Related papers: Comparative pulse shape discrimination study for C…
We'd like to share a simple tweak of Single Shot Multibox Detector (SSD) family of detectors, which is effective in reducing model size while maintaining the same quality. We share box predictors across all scales, and replace convolution…
A new Digital Pulse Processing (DPP) module has been developed, based on a domino ring sampler version 4 chip (DRS4), with good time resolution for LaBr3 detectors, and different digital timing analysis methods for processing the raw…
Quantum sensors using solid-state spin defects excel in the detection of radiofrequency (RF) fields, serving various purposes in communication, ranging, and sensing. For this purpose, pulsed dynamical decoupling (PDD) protocols are…
Pulse shape discrimination plays a key role in improving the signal-to-background ratio in NEOS analysis by removing fast neutrons. Identifying particles by looking at the tail of the waveform has been an effective and plausible approach…
A high light yield calcium iodide (CaI2) scintillator is being developed for an astroparticle physics experiments. This paper reports scintillation performance of calcium iodide (CaI2) crystal. Large light emission of 2.7 times that of…
In this paper, we present a decision level fused local Morphological Pattern Spectrum(PS) and Local Binary Pattern (LBP) approach for an efficient shape representation and classification. This method makes use of Earth Movers Distance(EMD)…
In this contribution we report on further investigations of the recently-evaluated Constant-Fraction Time-over-Threshold (CF-ToT) method for neutron/gamma-ray pulse shape discrimination (PSD). The superiority of the CF-ToT PSD method over…
We report the performance and characterization of a custom-built hybrid detector consisting of BC501A liquid scintillator for fast neutrons and BC702 scintillator for thermal neutrons. The calibration and the resolution of the BC501A liquid…
Recent research has focused on designing neural samplers that amortize the process of sampling from unnormalized densities. However, despite significant advancements, they still fall short of the state-of-the-art MCMC approach, Parallel…
The first domestic inorganic scintillator CLYC was grown in Beijing Glass Research Instituteusing the vertical Bridgman method. In this work, we evaluated the performance of this new CLYC crystal in terms of gamma-ray energy resolution and…
The FLASH effect holds significant potential in improving radiotherapy treatment outcomes. Very high energy electrons (VHEEs) can effectively target tumors deep in the body and can be accelerated to achieve ultra-high dose rates (UHDR),…
Positron Annihilation Lifetime Spectroscopy (PALS) is a non-destructive radiological technique widely used in material science studies. PALS typically relies on an analog coincidence measurement setup and allows the estimate of the positron…
This is a methodological guide to the use of deep neural networks in the processing of pulsed dipolar spectroscopy (PDS) data encountered in structural biology, organic photovoltaics, photosynthesis research, and other domains featuring…
As performance of dedicated facilities continually improved, massive pulsar candidates are being received, which makes selecting valuable pulsar signals from candidates challenging. In this paper, we designed a deep convolutional neural…
The SNO+ liquid scintillator experiment is under construction in the SNOLAB facility in Canada. The success of this experiment relies upon accurate characterization of the liquid scintillator, linear alkylbenzene (LAB). In this paper,…
The plasmon and phonon polaritons of two-dimensional (2d) and van-der-Waals materials have recently gained substantial interest. Unfortunately, they are notoriously hard to observe in linear response because of their strong confinement, low…
Single Shot MultiBox Detector (SSD) is one of the fastest algorithms in the current object detection field, which uses fully convolutional neural network to detect all scaled objects in an image. Deconvolutional Single Shot Detector (DSSD)…
Photoplethysmography (PPG) is a widely used non-invasive physiological sensing technique, suitable for various clinical applications. Such clinical applications are increasingly supported by machine learning methods, raising the question of…
One of the most promising approaches for the next generation of neutrino experiments is the realization of large hybrid Cherenkov/scintillation detectors made possible by recent innovations in photodetection technology and liquid…
The present study explores combining machine learning (ML) algorithms with standard optical diagnostics (such as time-integrated emission spectroscopy and imaging) to accurately predict operating conditions and assess the emission…