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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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NEXT Collaboration(Monrabal, F. et al), Laing, A., Alvarez, V., Benlloch-Rodriguez, J. M., Carcel, S., Carrion, J. V., et al. (2018). The NEXT White (NEW) detector. J. Instrum., 13, P12010–38pp.
Abstract: Conceived to host 5 kg of xenon at a pressure of 15 bar in the fiducial volume, the NEXT-White apparatus is currently the largest high pressure xenon gas TPC using electroluminescent amplification in the world. It is also a 1:2 scale model of the NEXT-100 detector for Xe-136 beta beta 0 nu decay searches, scheduled to start operations in 2019. Both detectors measure the energy of the event using a plane of photomultipliers located behind a transparent cathode. They can also reconstruct the trajectories of charged tracks in the dense gas of the TPC with the help of a plane of silicon photomultipliers located behind the anode. A sophisticated gas system, common to both detectors, allows the high gas purity needed to guarantee a long electron lifetime. NEXT-White has been operating since October 2016 at the Laboratorio Subterraneo de Canfranc (LSC), in Spain. This paper describes the detector and associated infrastructures, as well as the main aspects of its initial operation.
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Oset, E., Ramos, A., Garzon, E. J., Molina, R., Tolos, L., Xiao, C. W., et al. (2012). Interaction of vector mesons with baryons and nuclei. Int. J. Mod. Phys. E, 21(11), 1230011–18pp.
Abstract: After some short introductory remarks on particular issues on the vector mesons in nuclei, in this paper, we present a short review of recent developments concerning the interaction of vector mesons with baryons and with nuclei from a modern perspective using the local hidden gauge formalism for the interaction of vector mesons. We present results for the vector-baryon interaction and in particular for the resonances which appear as composite states, dynamically generated from the interaction of vector mesons with baryons, taking also the mixing of these states with pseudoscalars and baryons into account. We then venture into the charm sector, reporting on hidden charm baryon states around 4400 MeV, generated from the interaction of vector mesons and baryons with charm, which have a strong repercussion on the properties of the J/Psi N interaction. We also address the interaction of K* with nuclei and make suggestions to measure the predicted huge width in the medium by means of transparency ratio. The formalism is extended to study the phenomenon of J/psi suppression in nuclei via J/psi photo-production reactions.
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Ortiz Arciniega, J. L., Carrio, F., & Valero, A. (2019). FPGA implementation of a deep learning algorithm for real-time signal reconstruction in particle detectors under high pile-up conditions. J. Instrum., 14, P09002–13pp.
Abstract: The analog signals generated in the read-out electronics of particle detectors are shaped prior to the digitization in order to improve the signal to noise ratio (SNR). The real amplitude of the analog signal is then obtained using digital filters, which provides information about the energy deposited in the detector. The classical digital filters have a good performance in ideal situations with Gaussian electronic noise and no pulse shape distortion. However, high-energy particle colliders, such as the Large Hadron Collider (LHC) at CERN, can produce multiple simultaneous events, which produce signal pileup. The performance of classical digital filters deteriorates in these conditions since the signal pulse shape gets distorted. In addition, this type of experiments produces a high rate of collisions, which requires high throughput data acquisitions systems. In order to cope with these harsh requirements, new read-out electronics systems are based on high-performance FPGAs, which permit the utilization of more advanced real-time signal reconstruction algorithms. In this paper, a deep learning method is proposed for real-time signal reconstruction in high pileup particle detectors. The performance of the new method has been studied using simulated data and the results are compared with a classical FIR filter method. In particular, the signals and FIR filter used in the ATLAS Tile Calorimeter are used as benchmark. The implementation, resources usage and performance of the proposed Neural Network algorithm in FPGA are also presented.
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Oliveira, C. A. B., Sorel, M., Martin-Albo, J., Gomez-Cadenas, J. J., Ferreira, A. L., & Veloso, J. F. C. A. (2011). Energy resolution studies for NEXT. J. Instrum., 6, P05007–13pp.
Abstract: This work aims to present the current state of simulations of electroluminescence (EL) produced in gas-based detectors with special interest for NEXT – Neutrino Experiment with a Xenon TPC. NEXT is a neutrinoless double beta decay experiment, thus needs outstanding energy resolution which can be achieved by using electroluminescence. The process of light production is reviewed and properties such as EL yield and associated fluctuations, excitation and electroluminescence efficiencies, and energy resolution, are calculated. An EL production region with a 5 mm width gap between two infinite parallel planes is considered, where a uniform electric field is produced. The pressure and temperature considered are 10 bar and 293 K, respectively. The results show that, even for low values of VUV photon detection efficiency, good energy resolution can be achieved: below 0.4% (FWHM) at Q(beta beta) = 2.458 MeV.
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Nygren, D. R., Jones, B. J. P., Lopez-March, N., Mei, Y., Psihas, F., & Renner, J. (2018). Neutrinoless double beta decay with 82SeF6 and direct ion imaging. J. Instrum., 13, P03015–23pp.
Abstract: We present a new neutrinoless double beta decay concept: the high pressure selenium hexafluoride gas time projection chamber. A promising new detection technique is outlined which combines techniques pioneered in high pressure xenon gas, such as topological discrimination, with the high Q-value afforded by the double beta decay isotope Se-82. The lack of free electrons in SeF6 mandates the use of an ion TPC. The microphysics of ion production and drift, which have many nuances, are explored. Background estimates are presented, suggesting that such a detector may achieve background indices of better than 1 count per ton per year in the region of interest at the 100 kg scale, and still better at the ton-scale.
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Morisi, S., & Peinado, E. (2011). Admixture of quasi-Dirac and Majorana neutrinos with tri-bimaximal mixing. Phys. Lett. B, 701(4), 451–457.
Abstract: We propose a realization of the so-called bimodal/schizophrenic model proposed recently. We assume 54, the permutation group of four objects as flavor symmetry giving tri-bimaximal lepton mixing at leading order. In these models the second massive neutrino state is assumed quasi-Dirac and the remaining neutrinos are Majorana states. In the case of inverse mass hierarchy, the lower bound on the neutrinoless double beta decay parameter m(ee) is about two times that of the usual lower bound, within the range of sensitivity of the next generation of experiments.
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Meloni, D., Morisi, S., & Peinado, E. (2011). Neutrino phenomenology and stable dark matter with A(4). Phys. Lett. B, 697(4), 339–342.
Abstract: We present a model based on the A(4) non-Abelian discrete symmetry leading to a predictive five-parameter neutrino mass matrix and providing a stable dark matter candidate. We found an interesting correlation among the atmospheric and the reactor angles which predicts theta(23) similar to pi/4for very small reactor angle and deviation from maximal atmospheric mixing for large theta(13). Only normal neutrino mass spectrum is possible and the effective mass entering the neutrinoless double beta decay rate is constrained to be vertical bar m(ee)vertical bar > 4 x 10(-4) eV.
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Mendoza, S., & Olmo, G. J. (2015). Astrophysical constraints and insights on extended relativistic gravity. Astrophys. Space Sci., 357(2), 133–6pp.
Abstract: We give precise details to support that observations of gravitational lensing at scales of individual, groups and clusters of galaxies can be understood in terms of nonNewtonian gravitational interactions with a relativistic structure compatible with the Einstein Equivalence Principle. This result is derived on very general grounds without knowing the underlying structure of the gravitational field equations. As such, any developed gravitational theory built to deal with these astrophysical scales needs to reproduce the obtained results of this article.
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n_TOF Collaboration(Mazzone, A. et al), Babiano-Suarez, V., Caballero, L., Domingo-Pardo, C., Ladarescu, I., & Tain, J. L. (2020). Measurement of the Gd-154(n, gamma) cross section and its astrophysical implications. Phys. Lett. B, 804, 135405–6pp.
Abstract: The neutron capture cross section of Gd-154 was measured from 1 eV to 300 keV in the experimental area located 185 m from the CERN n_TOF neutron spallation source, using a metallic sample of gadolinium, enriched to 67% in Gd-154. The capture measurement, performed with four C6D6 scintillation detectors, has been complemented by a transmission measurement performed at the GELINA time-of-flight facility (JRC-Geel), thus minimising the uncertainty related to sample composition. An accurate Maxwellian averaged capture cross section (MACS) was deduced over the temperature range of interest for s process nucleosynthesis modelling. We report a value of 880(50) mb for the MACS at kT = 30 keV, significantly lower compared to values available in literature. The new adopted Gd-154(n, gamma) cross section reduces the discrepancy between observed and calculated solar s-only isotopic abundances predicted by s-process nucleosynthesis models.
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