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Davesne, D., Pastore, A., & Navarro, J. (2023). Hartree-Fock Calculations in Semi-Infinite Matter with Gogny Interactions. Universe, 9(9), 398–11pp.
Abstract: Hartree-Fock equations in semi-infinite nuclear matter for finite range Gogny interactions are presented together with a detailed numerical scheme to solve them. The value of the surface energy is then extracted and given for standard Gogny interactions.
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Fernandez Casani, A., Garcia Montoro, C., Gonzalez de la Hoz, S., Salt, J., Sanchez, J., & Villaplana Perez, M. (2023). Big Data Analytics for the ATLAS EventIndex Project with Apache Spark. Comput. Math. Methods, 2023, 6900908–19pp.
Abstract: The ATLAS EventIndex was designed to provide a global event catalogue and limited event-level metadata for ATLAS experiment of the Large Hadron Collider (LHC) and their analysis groups and users during Run 2 (2015-2018) and has been running in production since. The LHC Run 3, started in 2022, has seen increased data-taking and simulation production rates, with which the current infrastructure would still cope but may be stretched to its limits by the end of Run 3. A new core storage service is being developed in HBase/Phoenix, and there is work in progress to provide at least the same functionality as the current one for increased data ingestion and search rates and with increasing volumes of stored data. In addition, new tools are being developed for solving the needed access cases within the new storage. This paper describes a new tool using Spark and implemented in Scala for accessing the big data quantities of the EventIndex project stored in HBase/Phoenix. With this tool, we can offer data discovery capabilities at different granularities, providing Spark Dataframes that can be used or refined within the same framework. Data analytic cases of the EventIndex project are implemented, like the search for duplicates of events from the same or different datasets. An algorithm and implementation for the calculation of overlap matrices of events across different datasets are presented. Our approach can be used by other higher-level tools and users, to ease access to the data in a performant and standard way using Spark abstractions. The provided tools decouple data access from the actual data schema, which makes it convenient to hide complexity and possible changes on the backed storage.
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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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Van Isacker, P., Algora, A., Vitéz-Sveiczer, A., Kiss, G. G., Orrigo, S. E. A., Rubio, B., et al. (2023). Gamow-Teller Beta Decay and Pseudo-SU(4) Symmetry. Symmetry-Basel, 15(11), 2001–15pp.
Abstract: We report on recent experimental results on beta decay into self-conjugate ( N = Z) nuclei with mass number 58 <= A <= 70. Super-allowed b decays from the J(pi) = 0(+) ground state of a Z = N + 2 parent nucleus are to the isobaric analogue state through so-called Fermi transitions and to J(pi) = 1(+) states by way of Gamow-Teller (GT) transitions. The operator of the latter decay is a generator of Wigner's SU(4) algebra and as a consequence GT transitions obey selection rules associated with this symmetry. Since SU(4) is progressively broken with increasing A, mainly as a consequence of the spinorbit interaction, this symmetry is not relevant for the nuclei considered here. We argue, however, that the pseudo-spin-orbit splitting can be small in nuclei with 58 <= A <= 70, in which case nuclear states exhibit an approximate pseudo-SU(4) symmetry. To test this conjecture, GT decay strength is calculated with use of a schematic Hamiltonian with pseudo-SU(4) symmetry. Some generic features of the GT beta decay due to pseudo-SU(4) symmetry are pointed out. The experimentally observed GT strength indicates a restoration of pseudo-SU(4) symmetry for A = 70.
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Gerbino, M. et al, Martinez-Mirave, P., Mena, O., Tortola, M., & Valle, J. W.. (2023). Synergy between cosmological and laboratory searches in neutrino physics. Phys. Dark Universe, 42, 101333–36pp.
Abstract: The intersection of the cosmic and neutrino frontiers is a rich field where much discovery space still remains. Neutrinos play a pivotal role in the hot big bang cosmology, influencing the dynamics of the universe over numerous decades in cosmological history. Recent studies have made tremendous progress in understanding some properties of cosmological neutrinos, primarily their energy density. Upcoming cosmological probes will measure the energy density of relativistic particles with higher precision, but could also start probing other properties of the neutrino spectra. When convolved with results from terrestrial experiments, cosmology can become even more acute at probing new physics related to neutrinos or even Beyond the Standard Model (BSM). Any discordance between laboratory and cosmological data sets may reveal new BSM physics and/or suggest alternative models of cosmology. We give examples of the intersection between terrestrial and cosmological probes in the neutrino sector, and briefly discuss the possibilities of what different laboratory experiments may see in conjunction with cosmological observatories.
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