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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. doi  openurl
  Title Characterisation of the Hamamatsu photomultipliers for the KM3NeT Neutrino Telescope Type Journal Article
  Year 2018 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.  
  Volume 13 Issue Pages P05035 - 17pp  
  Keywords Cherenkov detectors; Large detector systems for particle and astroparticle physics; Neutrino detectors; Photon detectors for UV, visible and IR photons (vacuum)  
  Abstract (up) 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.  
  Address [Morganti, M.] Accademia Navale Livorno, Viale Italia 72, I-57100 Livorno, Italy, Email: oleg.kalekin@physik.uni-erlangen.de;  
  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 1748-0221 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000433886900001 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 3601  
Permanent link to this record
 

 
Author LHCb Collaboration (Aaij, R. et al); Jaimes Elles, S.J.; Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Rebollo De Miguel, M.; Sanderswood, I.; Zhuo, J. url  doi
openurl 
  Title Helium identification with LHCb Type Journal Article
  Year 2024 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.  
  Volume 19 Issue 2 Pages P02010 - 23pp  
  Keywords dE/dx detectors; Ion identification systems; Large detector systems for particle and astroparticle physics; Particle identification methods  
  Abstract (up) The identification of helium nuclei at LHCb is achieved using a method based on measurements of ionisation losses in the silicon sensors and timing measurements in the Outer Tracker drift tubes. The background from photon conversions is reduced using the RICH detectors and an isolation requirement. The method is developed using pp collision data at root s = 13 TeV recorded by the LHCb experiment in the years 2016 to 2018, corresponding to an integrated luminosity of 5.5 fb(-1). A total of around 10(5) helium and antihelium candidates are identified with negligible background contamination. The helium identification efficiency is estimated to be approximately 50% with a corresponding background rejection rate of up to O(10(12)). These results demonstrate the feasibility of a rich programme of measurements of QCD and astrophysics interest involving light nuclei.  
  Address [Egede, U.; Fujii, Y.; Hadavizadeh, T.; Henderson, R. D. L.; Lane, J. J.; Monk, M.; Song, R.; Walton, E. J.; Ward, J. A.] Monash Univ, Sch Phys & Astron, Melbourne, Vic, Australia, Email: rmoise@cern.ch  
  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 1748-0221 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001185791500006 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 6068  
Permanent link to this record
 

 
Author ATLAS Collaboration (Aad, G. et al); Alvarez Piqueras, D.; Cabrera Urban, S.; Castillo Gimenez, V.; Costa, M.J.; Fernandez Martinez, P.; Ferrer, A.; Fiorini, L.; Fuster, J.; Garcia, C.; Garcia Navarro, J.E.; Gonzalez de la Hoz, S.; Hernandez Jimenez, Y.; Higon-Rodriguez, E.; Irles Quiles, A.; Jimenez Pena, J.; Kaci, M.; King, M.; Lacasta, C.; Lacuesta, V.R.; Marti-Garcia, S.; Mitsou, V.A.; Moles-Valls, R.; Oliver Garcia, E.; Pedraza Lopez, S.; Perez Garcia-Estañ, M.T.; Romero Adam, E.; Ros, E.; Salt, J.; Sanchez Martinez, V.; Soldevila, U.; Sanchez, J.; Torro Pastor, E.; Valero, A.; Valladolid Gallego, E.; Valls Ferrer, J.A.; Vos, M. url  doi
openurl 
  Title Performance of b-jet identification in the ATLAS experiment Type Journal Article
  Year 2016 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.  
  Volume 11 Issue Pages P04008 - 126pp  
  Keywords Large detector systems for particle and astroparticle physics; Large detector-systems performance; Pattern recognition, cluster finding, calibration and fitting methods; Performance of High Energy Physics Detectors  
  Abstract (up) The identification of jets containing b hadrons is important for the physics programme of the ATLAS experiment at the Large Hadron Collider. Several algorithms to identify jets containing b hadrons are described, ranging from those based on the reconstruction of an inclusive secondary vertex or the presence of tracks with large impact parameters to combined tagging algorithms making use of multi-variate discriminants. An independent b-tagging algorithm based on the reconstruction of muons inside jets as well as the b-tagging algorithm used in the online trigger are also presented. The b-jet tagging efficiency, the c-jet tagging efficiency and the mistag rate for light flavour jets in data have been measured with a number of complementary methods. The calibration results are presented as scale factors defined as the ratio of the efficiency (or mistag rate) in data to that in simulation. In the case of b jets, where more than one calibration method exists, the results from the various analyses have been combined taking into account the statistical correlation as well as the correlation of the sources of systematic uncertainty.  
  Address [Jackson, P.; Lee, L.; Soni, N.; White, M. J.] Univ Adelaide, Dept Phys, Adelaide, SA, Australia  
  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 1748-0221 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000375746400027 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 2684  
Permanent link to this record
 

 
Author KM3NeT Collaboration (Aiello, S. et al); Calvo, D.; Coleiro, A.; Colomer, M.; Gozzini, S.R.; Hernandez-Rey, J.J.; Illuminati, G.; Khan Chowdhury, N.R.; Manczak, J.; Pieterse, C.; Real, D.; Thakore, T.; Zornoza, J.D.; Zuñiga, J. url  doi
openurl 
  Title The Control Unit of the KM3NeT Data Acquisition System Type Journal Article
  Year 2020 Publication Computer Physics Communications Abbreviated Journal Comput. Phys. Commun.  
  Volume 256 Issue Pages 107433 - 16pp  
  Keywords KM3NeT; Data acquisition control; Neutrino detector; Astroparticle detector; 07.05.Hd; 29.85.Ca  
  Abstract (up) The KM3NeT Collaboration runs a multi-site neutrino observatory in the Mediterranean Sea. Water Cherenkov particle detectors, deep in the sea and far off the coasts of France and Italy, are already taking data while incremental construction progresses. Data Acquisition Control software is operating off-shore detectors as well as testing and qualification stations for their components. The software, named Control Unit, is highly modular. It can undergo upgrades and reconfiguration with the acquisition running. Interplay with the central database of the Collaboration is obtained in a way that allows for data taking even if Internet links fail. In order to simplify the management of computing resources in the long term, and to cope with possible hardware failures of one or more computers, the KM3NeT Control Unit software features a custom dynamic resource provisioning and failover technology, which is especially important for ensuring continuity in case of rare transient events in multi-messenger astronomy. The software architecture relies on ubiquitous tools and broadly adopted technologies and has been successfully tested on several operating systems.  
  Address [Aiello, S.; Leonora, E.; Longhitano, F.; Randazzo, N.] Ist Nazl Fis Nucl, Sez Catania, Via Santa Sofia 64, I-95123 Catania, Italy, Email: cbozza@unisa.it;  
  Corporate Author Thesis  
  Publisher Elsevier Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0010-4655 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000590251400011 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4616  
Permanent link to this record
 

 
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. url  doi
openurl 
  Title Event reconstruction for KM3NeT/ORCA using convolutional neural networks Type Journal Article
  Year 2020 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.  
  Volume 15 Issue 10 Pages P10005 - 39pp  
  Keywords Cherenkov detectors; Large detector systems for particle and astroparticle physics; Neutrino detectors; Performance of High Energy Physics Detectors  
  Abstract (up) 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.  
  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;  
  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 1748-0221 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:000577278000005 Approved no  
  Is ISI yes International Collaboration yes  
  Call Number IFIC @ pastor @ Serial 4570  
Permanent link to this record
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