相关论文: XSgen: A Cross Section Generation Methodology for …
Simulations of the neutron background for future large-scale particle dark matter detectors are presented. Neutrons were generated in rock and detector elements via spontaneous fission and (alpha,n) reactions, and by cosmic-ray muons. The…
Acquiring and annotating surgical data is often resource-intensive, ethical constraining, and requiring significant expert involvement. While generative AI models like text-to-image can alleviate data scarcity, incorporating spatial…
Machine learning (ML) has recently gained attention as a means to develop more accurate exchange-correlation (XC) functionals for density functional theory, but functionals developed thus far need to be improved on several metrics,…
(Abridged) Modern studies and industrial applications related to the design, radiation protection, and reliability of nuclear facilities, medical applications, as well as space research and exploration are relying on extensive simulations…
The potential for using boundary functionals of random risk processes to solve nuclear safety problems at nuclear power plants is assessed. In certain situations (MSRs (Molten Salt Reactors), High-Temperature Gas-Cooled Reactors (HTGRs),…
For validation and development of codes and for modeling isotope production in high power accelerators and APT Materials studies, we have produced experimental, calculated, and evaluated activation libraries for interaction of nucleons with…
The XDEM multi-physics and multi-scale simulation platform roots in the Ex- tended Discrete Element Method (XDEM) and is being developed at the In- stitute of Computational Engineering at the University of Luxembourg. The platform is an…
The reduced cross sections of the semi-exclusive $(l,l'p)$ lepton scattering process can be identified with distorted nuclear spectral functions. Irrespective of the type of interaction the distorted spectral function is determined mainly…
Quantum machine learning (QML) is a fast-growing discipline within quantum computing. One popular QML algorithm, quantum kernel estimation, uses quantum circuits to estimate a similarity measure (kernel) between two classical feature…
A deep neural network was developed for the purpose of predicting thermal conductivity with a case study performed on neutron irradiated nuclear fuel. Traditional thermal conductivity modeling approaches rely on existing theoretical…
The T-REX neutron spectrometer at the European Spallation Source will use Multi-Grid Technology, which is a voxelised proportional counter relying on\mathrm{^{10}B_{4}C} coatings to detect the scattered neutrons. Measurements of the…
Currently running and forthcoming precision neutrino oscillation experiments aim to unambiguously determine the neutrino mass ordering, the charge-parity violating phase in the lepton sector and the possible existence of physics Beyond the…
Charged and neutral current low energy neutrino cross section predictions from a variety of Monte Carlo generators in present use are compared against existing experimental data. Comparisons are made to experimental data on quasi-elastic,…
This work presents CascadeCNN, an automated toolflow that pushes the quantisation limits of any given CNN model, to perform high-throughput inference by exploiting the computation time-accuracy trade-off. Without the need for retraining, a…
A finite-dimensional matrix model for the nucleon-nucleon cross section operator is used to calculate the dispersive correction to nucleon-nucleus total cross sections, and the leading terms in its expansion in the number of inelastic…
We introduce VertexRegen, a novel mesh generation framework that enables generation at a continuous level of detail. Existing autoregressive methods generate meshes in a partial-to-complete manner and thus intermediate steps of generation…
Black-box runtime verification methods for cyber-physical systems can be used to discover errors in systems whose inputs and outputs are expressed as signals over time and their correctness requirements are specified in a temporal logic.…
X-ray diffraction from molecules in the ground state produces an image of their charge density, and time-resolved X-ray diffraction can thus monitor the motion of the nuclei. However, the density change of excited valence electrons upon…
Despite their importance in a wide variety of applications, the estimation of ionization cross sections for large molecules continues to present challenges for both experiment and theory. Machine learning algorithms have been shown to be an…
Light axions can potentially leave a cosmic background, just like neutrinos. We complete the study of thermal axion production across the electroweak scale by providing a smooth and continuous treatment through the two phases. Focusing on…