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AIDA-2020

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2021-01-25
14:21
Python IRRAD Motor Control Application (PIMCA): How it works / Smith Mølholm, Alexander (Aarhus University) ; Ravotti, Federico (CERN) ; Gkotse, Blerina (CERN)
AIDA-2020-NOTE-2021-003.- Geneva : CERN, 2021 Fulltext: PDF;

Detaljnije - Slični zapisi
2021-01-21
14:40
Python IRRAD Motor Control Application (PIMCA) : How to use / Smith Mølholm, Alexander (Aarhus University) ; Ravotti, Federico (CERN) ; Gkotse, Blerina (CERN)
AIDA-2020-NOTE-2021-002.- Geneva : CERN, 2021 Fulltext: PDF;

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2020-07-20
13:37
AIDA-2020: 3rd periodic report
AIDA-2020-NOTE-2020-007.- Geneva : CERN, 2020 Fulltext: PDF;

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2020-06-08
15:44
First test results of the CHIPIX65 asynchronous front-end connected to a 3D sensor / Gaioni, L. (Universita di Bergamo) ; De Canio, F. (Universita di Pavia, INFN Pavia) ; Manghisoni, M. (Universita di Bergamo, INFN Pavia) ; Ratti, L. (Universita di Pavia, INFN Pavia) ; Re, V. (Universita di Bergamo, INFN Pavia) ; Sonzogni, M. (Universita di Bergamo, INFN Pavia) ; Traversi, G. (Universita di Bergamo, INFN Pavia)
This work reports on the main results from the experimental characterization of the asynchronous analog front-end integrated in a 65 nm CMOS mixed-signal chip for the readout of high granularity silicon pixel sensors at the high-luminosity upgrades of the ATLAS and CMS experiments. Such a mixed-signal chip has been designed and submitted in the framework of the CHIPIX65 project, funded by the Italian Institute of Nuclear Physics for the development of an advanced pixel chip in a 65 nm CMOS technology. [...]
AIDA-2020-PUB-2020-010.- Geneva : CERN, 2020 - Published in : Nuclear Instruments and Methods A Fulltext: PDF;

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2020-06-03
13:12
A Light Calibration System for the ProtoDUNE-DP Detector / Cuesta, C. (CIEMAT) ; Belver, D. (CIEMAT) ; Boix, J. (IFAE) ; Calvo, E. (CIEMAT) ; Gallego-Ros, A. (CIEMAT) ; Gil-Botella, I. (CIEMAT) ; Jiménez, S. (CIEMAT) ; Lastoria, C. (CIEMAT) ; Lux, T. (IFAE) ; Martin, I. (CIEMAT) et al.
A LED-based fiber calibration system for the ProtoDUNE-Dual Phase (DP) photon detection system (PDS) has been designed and validated. ProtoDUNE-DP is a 6x6x6 m3 liquid argon time-projection-chamber (LAr TPC) currently being installed at the Neutrino Platform at CERN. [...]
AIDA-2020-PUB-2020-009.- Geneva : CERN, 2020 Fulltext: PDF;

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2020-05-28
10:49
Cryogenic R5912-20Mod Photomultiplier Tube Characterization for the ProtoDUNE Dual Phase Detector / Cuesta, C. (CIEMAT) ; Belver, D. (CIEMAT) ; Calvo, E. (CIEMAT) ; Gallego-Ros, A. (CIEMAT) ; Gil-Botella, I. (CIEMAT) ; Jiménez, S. (CIEMAT) ; Lastoria, C. (CIEMAT) ; Lux, T. (IFAE) ; Palomares, C. (CIEMAT) ; Redondo, D. (CIEMAT) et al.
The Deep Underground Neutrino Experiment (DUNE) is a dual-site experiment for longbaseline neutrino oscillation studies, and for neutrino astrophysics and nucleon decay searches. The far detector is a 40-kton underground liquid argon time-projection-chamber (LAr TPC), in which the photon detector system adds precise timing capabilities. [...]
AIDA-2020-PUB-2020-008.- Geneva : CERN, 2020 Fulltext: PDF;

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2020-05-27
16:49
MarlinMT - parallelising the Marlin framework / Ete, R. (DESY) ; Gaede, F. (DESY) ; Benda, J. (DESY) ; Grasland, H. (Universite Paris-Saclay, CNRS-IJCLab)
Marlin is the event processing framework of the iLCSoft [1] ecosystem. Originally developed for the ILC more than 15 years ago, it is now widely used also by other communities, such as CLICdp, CEPC and many test beam projects such as CALICE, LCTPC and EU-Telescope. While Marlin is lightweight and flexible it was originally designed for sequential processing only. [...]
AIDA-2020-CONF-2020-019.- Geneva : CERN, 2020 - Published in : Fulltext: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019

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2020-05-27
16:46
PODIO: recent developments in the Plain Old Data EDM toolkit / Gaede, F. (DESY) ; Hegner, B. (CERN) ; Stewart, G. A. (CERN)
PODIO is a C++ toolkit for the creation of event data models (EDMs) with a fast and ecient I/O layer. It employs plain-old-data (POD) data structures wherever possible, while avoiding deep object-hierarchies and virtual inheritance. A lightweight layer of handle classes provides the necessary highlevel interface for the physicist. [...]
AIDA-2020-CONF-2020-018.- Geneva : CERN, 2020 - Published in : EPJ Web Conf. 245 (2020) 05024 Fulltext: PDF; Fulltext from publisher: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.05024

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2020-05-27
12:08
DD4hep a community driven detector description for HEP / Gaede, F. (DESY) ; Frank, M. (CERN) ; Petric, M. (CERN) ; Sailer, A. (CERN)
Detector description is an essential component in simulation, reconstruction and analysis of data resulting from particle collisions in high energy physics experiments and for the detector development studies for future experiments. Current detector description implementations of running experiments are mostly specific implementations. DD4hep [1] is an open source toolkit created in 2012 to serve as a generic detector description solution. [...]
AIDA-2020-CONF-2020-017.- Geneva : CERN, 2020 - Published in :
- Published in : EPJ Web Conf.: 245 (2020) , pp. 02004 Fulltext: PDF; Fulltext from publisher: PDF;
In : 24th International Conference on Computing in High Energy and Nuclear Physics, Adelaide, Australia, 4 - 8 Nov 2019, pp.02004

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2020-05-26
13:52
A modular mini-pad photon detector prototype for RICH application at the Electron Ion Collider / Dasgupta, S. (INFN Trieste) ; Agarwala, J. (Abdus Salam ICTP, INFN Trieste) ; Azevedo, C.D.R. (University of Aveiro) ; Chatterjee, C. (University of Trieste, INFN Trieste) ; Cicuttin, A. (Abdus Salam ICTP, INFN Trieste) ; Ciliberti, P. (University of Trieste, INFN Trieste) ; Crespo, M.L. (Abdus Salam ICTP, INFN Trieste) ; Dalla Torre, S. (INFN Trieste) ; Gregori, M. (INFN Trieste) ; Levorato, S. (INFN Trieste) et al.
AIDA-2020-NOTE-2020-006.- Geneva : CERN, 2020 Fulltext: PDF;

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AIDA-2020 has received funding from the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement no. 654168. Project website: http://aida2020.web.cern.ch/.