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Angles-Castillo, A., Perucho, M., Marti, J. M., & Laing, R. A. (2021). On the deceleration of Fanaroff-Riley Class I jets: mass loading of magnetized jets by stellar winds. Mon. Not. Roy. Astron. Soc., 500(1), 1512–1530.
Abstract: In this paper, we present steady-state relativistic magnetohydrodynamic simulations that include a mass-load term to study the process of jet deceleration. The mass load mimics the injection of a proton-electron plasma from stellar winds within the host galaxy into initially pair plasma jets, with mean stellar mass-losses ranging from 10(-14) to 10(-9) M-circle dot yr(-1). The spatial jet evolution covers similar to 500 pc from jet injection in the grid at 10 pc from the jet nozzle. Our simulations use a relativistic gas equation of state and a pressure profile for the ambient medium. We compare these simulations with previous dynamical simulations of relativistic, non-magnetized jets. Our results show that toroidal magnetic fields can prevent fast jet expansion and the subsequent embedding of further stars via magnetic tension. In this sense, magnetic fields avoid a runaway deceleration process. Furthermore, when the mass load is large enough to increase the jet density and produce fast, differential jet expansion, the conversion of magnetic energy flux into kinetic energy flux (i.e. magnetic acceleration), helps to delay the deceleration process with respect to non-magnetized jets. We conclude that the typical stellar population in elliptical galaxies cannot explain jet deceleration in classical Fanaroff-Riley type I radio galaxies. However, we observe a significant change in the jet composition, thermodynamical parameters, and energy dissipation along its evolution, even for moderate values of the mass load.
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Centelles Chulia, S., & Trautner, A. (2020). Asymmetric tri-bi-maximal mixing and residual symmetries. Mod. Phys. Lett. A, 35(35), 2050292–15pp.
Abstract: Asymmetric tri-bi-maximal mixing is a recently proposed, grand unified theory (GUT) based, flavor mixing scheme. In it, the charged lepton mixing is fixed by the GUT connection to down-type quarks and a T-13 flavor symmetry, while neutrino mixing is assumed to be tri-bi-maximal (TBM) with one additional free phase. Here we show that this additional free phase can be fixed by the residual flavor and CP symmetries of the effective neutrino mass matrix. We discuss how those residual symmetries can be unified with T-13 and identify the smallest possible unified flavor symmetries, namely (Z(13)xZ(13))(sic)D-12 and (Z(13)xZ(13))(sic)S-4. Sharp predictions are obtained for lepton mixing angles, CP violating phases and neutrinoless double beta decay.
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Al Kharusi, S. et al, & Colomer, M. (2021). SNEWS 2.0: a next-generation supernova early warning system for multi-messenger astronomy. New J. Phys., 23(3), 031201–34pp.
Abstract: The next core-collapse supernova in the Milky Way or its satellites will represent a once-in-a-generation opportunity to obtain detailed information about the explosion of a star and provide significant scientific insight for a variety of fields because of the extreme conditions found within. Supernovae in our galaxy are not only rare on a human timescale but also happen at unscheduled times, so it is crucial to be ready and use all available instruments to capture all possible information from the event. The first indication of a potential stellar explosion will be the arrival of a bright burst of neutrinos. Its observation by multiple detectors worldwide can provide an early warning for the subsequent electromagnetic fireworks, as well as signal to other detectors with significant backgrounds so they can store their recent data. The supernova early warning system (SNEWS) has been operating as a simple coincidence between neutrino experiments in automated mode since 2005. In the current era of multi-messenger astronomy there are new opportunities for SNEWS to optimize sensitivity to science from the next galactic supernova beyond the simple early alert. This document is the product of a workshop in June 2019 towards design of SNEWS 2.0, an upgraded SNEWS with enhanced capabilities exploiting the unique advantages of prompt neutrino detection to maximize the science gained from such a valuable event.
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Hall, O. et al, Agramunt, J., Algora, A., Domingo-Pardo, C., Morales, A. I., Rubio, B., et al. (2021). beta-delayed neutron emission of r-process nuclei at the N=82 shell closure. Phys. Lett. B, 816, 136266–7pp.
Abstract: Theoretical models of beta-delayed neutron emission are used as crucial inputs in r-process calculations. Benchmarking the predictions of these models is a challenge due to a lack of currently available experimental data. In this work the beta-delayed neutron emission probabilities of 33 nuclides in the important mass regions south and south-west of Sn-132 are presented, 16 for the first time. The measurements were performed at RIKEN using the Advanced Implantation Detector Array (AIDA) and the BRIKEN neutron detector array. The P-1n values presented constrain the predictions of theoretical models in the region, affecting the final abundance distribution of the second r-process peak at A approximate to 130.
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Salesa Greus, F., & Sanchez Losa, A. (2021). Multimessenger Astronomy with Neutrinos. Universe, 7(11), 397–11pp.
Abstract: Multimessenger astronomy is arguably the branch of the astroparticle physics field that has seen the most significant developments in recent years. In this manuscript, we will review the state-of-the-art, the recent observations, and the prospects and challenges for the near future. We will give special emphasis to the observation carried out with neutrino telescopes.
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Panes, B., Eckner, C., Hendriks, L., Caron, S., Dijkstra, K., Johannesson, G., et al. (2021). Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge. Astron. Astrophys., 656, A62–18pp.
Abstract: Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources.
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Folgado, M. G., & Sanz, V. (2022). Exploring the political pulse of a country using data science tools. J. Comput. Soc. Sci., 5, 987–1000.
Abstract: In this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train a Fully-Connected Neural Network (FCNN) to recognise the political affiliation of a tweet. The FCNN is able to predict the origin of the tweet with a precision in the range of 71-75%, and the political leaning (left or right) with a precision of around 90%. This study is meant to be viewed as an example of how to use Twitter data and different types of Data Science tools for a political analysis.
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DUNE Collaboration(Abud, A. A. et al), Antonova, M., Barenboim, G., Cervera-Villanueva, A., De Romeri, V., Fernandez Menendez, P., et al. (2022). Design, construction and operation of the ProtoDUNE-SP Liquid Argon TPC. J. Instrum., 17(1), P01005–111pp.
Abstract: The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber (LArTPC) that was constructed and operated in the CERN North Area at the end of the H4 beamline. This detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment (DUNE), which will be constructed at the Sandford Underground Research Facility (SURF) in Lead, South Dakota, U.S.A. The ProtoDUNE-SP detector incorporates full-size components as designed for DUNE and has an active volume of 7 x 6 x 7.2 m3. The H4 beam delivers incident particles with well-measured momenta and high-purity particle identification. ProtoDUNE-SP's successful operation between 2018 and 2020 demonstrates the effectiveness of the single-phase far detector design. This paper describes the design, construction, assembly and operation of the detector components.
Keywords: Noble liquid detectors (scintillation, ionization, double-phase); Photon detectors for UV; visible and IR photons (solid-state) (PIN diodes, APDs, Si-PMTs, G-APDs, CCDs, EBCCDs, EMCCDs, CMOS imagers, etc); Scintillators; scintillation and light emission processes (solid, gas and liquid scintillators); Time projection Chambers (TPC)
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Massimi, C., Cristallo, S., Domingo-Pardo, C., & Lederer-Woods, C. (2022). n_TOF: Measurements of Key Reactions of Interest to AGB Stars. Universe, 8(2), 100–19pp.
Abstract: In the last 20 years, the neutron time-of-flight facility nTOF at CERN has been providing relevant data for the astrophysical slow neutron capture process (s process). At nTOF, neutron-induced radiative capture (n,gamma) as well as (n,p) and (n,alpha) reaction cross sections are measured as a function of energy, using the time-of-flight method. Improved detection systems, innovative ideas and collaborations with other neutron facilities have lead to a considerable contribution of the n_TOF collaboration to studying the s process in asymptotic giant branch stars. Results have been reported for stable and radioactive samples, i.e.,Mg- 24,Mg-25,Mg-26, Al-26, S-33,Fe- 54,Fe-57, Ni-58,Ni-59,Ni-62,Ni-63, Ge-70,Ge-72,Ge-73, Zr-90,Zr-91,Zr-92,Zr-93,Zr-94,Zr-96, La-139, Ce-140, Pm-147, Sm-151,Gd- 154,Gd-155,Gd-157, Tm-171, Os-186,Os-187,Os-188, Au-197, Tl-203,Tl-204,Pb- 204,Pb-206,Pb-207 and Bi-209 isotopes, while others are being studied or planned to be studied in the near future. In this contribution, we present an overview of the most successful achievements, and an outlook of future challenging measurements, including ongoing detection system developments.
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Carrio, F. (2022). The Data Acquisition System for the ATLAS Tile Calorimeter Phase-II Upgrade Demonstrator. IEEE Trans. Nucl. Sci., 69(4), 687–695.
Abstract: The tile calorimeter (TileCal) is the central hadronic calorimeter of the ATLAS experiment at the large hadron collider (LHC). In 2025, the LHC will be upgraded leading to the high luminosity LHC (HL-LHC). The HL-LHC will deliver an instantaneous luminosity up to seven times larger than the LHC nominal luminosity. The ATLAS Phase-II upgrade (2025-2027) will accommodate the subdetectors to the HL-LHC requirements. As part of this upgrade, the majority of the TileCal on-detector and off-detector electronics will be replaced using a new readout strategy, where the on-detector electronics will digitize and transmit digitized detector data to the off-detector electronics at the bunch crossing frequency (40 MHz). In the counting rooms, the off-detector electronics will compute reconstructed trigger objects for the first-level trigger and will store the digitized samples in pipelined buffers until the reception of a trigger acceptance signal. The off-detector electronics will also distribute the LHC clock to the on-detector electronics embedded within the digital data stream. The TileCal Phase-II upgrade project has undertaken an extensive research and development program that includes the development of a Demonstrator module to evaluate the performance of the new clock and readout architecture envisaged for the HL-LHC. The Demonstrator module equipped with the latest version of the on-detector electronics was built and inserted into the ATLAS experiment. The Demonstrator module is operated and read out using a Tile PreProcessor (TilePPr) Demonstrator which enables backward compatibility with the present ATLAS Trigger and Data AcQuisition (TDAQ), and the timing, trigger, and command (TTC) systems. This article describes in detail the main hardware and firmware components of the clock distribution and data acquisition systems for the Demonstrator module, focusing on the TilePPr Demonstrator.
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