Related papers: FENDL: A library for fusion research and applicati…
Fission product yields are key infrastructure data for nuclear applications in many aspects. It is a challenge both experimentally and theoretically to obtain accurate and complete energy-dependent fission yields. We apply the Bayesian…
In the realm of drug discovery, DNA-encoded library (DEL) screening technology has emerged as an efficient method for identifying high-affinity compounds. However, DEL screening faces a significant challenge: noise arising from nonspecific…
The CN Van de Graaff accelerator of INFN--LNL provides forward-angle quasi-monoenergetic neutrons in the 0.7--4 MeV range via the 7Li(p,n)7Be reaction on thin metallic lithium targets. This work describes the development and experimental…
Transfer learning (TL) allows a deep neural network (DNN) trained on one type of data to be adapted for new problems with limited information. We propose to use the TL technique in physics. The DNN learns the details of one process, and…
The Advanced Experimental Fuel Counter (AEFC) is a nondestructive assay (NDA) instrument designed to determine the residual fissile mass in irradiated fuel assemblies for safeguards verification purposes. This is done by actively…
This paper reviews improved calibration methods for the Lunar Reconnaissance Orbiter Lunar Exploration Neutron Detector. We cross calibrated the set of LEND observations and models of its detectors physical geometry and composition against…
Current needs of nuclear science and technology include complete, well-documented, and easily verifiable nuclear data. The complete data records require supporting nuclear bibliography, presently stored in dedicated libraries, in addition,…
Tensor Networks have emerged as a prominent alternative to neural networks for addressing Machine Learning challenges in foundational sciences, paving the way for their applications to real-life problems. This paper introduces tn4ml, a…
The Medley setup is planned to be moved to and used at the new neutron facility NFS where measurements of light-ion production and fission cross-sections are planned at 1-40 MeV. Medley has eight detector telescopes providing Delta E-Delta…
Fluorescent nuclear track detectors (FNTDs) based on Al2O3:C,Mg single crystal combined with confocal microscopy provide 3D information on ion tracks with a resolution only limited by light diffraction. FNTDs are also ideal substrates to be…
This article summarizes recent progress in our understanding of the reaction mechanisms leading to the formation of superheavy nuclei in cold and hot fusion reactions. Calculations are done within the Fusion-by-Diffusion (FBD) model using…
The upgraded IGISOL facility with JYFLTRAP, at the accelerator laboratory of the University of Jyv\"askyl\"a, has been supplied with a new cyclotron which will provide protons of the order of 100 {\mu}A with up to 30 MeV energy, or…
We present JDLL, an agile Java library that offers a comprehensive toolset/API to unify the development of high-end applications of DL for bioimage analysis and to streamline their installation and maintenance. JDLL provides all the…
Unrestricted file upload (UFU) is a class of web security vulnerabilities that can have a severe impact on web applications if uploaded files are not sufficiently validated or securely handled. A review of related work shows an increased…
We present NeoPDF, an interpolation library that supports both collinear and transverse momentum-dependent parton distribution functions. NeoPDF is designed to be fast and reliable, with modern functionalities that target both current and…
Deploying deep neural networks on edge devices is often limited by the memory traffic and compute cost of dense linear operators. While quaternion neural networks improve parameter efficiency by coupling multiple channels through Hamilton…
Next Generation (NextG) networks are expected to support demanding tactile internet applications such as augmented reality and connected autonomous vehicles. Whereas recent innovations bring the promise of larger link capacity, their…
In this study, we explore the innovative domain of Quantum Federated Learning (QFL) as a framework for training Quantum Machine Learning (QML) models via distributed networks. Conventional machine learning models frequently grapple with…
Interest in deploying Deep Neural Network (DNN) inference on edge devices has resulted in an explosion of the number and types of hardware platforms to use. While the high-level programming interface, such as TensorFlow, can be readily…
Detailed notes on the functions included in the DMRjulia library are included here. This discussion of how to program functions for a tensor network library are intended to be a supplement to the other documentation dedicated to explaining…