Related papers: Unfolding the Neutron Spectra from a Water-Pumping…
Deep learning is an increasingly popular approach for inverting surface wave dispersion curves to obtain Vs profiles. However, its generalizability is constrained by the depth and velocity scales of training data. We propose a unified deep…
An optimization of the CERN SPL beam line has been performed guided by the sensitivities to the \theta_{13} mixing angle and to the \delta_{CP} Dirac CP violating phase. A UNO-like 440 ktons water Cerenkov detector located at 130 km from…
We explore the sensitivity of several core-level spectroscopic methods to the underlying atomistic structure by using the water molecule as our test system. We first define a metric that measures the magnitude of spectral change as a…
We develop a multi-port-backscatter-modulation technique to determine, over the air (OTA), the scattering parameters of a linear, passive, time-invariant multi-port device under test (DUT). A set of "not-directly-accessible" (NDA) antennas…
In this paper, the nonlinear Volterra series expansion is extended and used to describe certain types of nonautonomous differential equations related to the inverse scattering problem in nuclear physics. The nonautonomous Volterra series…
Photon readout of plastic scintillators is investigated with the aim of improving the precision of neutron \b{eta} decay experiments. Neutron decay is nowadays studied with high statistics, based on up to 109 registered decay events, and…
We adapted the highly successful scattering density profile (SDP) model, which is used to jointly analyze small angle x-ray and neutron scattering data from unilamellar vesicles, for use with data from fully hydrated, liquid crystalline…
A fast neutron spectrometer consisting of segmented plastic scintillator and He-3 proportional counters was constructed for the measurement of neutrons in the energy range 1 MeV to 200 MeV. We discuss its design, principles of operation,…
We calculate the scattering rate of low energy neutrinos in hot and dense neutron matter encountered in neutrons stars and supernova in the hydrodynamic regime. We find that the Brillouin peak, associated with the sound mode, and the…
Intracortical brain-machine interfaces demand low-latency, energy-efficient solutions for neural decoding. Spiking Neural Networks (SNNs) deployed on neuromorphic hardware have demonstrated remarkable efficiency in neural decoding by…
We present a new deep unfolding network for analysis-sparsity-based Compressed Sensing. The proposed network coined Decoding Network (DECONET) jointly learns a decoder that reconstructs vectors from their incomplete, noisy measurements and…
This study shows an implementation of neutron-gamma pulse shape discrimination (PSD) using a two-dimensional convolutional neural network. The inputs to the network are snapshots of the unprocessed, digitized signals from a BC501A detector.…
Deep Unfolding Network-based methods have emerged as effective solutions for multi-source image fusion by combining model-driven iterative optimization with data-driven deep learning. However, most existing deep unfolding image fusion…
Deep learning has been broadly applied to imaging in scattering applications. A common framework is to train a descattering network for image recovery by removing scattering artifacts. To achieve the best results on a broad spectrum of…
Wireless multi-port sensing remotely retrieves the scattering matrix of a multi-port device under test (DUT) connected to a set of not-directly-accessible (NDA) antennas that couple over-the-air (OTA) to a set of accessible antennas. If (i)…
We derive concentration inequalities for the supremum norm of the difference between a kernel density estimator (KDE) and its point-wise expectation that hold uniformly over the selection of the bandwidth and under weaker conditions on the…
Accurate and automated lesion segmentation in Positron Emission Tomography / Computed Tomography (PET/CT) imaging is essential for cancer diagnosis and therapy planning. This paper presents a Swin Transformer UNet 3D (SwinUNet3D) framework…
This report serves as a technology description of a Julia-based re-implementation of the fixed-point current injection algorithm, available in PowerModelsDistribution.jl [1]. This report does not describe a novel method for solving…
The study of phonon dynamics is pivotal for understanding material properties, yet it faces challenges due to the irreversible information loss inherent in powder inelastic neutron scattering spectra and the limitations of traditional…
One of the robust features found in simulations of core-collapse supernovae (SNe) is the prompt neutronization burst, i.e. the first $\sim 25$ milliseconds after bounce when the SN emits with very high luminosity mainly $\nu_e$ neutrinos.…