CMS Physics : Technical Design Report Volume 1: Detector Performance and Software
By G. Bayatian, A. Korablev, A. Soha, O. Sharif, M. Chertok, W. Mitaroff, F. Pauss, Genchev, M. Wensveen, Lemaître and 1,991 more. 2006
285 citations recorded by the source corpus.
Subfields: AI for Physical Sciences
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In AI for Physical Sciences
- Cms Collaboration
- S. Visscher
- Salvatore Rappoccio
- M. Selvaggi
- Alexander Belyaev
- Philip C. Harris
- Nhan Tran
- V. Khachatryan
Citations in the corpus
- Energy calibration and resolution of the CMS electromagnetic calorimeter in pp collisions at √s = 7 TeV (2013, methodology): “The single-crystal energy deposits are small and corrections are applied to these deposits to account for the effects of the noise suppression algorithm used in the readout [29].”
- Observation and studies of jet quenching in PbPb collisions at nucleon-nucleon center-of-mass energy = 2.76 TeV (2011, methodology): “Jets are then reconstructed, using a standard iterative cone algorithm [32, 33], from the remaining cells with non-zero energy.”
- Energy calibration and resolution of the CMS electromagnetic calorimeter in pp collisions at √s = 7 TeV (2013, methodology): “The clustering algorithm used in EB, called the ‘hybrid’ algorithm, is described in [30].”
- Particle-flow reconstruction and global event description with the CMS detector (2017, background): “Muon tracking [27, 28] is not specific to PF reconstruction.”
- Performance of electron reconstruction and selection with the CMS detector in proton-proton collisions at √s = 8 TeV (2015, methodology): “The basic principles of offline electron reconstruction, outlined in the CMS Physics Technical Design Report [2, 3], rely on a combination of the energy measured in the electromagnetic calorimeter (ECAL) and the momentum measured in the tracking detector (tracker), to optimize the performance over a”