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Author ANTARES Collaboration (Albert, A. et al); Barrios-Marti, J.; Coleiro, A.; Colomer, M.; Hernandez-Rey, J.J.; Illuminati, G.; Lotze, M.; Zornoza, J.D.; Zuñiga, J. url  doi
openurl 
  Title The search for high-energy neutrinos coincident with fast radio bursts with the ANTARES neutrino telescope Type Journal Article
  Year 2019 Publication Monthly Notices of the Royal Astronomical Society Abbreviated Journal Mon. Not. Roy. Astron. Soc.  
  Volume 482 Issue 1 Pages 184-193  
  Keywords (up) acceleration of particles; neutrinos; astroparticle physics; radio continuum: transients; methods: data analysis  
  Abstract In the past decade, a new class of bright transient radio sources with millisecond duration has been discovered. The origin of these so-called fast radio bursts (FRBs) is still a mystery, despite the growing observational efforts made by various multiwavelength and multimessenger facilities. To date, many models have been proposed to explain FRBs, but neither the progenitors nor the radiative and the particle acceleration processes at work have been clearly identified. In this paper, we assess whether hadronic processes may occur in the vicinity of the FRB source. If they do, FRBs may contribute to the high-energy cosmic-ray and neutrino fluxes. A search for these hadronic signatures was carried out using the ANTARES neutrino telescope. The analysis consists in looking for high-energy neutrinos, in the TeV-PeV regime, that are spatially and temporally coincident with the detected FRBs. Most of the FRBs discovered in the period 2013-2017 were in the field of view of the ANTARES detector, which is sensitive mostly to events originating from the Southern hemisphere. From this period, 12 FRBs were selected and no coincident neutrino candidate was observed. Upper limits on the per-burst neutrino fluence were derived using a power-law spectrum, dN/DE nu proportional to E-nu(-gamma), for the incoming neutrino flux, assuming spectral indexes gamma = 1.0, 2.0, 2.5. Finally, the neutrino energy was constrained by computing the total energy radiated in neutrinos, assuming different distances for the FRBs. Constraints on the neutrino fluence and on the energy released were derived from the associated null results.  
  Address [Turpin, D.] Chinese Acad Sci, Natl Astron Observ, Key Lab Space Astron & Technol, Beijing 100101, Peoples R China, Email: dornic@cppm.in2p3.fr;  
  Corporate Author Thesis  
  Publisher Oxford Univ Press Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0035-8711 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000454575300014 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 3860  
Permanent link to this record
 

 
Author Stoppa, F.; Ruiz de Austri, R.; Vreeswijk, P.; Bhattacharyya, S.; Caron, S.; Bloemen, S.; Zaharijas, G.; Principe, G.; Vodeb, V.; Groot, P.J.; Cator, E.; Nelemans, G. url  doi
openurl 
  Title AutoSourceID-FeatureExtractor Optical image analysis using a two-step mean variance estimation network for feature estimation and uncertainty characterisation Type Journal Article
  Year 2023 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.  
  Volume 680 Issue Pages A108 - 14pp  
  Keywords (up) astronomical databases: miscellaneous; methods: data analysis; stars: imaging; techniques: image processing  
  Abstract Aims. In astronomy, machine learning has been successful in various tasks such as source localisation, classification, anomaly detection, and segmentation. However, feature regression remains an area with room for improvement. We aim to design a network that can accurately estimate sources' features and their uncertainties from single-band image cutouts, given the approximated locations of the sources provided by the previously developed code AutoSourceID-Light (ASID-L) or other external catalogues. This work serves as a proof of concept, showing the potential of machine learning in estimating astronomical features when trained on meticulously crafted synthetic images and subsequently applied to real astronomical data.Methods. The algorithm presented here, AutoSourceID-FeatureExtractor (ASID-FE), uses single-band cutouts of 32x32 pixels around the localised sources to estimate flux, sub-pixel centre coordinates, and their uncertainties. ASID-FE employs a two-step mean variance estimation (TS-MVE) approach to first estimate the features and then their uncertainties without the need for additional information, for example the point spread function (PSF). For this proof of concept, we generated a synthetic dataset comprising only point sources directly derived from real images, ensuring a controlled yet authentic testing environment.Results. We show that ASID-FE, trained on synthetic images derived from the MeerLICHT telescope, can predict more accurate features with respect to similar codes such as SourceExtractor and that the two-step method can estimate well-calibrated uncertainties that are better behaved compared to similar methods that use deep ensembles of simple MVE networks. Finally, we evaluate the model on real images from the MeerLICHT telescope and the Zwicky Transient Facility (ZTF) to test its transfer learning abilities.  
  Address [Stoppa, F.; Vreeswijk, P.; Bloemen, S.; Groot, P. J.; Nelemans, G.] Radboud Univ Nijmegen, Dept Astrophys, IMAPP, POB 9010, NL-6500 GL Nijmegen, Netherlands, Email: f.stoppa@astro.ru.nl  
  Corporate Author Thesis  
  Publisher Edp Sciences S A Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0004-6361 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001131898100003 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5887  
Permanent link to this record
 

 
Author Pierre Auger Collaboration (Aab, A. et al); Pastor, S. url  doi
openurl 
  Title A search for point sources of EeV photons Type Journal Article
  Year 2014 Publication Astrophysical Journal Abbreviated Journal Astrophys. J.  
  Volume 789 Issue 2 Pages 160 - 12pp  
  Keywords (up) astroparticle physics; cosmic rays; methods: data analysis  
  Abstract Measurements of air showers made using the hybrid technique developed with the fluorescence and surface detectors of the Pierre Auger Observatory allow a sensitive search for point sources of EeV photons anywhere in the exposed sky. A multivariate analysis reduces the background of hadronic cosmic rays. The search is sensitive to a declination band from -85 degrees to +20 degrees, in an energy range from 10(17.3) eV to 10(18.5) eV. No photon point source has been detected. An upper limit on the photon flux has been derived for every direction. The mean value of the energy flux limit that results from this, assuming a photon spectral index of -2, is 0.06 eV cm(-2) s(-1), and no celestial direction exceeds 0.25 eV cm(-2) s(-1). These upper limits constrain scenarios in which EeV cosmic ray protons are emitted by non-transient sources in the Galaxy.  
  Address [Aab, A.; Buchholz, P.; Erfani, M.; Froehlich, U.; Heimann, P.; Homola, P.; Kuempel, D.; Niechciol, M.; Ochilo, L.; Risse, M.; Yushkov, A.; Ziolkowski, M.] Univ Siegen, D-57068 Siegen, Germany  
  Corporate Author Thesis  
  Publisher Iop Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0004-637x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000338674900069 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 1842  
Permanent link to this record
 

 
Author Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. url  doi
openurl 
  Title Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge Type Journal Article
  Year 2021 Publication Astronomy & Astrophysics Abbreviated Journal Astron. Astrophys.  
  Volume 656 Issue Pages A62 - 18pp  
  Keywords (up) catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing  
  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.  
  Address [Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com  
  Corporate Author Thesis  
  Publisher Edp Sciences S A Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0004-6361 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000725877600001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 5053  
Permanent link to this record
 

 
Author Pierre Auger Collaboration (Abreu, P. et al); Pastor, S. url  doi
openurl 
  Title A search for point sources of EeV neutrons Type Journal Article
  Year 2012 Publication Astrophysical Journal Abbreviated Journal Astrophys. J.  
  Volume 760 Issue 2 Pages 148 - 11pp  
  Keywords (up) cosmic rays; Galaxy: disk; methods: data analysis  
  Abstract A thorough search of the sky exposed at the Pierre Auger Cosmic Ray Observatory reveals no statistically significant excess of events in any small solid angle that would be indicative of a flux of neutral particles from a discrete source. The search covers from -90 degrees to +15 degrees in declination using four different energy ranges above 1 EeV (10(18) eV). The method used in this search is more sensitive to neutrons than to photons. The upper limit on a neutron flux is derived for a dense grid of directions for each of the four energy ranges. These results constrain scenarios for the production of ultrahigh energy cosmic rays in the Galaxy.  
  Address [Abreu, P.; Andringa, S.; Assis, P.; Brogueira, P.; Cazon, L.; Conceicao, R.; Diogo, F.; Espadanal, J.; Goncalves, P.; Pimenta, M.; Santo, C. E.; Santos, E.; Tome, B.] Univ Tecn Lisboa, LIP, Lisbon, Portugal  
  Corporate Author Thesis  
  Publisher Iop Publishing Ltd Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0004-637x ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000311217000052 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 1218  
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