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Author Poley, L. et al; Lacasta, C.
Title Investigations into the impact of locally modified sensor architectures on the detection efficiency of silicon micro-strip sensors Type Journal Article
Year 2017 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 12 Issue Pages P07006 - 17pp
Keywords Si microstrip and pad detectors; Inspection with x-rays; Hybrid detectors; Instrumentation for particle accelerators and storage rings – high energy (linear accelerators, synchrotrons)
Abstract (up) The High Luminosity Upgrade of the LHC will require the replacement of the Inner Detector of ATLAS with the Inner Tracker (ITk) in order to cope with higher radiation levels and higher track densities. Prototype silicon strip detector modules are currently developed and their performance is studied in both particle test beams and X-ray beams. In previous test beam measurements of prototype modules, the response of silicon sensors has been studied in detailed scans across individual sensor strips. These scans found instances of sensor strips collecting charge across areas on the sensor deviating from the geometrical width of a sensor strip. The variations have been linked to local features of the sensor architecture. This paper presents results of detailed sensor measurements in both X-ray and particle beams investigating the impact of sensor features (metal pads and p-stops) on the sensor strip response.
Address [Poley, L.] DESY, Notkestr, Hamburg, Germany, Email: Anne-Luise.Poley@desy.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:000406392600006 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 3234
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Author HAWC Collaboration (Abeysekara, A.U. et al); Salesa Greus, F.
Title The High-Altitude Water Cherenkov (HAWC) observatory in Mexico: The primary detector Type Journal Article
Year 2023 Publication Nuclear Instruments & Methods in Physics Research A Abbreviated Journal Nucl. Instrum. Methods Phys. Res. A
Volume 1052 Issue Pages 168253 - 18pp
Keywords Physics – instrumentation and detectors; Water Cherenkov Detectors; Astrophysics; High energy physics – experiment; Nuclear experiment
Abstract (up) The High-Altitude Water Cherenkov (HAWC) observatory is a second-generation continuously operated, wide field-of-view, TeV gamma-ray observatory. The HAWC observatory and its analysis techniques build on experience of the Milagro experiment in using ground-based water Cherenkov detectors for gamma-ray astronomy. HAWC is located on the Sierra Negra volcano in Mexico at an elevation of 4100 meters above sea level. The completed HAWC observatory principal detector (HAWC) consists of 300 closely spaced water Cherenkov detectors, each equipped with four photomultiplier tubes to provide timing and charge information to reconstruct the extensive air shower energy and arrival direction. The HAWC observatory has been optimized to observe transient and steady emission from sources of gamma rays within an energy range from several hundred GeV to several hundred TeV. However, most of the air showers detected are initiated by cosmic rays, allowing studies of cosmic rays also to be performed. This paper describes the characteristics of the HAWC main array and its hardware.
Address [Abeysekara, A. U.; Barber, A. S.; Hona, B.; Kieda, D.; Newbold, M.; Springer, R. W.] Univ Utah, Dept Phys & Astron, Salt Lake City, UT USA, Email: eduardo.delafuentea@academicos.udg.mx
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 0168-9002 ISBN Medium
Area Expedition Conference
Notes WOS:001063137300001 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5674
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Author LHCb Collaboration (Aaij, R. et al); Jashal, B.K.; Martinez-Vidal, F.; Oyanguren, A.; Remon Alepuz, C.; Ruiz Vidal, J.
Title Identification of charm jets at LHCb Type Journal Article
Year 2022 Publication Journal of Instrumentation Abbreviated Journal J. Instrum.
Volume 17 Issue 2 Pages P02028 - 23pp
Keywords Analysis and statistical methods; Pattern recognition; cluster finding; calibration and fitting methods; Performance of High Energy Physics Detectors
Abstract (up) The identification of charm jets is achieved at LHCb for data collected in 2015-2018 using a method based on the properties of displaced vertices reconstructed and matched with jets. The performance of this method is determined using a dijet calibration dataset recorded by the LHCb detector and selected such that the jets are unbiased in quantities used in the tagging algorithm. The charm-tagging efficiency is reported as a function of the transverse momentum of the jet. The measured efficiencies are compared to those obtained from simulation and found to be in good agreement.
Address [Leite, J. Baptista; Bediaga, I; Torres, M. Cruz; De Miranda, J. M.; dos Reis, A. C.; Gomes, A.; Massafferri, A.; Machado, D. Torres] Ctr Brasileiro Pesquisas Fis CBPF, Rio De Janeiro, Brazil, Email: dcraik@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:000770368300015 Approved no
Is ISI yes International Collaboration yes
Call Number IFIC @ pastor @ Serial 5177
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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.
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
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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.
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