Delta m^2_{21}$ and the mixing angle $\theta_{12}$. In this article we perform an exploratory…
The Jiangmen Underground Neutrino Observatory (JUNO) is a multipurpose neutrino experiment with a 20 kt liquid scintillator detector designed to determine the neutrino mass hierarchy, and measure the neutrino oscillation parameters. Linear…
The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator (LS) detector for neutrino mass ordering and other neutrino physics research. The detector uses large-size $20$ inches photomultiplier tubes to detect…
Dual-phase time projection chamber (TPC) that employs a multi-ton-scale liquid xenon (LXe) target mass is a pioneering detector technology to search for dark matter. Beyond its advantage in dark matter direct detection efforts, the natural…
The 20kt Liquid Scintillator (LS) JUNO detector is being constructed by the International Collaboration in China, with the primary goal of addressing the question of neutrino mass ordering (hierarchy). The main challenge for JUNO is to…
The Taishan Antineutrino Observatory (TAO, also known as JUNO-TAO) is a satellite experiment of the Jiangmen Underground Neutrino Observatory (JUNO). A ton-level liquid scintillator detector will be placed at about 30 m from a core of the…
Rotary machine breakdown detection systems are outdated and dependent upon routine testing to discover faults. This is costly and often reactive in nature. Real-time monitoring offers a solution for detecting faults without the need for…
Liquid scintillator detectors are playing an increasingly important role in low-energy neutrino experiments. In this article, we describe a generic energy response model of liquid scintillator detectors that provides energy estimations of…
Jet measurements in heavy ion collisions can provide constraints on the properties of the quark gluon plasma, but the kinematic reach is limited by a large, fluctuating background. We present a novel application of symbolic regression to…
We describe a method for determining the hierarchy of the neutrino mass spectrum and theta_13 through remote detection of antineutrinos from a nuclear reactor. This method utilizing a single, 10-kt scintillating liquid detector at a…
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…
We have developed a neutrino detector with threshold energies from ~0.115 to 105 MeV in a clean detection mode almost completely void of accidental backgrounds. It was initially developed for the NASA $\nu$SOL project to put a solar…