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Choi, K. Y., Lopez-Fogliani, D. E., Muñoz, C., & Ruiz de Austri, R. (2010). Gamma-ray detection from gravitino dark matter decay in the μnu SSM. J. Cosmol. Astropart. Phys., 03(3), 028–14pp.
Abstract: The μnu SSM provides a solution to the mu-problem of the MSSM and explains the origin of neutrino masses by simply using right-handed neutrino superfields. Given that R-parity is broken in this model, the gravitino is a natural candidate for dark matter since its lifetime becomes much longer than the age of the Universe. We consider the implications of gravitino dark matter in the μnu SSM, analyzing in particular the prospects for detecting gamma rays from decaying gravitinos. If the gravitino explains the whole dark matter component, a gravitino mass larger than 20 GeV is disfavored by the isotropic diffuse photon background measurements. On the other hand, a gravitino with a mass range between 0.1 – 20 GeV gives rise to a signal that might be observed by the FERMI satellite. In this way important regions of the parameter space of the μnu SSM can be checked.
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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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Cui, Z. F., Zhang, J. L., Binosi, D., De Soto, F., Mezrag, C., Papavassiliou, J., et al. (2020). Effective charge from lattice QCD. Chin. Phys. C, 44(8), 083102–10pp.
Abstract: Using lattice configurations for quantum chromodynamics (QCD) generated with three domain-wall fermions at a physical pion mass, we obtain a parameter-free prediction of QCD 's renormalisation-group-invariant process-independent effective charge, (alpha) over cap (k(2)). Owing to the dynamical breaking of scale invariance, evident in the emergence of a gluon mass-scale, m(0) = 0.43(1) GeV, this coupling saturates at infrared momenta: (alpha) over cap/pi = 0.97(4). Amongst other things: (alpha) over cap (k(2)) is almost identical to the process-dependent (PD) effective charge defined via the Bjorken sum rule; and also that PD charge which, employed in the one-loop evolution equations, delivers agreement between pion parton distribution functions computed at the hadronic scale and experiment. The diversity of unifying roles played by (alpha) over cap (k(2)) suggests that it is a strong candidate for that object which represents the interaction strength in QCD at any given momentum scale; and its properties support a conclusion that QCD is a mathematically well-defined quantum field theory in four dimensions.
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Das, S., de Putter, R., Linder, E. V., & Nakajima, R. (2012). Weak lensing cosmology beyond Lambda CDM. J. Cosmol. Astropart. Phys., 11(11), 23pp.
Abstract: Weak gravitational lensing is one of the key probes of the cosmological model, dark energy, and dark matter, providing insight into both the cosmic expansion history and large scale structure growth history. Taking into account a broad spectrum of physics affecting growth – dynamical dark energy, extended gravity, neutrino masses, and spatial curvature – we analyze the cosmological constraints. Similarly we consider the effects of a range of systematic uncertainties, in shear measurement, photometric redshifts, intrinsic alignments, and the nonlinear power spectrum, on cosmological parameter extraction. We also investigate, and provide fitting formulas tor, the influence of survey parameters such as redshift depth, galaxy number densities, and sky area on the cosmological constraints in the beyond-ACDM parameter space. Finally, we examine the robustness of results for different fiducial cosmologies.
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Davesne, D., Pastore, A., & Navarro, J. (2014). Fitting (NLO)-L-3 pseudo-potentials through central plus tensor Landau parameters. J. Phys. G, 41(6), 065104–12pp.
Abstract: Landau parameters determined from phenomenological finite-range interactions are used to get an estimation of next-to-next-to-next-to-leading order ((NLO)-L-3) pseudo-potentials parameters. The parameter sets obtained in this way are shown to lead to consistent results concerning saturation properties. The uniqueness of this procedure is discussed, and an estimate of the error induced by the truncation at (NLO)-L-3 is given.
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