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Olivares Herrador, J., Wroe, L. M., Latina, A., Corsini, R., Wuensch, W., Stapnes, S., et al. (2026). Feasibility of High-Intensity Electron Linacs as Drivers for Compact Neutron Sources. IEEE Trans. Nucl. Sci., 73(1), 2–11.
Abstract: The increasing demand for neutron production facilities is driven both by the growing use of neutrons in a wide range of applications and by the progressive shutdown of major existing sources. These trends highlight the need for efficient and compact alternatives to traditional spallation and reactor-based systems. In this context, the present work investigates the potential of normal-conducting compact electron linacs, operating in the energy range of 20-500 MeV, as drivers for neutron generation. Using detailed G4beamline simulations, the optimal dimensions of a tungsten target are determined, and the resulting neutron emission spectrum is characterized. Two electron linac designs are evaluated as drivers for such a target: the HPCI X-band linac and the CTF3 drive-beam S-band linac. The study demonstrates that neutron source strengths up to 1.5 x 10(15) n/s can be achieved, with energy consumption per neutron produced as low as 5.6 x 10-(10) J/n. These findings suggest that electron-linac-based neutron sources offer a compact and energy-efficient solution suitable for a wide range of applications in research, industry, and medicine.
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Zhuo, J., Oyanguren, A., Fernandez Casani, A., Fiorini, L., & Kholoimov, V. (2026). Energy efficiency of a GPU-based computing system for high energy physics experiments. Front. Physics, 14, 1868616–8pp.
Abstract: In this paper we introduce the energy efficiency as a new metric for evaluating both hardware platforms based on Graphic Processor Units (GPU), and algorithm optimisations at High Energy Physics (HEP) experiments. We develop a method to compute the energy efficiency for the case of the first high level trigger (HLT1) of the LHCb experiment, relating the throughput with GPU specifications such as the number of cores, clock frequency, memory bandwidth and thermal design power. The model can be extended to other HEP experiments to make decisions and reach sustainable computing ecosystems.
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