Abstract: The shape of the electron spectrum emitted in /3 decay carries a wealth of information about nuclear structure and fundamental physics. In spite of that, few dedicated measurements have been made of /3 -spectrum shapes. In this work we present a newly developed detector for /3 electrons based on a telescope concept. A thick plastic scintillator is employed in coincidence with a thin silicon detector. The first measurements employing this detector have been carried out with mono -energetic electrons from the high-energy resolution electron -beam spectrometer at Bordeaux. Here we report on the good reproduction of the experimental spectra of mono -energetic electrons using Monte Carlo simulations. This is a crucial step for future experiments, where a detailed Monte Carlo characterization of the detector is needed to determine the shape of the /3 -electron spectra by deconvolution of the measured spectra with the response function of the detector. A chamber to contain two telescope assemblies has been designed for future /3 -decay experiments at the Ion Guide Isotope Separator On -Line facility in Jyvaskyla, aimed at improving our understanding of reactor antineutrino spectra.

Abstract: The International Fusion Materials Irradiation Facility- DEMO Oriented Neutron Source (IFMIF-DONES) is a scientific infrastructure aimed to provide an intense neutron source for the qualification of materials to be used in future fusion power reactors. Its implementation is critical for the construction of the fusion DEMOnstration Power Plant (DEMO). IFMIF-DONES is a unique facility requiring a broad set of technologies. Although most of the necessary technologies have already been validated, there are still some aspects that introduce risks in the evolution of the project. In order to mitigate these risks, a consortium of companies, with the support of research centres and the funding of the CDTI (Centre for the Development of Industrial Technology and Innovation), has launched the DONES EVO Programme, which comprises six lines of research: center dot Improvement of signal transmission and integrity (planning and integration risks) center dot Optimisation of RF conditioning processes (planning and reliability risks) center dot Development of a reliable beam extraction device (reliability risks) center dot Development of technologies for the production of medical isotopes (reliability risks) center dot Improvement of critical parts of the lithium purification system (safety and reliability risks) center dot Validation of the manufacture of critical components with special materials (reliability risk). DONES EVO will focus on developing the appropriate response to the risks identified in the IFMIFDONES project through research and prototyping around the associated technologies.

Abstract: We present a novel methodology based on Physics-Informed Neural Networks (PINNs) for solving systems of partial differential equations admitting discontinuous solutions. Our method, called Gradient-Annihilated PINNs (GA-PINNs), introduces a modified loss function that forces the model to partially ignore high-gradients in the physical variables, achieved by introducing a suitable weighting function. The method relies on a set of hyperparameters that control how gradients are treated in the physical loss. The performance of our methodology is demonstrated by solving Riemann problems in special relativistic hydrodynamics, extending earlier studies with PINNs in the context of the classical Euler equations. The solutions obtained with the GA-PINN model correctly describe the propagation speeds of discontinuities and sharply capture the associated jumps. We use the relative l(2) error to compare our results with the exact solution of special relativistic Riemann problems, used as the reference ''ground truth'', and with the corresponding error obtained with a second-order, central, shock-capturing scheme. In all problems investigated, the accuracy reached by the GA-PINN model is comparable to that obtained with a shock-capturing scheme, achieving a performance superior to that of the baseline PINN algorithm in general. An additional benefit worth stressing is that our PINN-based approach sidesteps the costly recovery of the primitive variables from the state vector of conserved variables, a well-known drawback of grid-based solutions of the relativistic hydrodynamics equations. Due to its inherent generality and its ability to handle steep gradients, the GA-PINN methodology discussed in this paper could be a valuable tool to model relativistic flows in astrophysics and particle physics, characterized by the prevalence of discontinuous solutions.