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Bertoldo, S., Maggioni, G., Raniero, W., Carraro, C., Riccetto, S., Sgarbossa, F., et al. (2021). New method for the production of thin and stable, segmented n plus contacts in HPGe detectors. Eur. Phys. J. A, 57(6), 177–10pp.
Abstract: The realization of pulsed-laser diffused, thin n+ contacts on high purity germanium (HPGe) and their successful segmentation is described. The contacts have been obtained by a laser-induced diffusion of Sb atoms, deposited by sputtering on Ge surface, and then segmented by means of a photolithographic technique. Three small prototypes of gamma ray detectors have been implemented, using the same n+ contact (laser diffused Sb) but with three different geometries and a B implanted p+ contact. Electrical and detection properties of the prototypes have been characterized, showing low leakage currents and good spectroscopy data with different gamma-ray sources. The stability of the detector performance has also been tested subjecting one of the prototypes to a typical annealing treatment.
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ANTARES Collaboration(Albert, A. et al), Colomer, M., Gozzini, R., Hernandez-Rey, J. J., Illuminati, G., Khan-Chowdhury, N. R., et al. (2021). Constraining the contribution of Gamma-Ray Bursts to the high-energy diffuse neutrino flux with 10 yr of ANTARES data. Mon. Not. Roy. Astron. Soc., 500(4), 5614–5628.
Abstract: Addressing the origin of the astrophysical neutrino flux observed by IceCube is of paramount importance. Gamma-Ray Bursts (GRBs) are among the few astrophysical sources capable of achieving the required energy to contribute to such neutrino flux through p gamma interactions. In this work, ANTARFS data have been used to search for upward going muon neutrinos in spatial and temporal coincidence with 784 GRBs occurred from 2007 to 2017. For each GRB, the expected neutrino flux has been calculated in the framework of the internal shock model and the impact of the lack of knowledge on the majority of source redshifts and on other intrinsic parameters of the emission mechanism has been quantified. It is found that the model parameters that set the radial distance where shock collisions occur have the largest impact on neutrino flux expectations. In particular, the bulk Lorentz factor of the source ejecta and the minimum variability time-scale are found to contribute significantly to the GRB-neutrino flux uncertainty. For the selected sources, ANTARES data have been analysed by maximizing the discovery probability of the stacking sample through an extended maximum-likelihood strategy. Since no neutrino event passed the quality cuts set by the optimization procedure, 90 per cent confidence level upper limits (with their uncertainty) on the total expected diffuse neutrino flux have been derived, according to the model. The GRB contribution to the observed diffuse astrophysical neutrino flux around 100 TeV is constrained to be less than 10 percent.
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HAWC Collaboration(Albert, A. et al), & Salesa Greus, F. (2021). A Survey of Active Galaxies at TeV Photon Energies with the HAWC Gamma-Ray Observatory. Astrophys. J., 907(2), 67–18pp.
Abstract: The High Altitude Water Cherenkov (HAWC) Gamma-Ray Observatory continuously detects TeV photons and particles within its large field of view, accumulating every day a deeper exposure of two-thirds of the sky. We analyzed 1523 days of HAWC live data acquired over four and a half years, in a follow-up analysis of 138 nearby (z < 0.3) active galactic nuclei from the Third Catalog of Hard Fermi-LAT sources culminating within 40 degrees of the zenith at Sierra Negra, the HAWC site. This search for persistent TeV emission used a maximum-likelihood analysis assuming intrinsic power-law spectra attenuated by pair production of gamma-ray photons with the extragalactic background light. HAWC clearly detects persistent emission from Mkn 421 and Mkn 501, the two brightest blazars in the TeV sky, at 65 sigma and 17 sigma level, respectively. Marginal evidence, just above the 3 sigma level, was found for three other known very high-energy emitters: the radio galaxy M87 and the BL Lac objects VER J0521+211 and 1ES 1215+303, the latter two at z similar to 0.1. We find a 4.2 sigma evidence for collective emission from the set of 30 previously reported very high-energy sources, with Mkn 421 and Mkn 501 excluded. Upper limits are presented for the sample under the power-law assumption and in the predefined (0.5-2.0), (2.0-8.0), and (8.0-32.0) TeV energy intervals.
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Arrechea, J., Delhom, A., & Jimenez-Cano, A. (2021). Inconsistencies in four-dimensional Einstein-Gauss-Bonnet gravity. Chin. Phys. C, 45(1), 013107–8pp.
Abstract: We attempt to clarify several aspects concerning the recently presented four-dimensional Einstein-Gauss-Bonnet gravity. We argue that the limiting procedure outlined in [Phys. Rev. Lett. 124, 081301 (2020)] generally involves ill-defined terms in the four dimensional field equations. Potential ways to circumvent this issue are discussed, alongside remarks regarding specific solutions of the theory. We prove that, although linear perturbations are well behaved around maximally symmetric backgrounds, the equations for second-order perturbations are ill-defined even around a Minkowskian background. Additionally, we perform a detailed analysis of the spherically symmetric solutions and find that the central curvature singularity can be reached within a finite proper time.
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Kasieczka, G. et al, & Sanz, V. (2021). The LHC Olympics 2020: a community challenge for anomaly detection in high energy physics. Rep. Prog. Phys., 84(12), 124201–64pp.
Abstract: A new paradigm for data-driven, model-agnostic new physics searches at colliders is emerging, and aims to leverage recent breakthroughs in anomaly detection and machine learning. In order to develop and benchmark new anomaly detection methods within this framework, it is essential to have standard datasets. To this end, we have created the LHC Olympics 2020, a community challenge accompanied by a set of simulated collider events. Participants in these Olympics have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly (or not). Methods made use of modern machine learning tools and were based on unsupervised learning (autoencoders, generative adversarial networks, normalizing flows), weakly supervised learning, and semi-supervised learning. This paper will review the LHC Olympics 2020 challenge, including an overview of the competition, a description of methods deployed in the competition, lessons learned from the experience, and implications for data analyses with future datasets as well as future colliders.
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