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Giare, W., Di Valentino, E., Melchiorri, A., & Mena, O. (2021). New cosmological bounds on hot relics: axions and neutrinos. Mon. Not. Roy. Astron. Soc., 505(2), 2703–2711.
Abstract: Axions, if realized in nature, can be copiously produced in the early universe via thermal processes, contributing to the mass-energy density of thermal hot relics. In light of the most recent cosmological observations, we analyse two different thermal processes within a realistic mixed hot dark matter scenario which includes also massive neutrinos. Considering the axion-gluon thermalization channel, we derive our most constraining bounds on the hot relic masses m(a) < 7.46 eV and Sigma m(nu) < 0.114 eV both at 95 percent CL; while studying the axion-pion scattering, without assuming any specific model for the axion-pion interactions, and remaining in the range of validity of the chiral perturbation theory, our most constraining bounds are improved to m(a) < 0.91 eV and Sigma m(nu) < 0.105 eV, both at 95 percent CL. Interestingly, in both cases, the total neutrino mass lies very close to the inverted neutrino mass ordering prediction. If future terrestrial double beta decay and/or long-baseline neutrino experiments find that the nature mass ordering is the inverted one, this could rule out a wide region in the currently allowed thermal axion window. Our results therefore, strongly support multi messenger searches of axions and neutrino properties, together with joint analyses of their expected sensitivities.
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Marco-Hernandez, R., Bau, M., Ferrari, M., Ferrari, V., Pedersen, F., & Soby, L. (2017). A Low-Noise Charge Amplifier for the ELENA Trajectory, Orbit, and Intensity Measurement System. IEEE Trans. Nucl. Sci., 64(9), 2465–2473.
Abstract: A low-noise head amplifier has been developed for the extra low energy antiproton ring beam trajectory, orbit, and intensity measurement system at CERN. This system is based on 24 double-electrode electrostatic beam position monitors installed around the ring. A head amplifier is placed close to each beam position monitor to amplify the electrode signals and generate a difference and a sum signal. These signals are sent to the digital acquisition system, about 50 m away from the ring, where they are digitized and further processed. The beam position can be measured by dividing the difference signal by the sum signal while the sum signal gives information relative to the beam intensity. The head amplifier consists of two discrete charge preamplifiers with junction field effect transistor (JFET) inputs, a sum and a difference stage, and two cable drivers. Special attention has been paid to the amplifier printed circuit board design to minimize the parasitic capacitances and inductances at the charge amplifier stages to meet the gain and noise requirements. The measurements carried out on the head amplifier showed a gain of 40.5 and 46.5 dB for the sum and difference outputs with a bandwidth from 200 Hz to 75 MHz and an input voltage noise density lower than 400 pV/v Hz. Twenty head amplifiers have been already installed in the ring and they have been used to detect the first beam signals during the first commissioning stage in November 2016.
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Aliaga, R. J. (2017). Real-Time Estimation of Zero Crossings of Sampled Signals for Timing Using Cubic Spline Interpolation. IEEE Trans. Nucl. Sci., 64(8), 2414–2422.
Abstract: A scheme is proposed for hardware estimation of the location of zero crossings of sampled signals with subsample resolution for timing applications, which consists of interpolating the signal with a cubic spline near the zero crossing and then finding the root of the resulting polynomial. An iterative algorithm based on the bisection method is presented that obtains one bit of the result per step and admits an efficient digital implementation using fixed-point representation. In particular, the root estimation iteration involves only two additions, and the initial values can be obtained from finite impulse response (FIR) filters with certain symmetry properties. It is shown that this allows online real-time estimation of timestamps in free-running sampling detector systems with improved accuracy with respect to the more common linear interpolation. The method is evaluated with simulations using ideal and real timing signals, and estimates are given for the resource usage and speed of its implementation.
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Guadilla, V., Algora, A., Estienne, M., Fallot, M., Gelletly, W., Porta, A., et al. (2024). First measurements with a new fl-electron detector for spectral shape studies. J. Instrum., 19(2), P02027–21pp.
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.
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Conde, D., Castillo, F. L., Escobar, C., García, C., Garcia Navarro, J. E., Sanz, V., et al. (2023). Forecasting Geomagnetic Storm Disturbances and Their Uncertainties Using Deep Learning. Space Weather, 21(11), e2023SW003474–27pp.
Abstract: Severe space weather produced by disturbed conditions on the Sun results in harmful effects both for humans in space and in high-latitude flights, and for technological systems such as spacecraft or communications. Also, geomagnetically induced currents (GICs) flowing on long ground-based conductors, such as power networks, potentially threaten critical infrastructures on Earth. The first step in developing an alarm system against GICs is to forecast them. This is a challenging task given the highly non-linear dependencies of the response of the magnetosphere to these perturbations. In the last few years, modern machine-learning models have shown to be very good at predicting magnetic activity indices. However, such complex models are on the one hand difficult to tune, and on the other hand they are known to bring along potentially large prediction uncertainties which are generally difficult to estimate. In this work we aim at predicting the SYM-H index characterizing geomagnetic storms multiple-hour ahead, using public interplanetary magnetic field (IMF) data from the Sun-Earth L1 Lagrange point and SYM-H data. We implement a type of machine-learning model called long short-term memory (LSTM) network. Our scope is to estimate the prediction uncertainties coming from a deep-learning model in the context of forecasting the SYM-H index. These uncertainties will be essential to set reliable alarm thresholds. The resulting uncertainties turn out to be sizable at the critical stages of the geomagnetic storms. Our methodology includes as well an efficient optimization of important hyper-parameters of the LSTM network and robustness tests.
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