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A. Trabelsi

Publications and source records attributed to A. Trabelsi.

4 recordsLinked to original sources
arXiv2026

Gamma-ray production cross sections in proton interactions with natMg, natSi and 56Fe targets: measurement over the energy range of $E_p = 66$-125 MeV, data analysis, results and discussion. Astrophysical implications

We have measured nuclear gamma-ray line production cross sections in interactions of highly accelerated proton beams with various target nuclei abundant in astrophysical sites. The experiments were carried out at the 200-MV Separated Sector Cyclotron (SSC) of iThemba LABS (near Cape Town, in South Africa) using a high-energy resolution and high efficiency detection system for registering the emitted gamma-ray photons. We report and discuss in this paper the collected experimental data sets for various gamma-ray lines produced in bombarding natMg, natSi and 56Fe targets with proton beams of incident energies of Ep = 66, 80, 95, 110 and 125 MeV. After describing the experimental set up and the data analysis method used, we report and discuss our total experimental cross section results in comparisons to previous counterparts from the literature, to a semi-empirical compilation and to the predictions of nuclear reaction theory via performed TALYS code calculations. Significantly improved agreements between theory and experiment are point out when using our modified optical model potential and B\^eta (lambda) level deformation parameters instead of the default input parameters built in TALYS. Finally, we put into perspective the applications of our results in nuclear physics and astrophysics with drawing relevant conclusions. gammaKeywords: Proton-induced nuclear reactions; gamma-ray production cross sections; gamma-ray spectrometry; gamma-ray spectroscopy; Astrophysical implications

nucl-ex↗
arXiv2022

Hardware calibrated learning to compensate heterogeneity in analog RRAM-based Spiking Neural Networks

Spiking Neural Networks (SNNs) can unleash the full power of analog Resistive Random Access Memories (RRAMs) based circuits for low power signal processing. Their inherent computational sparsity naturally results in energy efficiency benefits. The main challenge implementing robust SNNs is the intrinsic variability (heterogeneity) of both analog CMOS circuits and RRAM technology. In this work, we assessed the performance and variability of RRAM-based neuromorphic circuits that were designed and fabricated using a 130\,nm technology node. Based on these results, we propose a Neuromorphic Hardware Calibrated (NHC) SNN, where the learning circuits are calibrated on the measured data. We show that by taking into account the measured heterogeneity characteristics in the off-chip learning phase, the NHC SNN self-corrects its hardware non-idealities and learns to solve benchmark tasks with high accuracy. This work demonstrates how to cope with the heterogeneity of neurons and synapses for increasing classification accuracy in temporal tasks.

cs.NE↗
arXiv1996

Determination of the mass of the W boson

Previous studies of the physics potential of LEP2 indicated that with the design luminosity of 500 inverse picobarn one may get a direct measurement of the mass of the W-boson with a precision in the range 30 - 50 MeV. This report presents an updated evaluation of the estimated error on the mass of the W-boson based on recent simulation work and improved theoretical input. The most efficient experimental methods which will be used are also described.

hep-ph↗