Related papers: Deep learning based pulse shape discrimination for…
Various pulse shape discrimination methods have been used to solve the neutron-gamma discrimination problem. But most of them are limited to off-line calculation due to the computation amount and FPGA performance. In order to realize real…
Collisions at high-energy particle colliders are a traditionally fruitful source of exotic particle discoveries. Finding these rare particles requires solving difficult signal-versus-background classification problems, hence machine…
A toy detector has been designed to simulate central detectors in reactor neutrino experiments in the paper. The samples of neutrino events and three major backgrounds from the Monte-Carlo simulation of the toy detector are generated in the…
Space-based X-ray detectors are subject to significant fluxes of charged particles in orbit, notably energetic cosmic ray protons, contributing a significant background. We develop novel machine learning algorithms to detect charged…
High pressure gas detectors offer advantages for the detection of rare events, where background reduction is crucial. For the neutrinoless double beta decay of 136Xe a high pressure xenon gas Time Projection Chamber (TPC) combines a good…
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…
A new data-driven method is proposed to detect events in the data streams from distribution-level phasor measurement units, a.k.a., micro-PMUs. The proposed method is developed by constructing unsupervised deep learning anomaly detection…
The GERmanium Detector Array, GERDA, is designed to search for neutrinoless double beta (0$\nu\beta\beta$) decay of $^{76}$Ge and it is installed in the Laboratori Nazionali del Gran Sasso (LNGS) of INFN, Italy. In this review, the…
It is important to identify and reduce the gamma radiation which can be a significant source of background for any double beta decay experiment. The TIN.TIN detector array, which is under development for the search of Neutrinoless Double…
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…
Cosmogenic nuclides inside germanium detectors contribute background noise spectra quite different from ordinary external sources. We propose and discuss a nuclide decay and level transition model based on graph theory to understand the…
The performance of a 630g commercial broad energy germanium (BEGe) detector has been systematically investigated. Energy resolution, linearity, stability vs. high-voltage (HV) bias, thickness and uniformity of dead layers have been measured…
We report a new method of using the plasma time difference, which results from the plasma effect, between the nuclear and electronic recoil events in high-purity germanium detectors to distinguish these two types of events in the search for…
We propose a novel approach to the recognition of particular classes of non-conventional events in signals from phase-sensitive optical time-domain-reflectometry-based sensors. Our algorithmic solution has two main features: filtering aimed…
A new type of radiation detector, a p-type modified electrode germanium diode, is presented. The prototype displays, for the first time, a combination of features (mass, energy threshold and background expectation) required for a…
Particle tracks and differential energy loss measured in high pressure gaseous detectors can be exploited for event identification in neutrinoless double beta decay~($0\nu \beta \beta$) searches. We develop a new method based on Kalman…
Resonant anomaly detection is a promising framework for model-independent searches for new particles. Weakly supervised resonant anomaly detection methods compare data with a potential signal against a template of the Standard Model (SM)…
Rare event searches allow us to search for new physics at energy scales inaccessible with other means by leveraging specialized large-mass detectors. Machine learning provides a new tool to maximize the information provided by these…
The success of current and future-generation neutrinoless double beta decay experiments relies on the ability to eliminate or reduce extraneous backgrounds. In addition to constructing experiments using radiopure materials and handling in…
Convolutional neural networks (CNNs) are widely used state-of-the-art computer vision tools that are becoming increasingly popular in high energy physics. In this paper, we attempt to understand the potential of CNNs for event…