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KM3NeT Collaboration (Aiello, S. et al); Alves Garre, S.; Calvo, D.; Carretero, V.; Colomer, M.; Garcia Soto, A.; Gozzini, S.R.; Hernandez-Rey, J.J.; Khan Chowdhury, N.R.; Lazo, A.; Manczak, J.; Palacios Gonzalez, J.; Pieterse, C.; Real, D.; Salesa Greus, F.; Sanchez Losa, A.; Zornoza, J.D.; Zuñiga, J. |
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Title |
Implementation and first results of the KM3NeT real-time core-collapse supernova neutrino search |
Type |
Journal Article |
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Year |
2022 |
Publication |
European Physical Journal C |
Abbreviated Journal |
Eur. Phys. J. C |
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Volume |
82 |
Issue |
4 |
Pages |
317 - 16pp |
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Abstract |
The KM3NeT research infrastructure is unconstruction in the Mediterranean Sea. KM3NeT will study atmospheric and astrophysical neutrinos with two multi-purpose neutrino detectors, ARCA and ORCA, primarily aimed at GeV-PeV neutrinos. Thanks to the multi-photomultiplier tube design of the digital optical modules, KM3NeT is capable of detecting the neutrino burst from a Galactic or near-Galactic core-collapse supernova. This potential is already exploitable with the first detection units deployed in the sea. This paper describes the real-time implementation of the supernova neutrino search, operating on the two KM3NeT detectors since the first months of 2019. A quasi-online astronomy analysis is introduced to study the time profile of the detected neutrinos for especially significant events. The mechanism of generation and distribution of alerts, as well as the integration into the SNEWS and SNEWS 2.0 global alert systems, are described. The approach for the follow-up of external alerts with a search for a neutrino excess in the archival data is defined. Finally, an overview of the current detector capabilities and a report after the first two years of operation are given. |
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Address |
[Aiello, S.; Bruno, R.; Leonora, E.; Longhitano, F.; Randazzo, N.] Ist Nazl Fis Nucl, Sez Catania, Via Santa Sofia 64, I-95123 Catania, Italy, Email: lincetto@astro.ruhr-uni-bochum.de; |
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Springer |
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English |
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1434-6044 |
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Conference |
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Notes |
WOS:000780973500001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5197 |
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Author |
KM3NeT Collaboration (Aiello, S. et al); Alves Garre, S.; Calvo, D.; Carretero, V.; Garcia Soto, A.; Gozzini, S.R.; Hernandez-Rey, J.J.; Khan Chowdhury, N.R.; Lazo, A.; Manczak, J.; Palacios Gonzalez, J.; Pastor Gomez, E.J.; Rahaman, U.; Real, D.; Salesa Greus, F.; Sanchez Losa, A.; Zornoza, J.D.; Zuñiga, J. |
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Title |
First observation of the cosmic ray shadow of the Moon and the Sun with KM3NeT/ORCA |
Type |
Journal Article |
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Year |
2023 |
Publication |
European Physical Journal C |
Abbreviated Journal |
Eur. Phys. J. C |
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Volume |
83 |
Issue |
4 |
Pages |
344 - 9pp |
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Abstract |
This article reports the first observation of the Moon and the Sun shadows in the sky distribution of cosmicray induced muons measured by the KM3NeT/ORCA detector. The analysed data-taking period spans from February 2020 to November 2021, when the detector had 6 Detection Units deployed at the bottom of the Mediterranean Sea, each composed of 18 Digital Optical Modules. The shadows induced by theMoon and the Sun were detected at their nominal position with a statistical significance of 4.2 sigma and 6.2 sigma, and an angular resolution of sigma(res) = 0.49 degrees and sigma(res) = 0.66 degrees, respectively, consistent with the prediction of 0.53 degrees from simulations. This early result confirms the effectiveness of the detector calibration, in time, position and orientation and the accuracy of the event direction reconstruction. This also demonstrates the performance and the competitiveness of the detector in terms of pointing accuracy and angular resolution. |
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Address |
[Aiello, S.; Bruno, R.; Leonora, E.; Longhitano, F.; Randazzo, N.] INFN, Sez Catania, Via Santa Sofia 64, I-95123 Catania, Italy, Email: brunner@cppm.in2p3.fr; |
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Springer |
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English |
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ISSN |
1434-6044 |
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Conference |
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Notes |
WOS:001055357200004 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5631 |
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Author |
KM3NeT Collaboration (Aiello, S. et al); Alves Garre, S.; Bariego-Quintana, A.; Calvo, D.; Carretero, V.; Garcia Soto, A.; Gozzini, S.R.; Hernandez-Rey, J.J.; Lazo, A.; Lessing, N.; Manczak, J.; Palacios Gonzalez, J.; Pastor Gomez, E.J.; Rahaman, U.; Real, D.; Saina, A.; Salesa Greus, F.; Sanchez Losa, A.; Zornoza, J.D.; Zuñiga, J. |
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Title |
Searches for neutrino counterparts of gravitational waves from the LIGO/Virgo third observing run with KM3NeT |
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Journal Article |
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Year |
2024 |
Publication |
Journal of Cosmology and Astroparticle Physics |
Abbreviated Journal |
J. Cosmol. Astropart. Phys. |
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Volume |
04 |
Issue |
4 |
Pages |
026 - 28pp |
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Keywords |
neutrino astronomy; gravitational waves / sources; neutrino experiments |
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Abstract |
The KM3NeT neutrino telescope is currently being deployed at two different sites in the Mediterranean Sea. First searches for astrophysical neutrinos have been performed using data taken with the partial detector configuration already in operation. The paper presents the results of two independent searches for neutrinos from compact binary mergers detected during the third observing run of the LIGO and Virgo gravitational wave interferometers. The first search looks for a global increase in the detector counting rates that could be associated with inverse beta decay events generated by MeV-scale electron anti -neutrinos. The second one focuses on upgoing track -like events mainly induced by muon (anti -)neutrinos in the GeV-TeV energy range. Both searches yield no significant excess for the sources in the gravitational wave catalogs. For each source, upper limits on the neutrino flux and on the total energy emitted in neutrinos in the respective energy ranges have been set. Stacking analyses of binary black hole mergers and neutron star -black hole mergers have also been performed to constrain the characteristic neutrino emission from these categories. |
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Address |
[Aiello, S.; Bruno, R.; Leonora, E.; Longhitano, F.; Randazzo, N.; Sinopoulou, A.; Tosta e Melo, I] INFN, Sez Catania, Via Santa Sofia 64, I-95123 Catania, Italy, Email: lestum@cppm.in2p3.fr; |
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Publisher |
IOP Publishing Ltd |
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English |
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Series Volume |
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Edition |
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ISSN |
1475-7516 |
ISBN |
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Conference |
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Notes |
WOS:001208840500002 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
6115 |
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Author |
KM3NeT Collaboration (Aiello, S. et al); Barrios-Marti, J.; Calvo, D.; Coleiro, A.; Colomer, M.; Gozzini, S.R.; Hernandez-Rey, J.J.; Illuminati, G.; Khan-Chowdhury, N.R.; Lotze, M.; Perez Romero, J.; Real, D.; Thakore, T.; Zornoza, J.D.; Zuñiga, J. |
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Title |
Characterisation of the Hamamatsu photomultipliers for the KM3NeT Neutrino Telescope |
Type |
Journal Article |
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Year |
2018 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
13 |
Issue |
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Pages |
P05035 - 17pp |
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Keywords |
Cherenkov detectors; Large detector systems for particle and astroparticle physics; Neutrino detectors; Photon detectors for UV, visible and IR photons (vacuum) |
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Abstract |
The Hamamatsu R12199-023-inch photomultiplier tube is the photodetector chosen for the first phase of the KM3NeT neutrino telescope. About 7000 photomultipliers have been characterised for dark count rate, timing spread and spurious pulses. The quantum efficiency, the gain and the peak-to-valley ratio have also been measured for a sub-sample in order to determine parameter values needed as input to numerical simulations of the detector. |
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Address |
[Morganti, M.] Accademia Navale Livorno, Viale Italia 72, I-57100 Livorno, Italy, Email: oleg.kalekin@physik.uni-erlangen.de; |
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Publisher |
Iop Publishing Ltd |
Place of Publication |
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English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000433886900001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
3601 |
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| Permanent link to this record |
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Author |
KM3NeT Collaboration (Aiello, S. et al); Alves Garre, S.; Calvo, D.; Carretero, V.; Colomer, M.; Corredoira, I; Gozzini, S.R.; Hernandez-Rey, J.J.; Illuminati, G.; Khan Chowdhury, N.R.; Manczak, J.; Pieterse, C.; Real, D.; Salesa Greus, F.; Thakore, T.; Zornoza, J.D.; Zuñiga, J. |
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Title |
Event reconstruction for KM3NeT/ORCA using convolutional neural networks |
Type |
Journal Article |
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Year |
2020 |
Publication |
Journal of Instrumentation |
Abbreviated Journal |
J. Instrum. |
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Volume |
15 |
Issue |
10 |
Pages |
P10005 - 39pp |
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Keywords |
Cherenkov detectors; Large detector systems for particle and astroparticle physics; Neutrino detectors; Performance of High Energy Physics Detectors |
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Abstract |
The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches. |
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Address |
[Aiello, S.; Leonora, E.; Longhitano, F.; Randazzo, N.] Ist Nazl Fis Nucl, Sez Catania, Via Santa Sofia 64, I-95123 Catania, Italy, Email: thomas.eberl@fau.de; |
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Corporate Author |
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Thesis |
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Publisher |
Iop Publishing Ltd |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
1748-0221 |
ISBN |
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Area |
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Expedition |
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Conference |
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Notes |
WOS:000577278000005 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
4570 |
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| Permanent link to this record |
