Davidek, T., & Fiorini, L. (2020). Search for Lepton-Flavor-Violating Decays of Bosons With the ATLAS Detector. Front. Physics, 8, 149–13pp.
Abstract: The quest for lepton-flavor-violating processes at the LHC represents one of the key searches for new physics beyond the Standard Model. This review summarizes the direct searches for lepton-flavor-violating decays of heavy bosons with the ATLAS detector, using proton-proton collisions at the center-of-mass energy of 13 TeV.
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KM3NeT Collaboration(Aiello, S. et al), Alves Garre, S., Calvo, D., Carretero, V., Colomer, M., Corredoira, I., et al. (2020). gSeaGen: The KM3NeT GENIE-based code for neutrino telescopes. Comput. Phys. Commun., 256, 107477–15pp.
Abstract: The gSeaGen code is a GENIE-based application developed to efficiently generate high statistics samples of events, induced by neutrino interactions, detectable in a neutrino telescope. The gSeaGen code is able to generate events induced by all neutrino flavours, considering topological differences between tracktype and shower-like events. Neutrino interactions are simulated taking into account the density and the composition of the media surrounding the detector. The main features of gSeaGen are presented together with some examples of its application within the KM3NeT project. Program summary Program Title: gSeaGen CPC Library link to program files: http://dx.doi.org/10.17632/ymgxvy2br4.1 Licensing provisions: GPLv3 Programming language: C++ External routines/libraries: GENIE [1] and its external dependencies. Linkable to MUSIC [2] and PROPOSAL [3]. Nature of problem: Development of a code to generate detectable events in neutrino telescopes, using modern and maintained neutrino interaction simulation libraries which include the state-of-the-art physics models. The default application is the simulation of neutrino interactions within KM3NeT [4]. Solution method: Neutrino interactions are simulated using GENIE, a modern framework for Monte Carlo event generators. The GENIE framework, used by nearly all modern neutrino experiments, is considered as a reference code within the neutrino community. Additional comments including restrictions and unusual features: The code was tested with GENIE version 2.12.10 and it is linkable with release series 3. Presently valid up to 5 TeV. This limitation is not intrinsic to the code but due to the present GENIE valid energy range. References: [1] C. Andreopoulos at al., Nucl. Instrum. Meth. A614 (2010) 87. [2] P. Antonioli et al., Astropart. Phys. 7 (1997) 357. [3] J. H. Koehne et al., Comput. Phys. Commun. 184 (2013) 2070. [4] S. Adrian-Martinez et al., J. Phys. G: Nucl. Part. Phys. 43 (2016) 084001.
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Ruhr, F. et al, Escobar, C., & Miñano, M. (2020). Testbeam studies of barrel and end-cap modules for the ATLAS ITk strip detector before and after irradiation. Nucl. Instrum. Methods Phys. Res. A, 979, 164430–6pp.
Abstract: In order to cope with the occupancy and radiation doses expected at the High-Luminosity LHC, the ATLAS experiment will replace its Inner Detector with an all-silicon Inner Tracker (ITk), consisting of pixel and strip subsystems. In the last two years, several prototype ITk strip modules have been tested using beams of high energy electrons produced at the DESY-II testbeam facility. Tracking was provided by EUDET telescopes. The modules tested are built from two sensor types: the rectangular ATLAS17LS, which will be used in the outer layers of the central barrel region of the detector, and the annular ATLAS12EC, which will be used in the innermost ring (R0) of the forward region. Additionally, a structure with two RO modules positioned back-to-back has been measured, demonstrating space point reconstruction using the stereo angle of the strips. Finally, one barrel and one RO module have been measured after irradiation to 40% beyond the expected end-of-lifetime fluence. The data obtained allow for thorough tests of the module performance, including charge collection, noise occupancy, detection efficiency, and tracking performance. The results give confidence that the ITk strip detector will meet the requirements of the ATLAS experiment.
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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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ANTARES Collaboration(Adrian-Martinez, S. et al), Aguilar, J. A., Bigongiari, C., Dornic, D., Emanuele, U., Gomez-Gonzalez, J. P., et al. (2011). First Search For Point Sources Of High-Energy Cosmic Neutrinos With The Antares Neutrino Telescope. Astrophys. J. Lett., 743(1), L14–6pp.
Abstract: Results are presented of a search for cosmic sources of high-energy neutrinos with the ANTARES neutrino telescope. The data were collected during 2007 and 2008 using detector configurations containing between 5 and 12 detection lines. The integrated live time of the analyzed data is 304 days. Muon tracks are reconstructed using a likelihood-based algorithm. Studies of the detector timing indicate a median angular resolution of 0.5 +/- 0.1 deg. The neutrino flux sensitivity is 7.5 x 10(-8)(E(v)/GeV)(-2) GeV(-1) s(-1) cm(-2) for the part of the sky that is always visible (delta < -48 deg), which is better than limits obtained by previous experiments. No cosmic neutrino sources have been observed.
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