Particle-flow reconstruction and global event description with the CMS detector

Восстановление на основе потоков частиц и глобальное описание события с детектором CMS
M. Flechl, T. Matsushita, J. Schieck, K. Skovpen, W. Adam, T. Bergauer, M. Dragicevic, X. Janssen, J. Lauwers, P. Van Mechelen, F. Blekman, J. D’Hondt, S. Lowette, P. Van Mulders, B. Clerbaux, H. Delannoy, L. Favart, R. Goldouzian, D. Vannerom, F. Zhang, S. Tavernier, L. Favart, M. Jeitler, A. M. Sirunyan, A. Tumasyan, E. Asilar, J. Brandstetter, E. Brondolin, J. Erö, M. Friedl, R. Frühwirth, V.M. Ghete, C. Hartl, N. Hörmann, J. Hrubec, A. König, I. Krätschmer, D. Liko, I. Mikulec, Dinyar Rabady, N. Rad, B. Rahbaran, H. Rohringer, Johann Strauß, W. Waltenberger, C.-E. Wulz, O. Dvornikov, В. Макаренко, V. Mossolov, J. Suarez Gonzalez, V. Zykunov, N. Shumeiko, S. Alderweireldt, E.A. De Wolf, M. Van De Klundert, H. Van Haevermaet, N. Van Remortel, A. Van Spilbeeck, S. Abu Zeid, N. Daci, I. De Bruyn, K. Deroover, S. Moortgat, L. Moreels, A. Olbrechts, Q. Python, W. Van Doninck, I. Van Parijs, H. Brun, G. De Lentdecker, Giuseppe Fasanella, A. Grebenyuk, G. Karapostoli, T. Lenzi, A. Léonard, J. Luetic, T. Maerschalk, A. Marinov, A. Randle-Conde, T. Seva, C. Vander Velde, P. Vanlaer, R. Yonamine, F. Zenoni, T. Cornelis, D. Dobur, A. Fagot, M. Gul, I. Khvastunov, Deniz Poyraz, S. Salva, R. Schöfbeck, M. Tytgat, W. Van Driessche, E. Yazgan, N. Zaganidis, H. Bakhshiansohi, O. Bondu, S. Brochet, G. Bruno, A. Caudron, Dinyar Rabady
2017-10-06
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CMS detectorglobal event descriptionmissing transverse momentumparticle-flow reconstructionpileup mitigation
Abstract (AI)
The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collider. For each collision, the comprehensive list of final-state particles identified and reconstructed by the algorithm provides a global event description that leads to unprecedented CMS performance for jet and hadronic decay reconstruction, missing transverse momentum determination, and electron and muon identification. This approach also allows particles from pileup interactions to be identified and enables efficient pileup mitigation methods. The data collected by CMS at a centre-of-mass energy of 8show excellent agreement with the simulation and confirm the superior PF performance at least up to an average of 20 pileup interactions.
Key Findings
1
A fully-fledged PF reconstruction algorithm tuned to CMS was developed and used consistently in physics analyses at a hadron collider for the first time.
2
CMS data at 8 TeV show excellent agreement with simulation and confirm superior PF performance up to an average of 20 pileup interactions.
3
CMS detector features (highly-segmented tracker, fine-grained ECAL, hermetic HCAL, strong magnetic field, excellent muon spectrometer) are well suited to particle-flow (PF) reconstruction.
4
PF reconstructs a comprehensive list of final-state particles per collision, providing a global event description that improves jet and hadronic decay reconstruction.
5
PF-based global event description leads to improved missing transverse momentum determination and enhanced electron and muon identification.
6
The PF approach enables identification of particles from pileup interactions and supports efficient pileup mitigation methods.
Research Object

Particle-flow (PF) reconstruction algorithm tuned to the CMS detector

Research Subject

Identification and reconstruction of final-state particles to provide a global event description for improved jet and hadronic decay reconstruction, missing transverse momentum determination, electron and muon identification, and pileup mitigation

Publication Details
Publication Date
2017-10-06
Journal
Publisher
ISSN
Access Type
Author Information
Authors
M. Flechl
T. Matsushita
J. Schieck
K. Skovpen
W. Adam
T. Bergauer
M. Dragicevic
X. Janssen
J. Lauwers
P. Van Mechelen
F. Blekman
J. D’Hondt
S. Lowette
P. Van Mulders
B. Clerbaux
H. Delannoy
L. Favart
R. Goldouzian
D. Vannerom
F. Zhang
S. Tavernier
L. Favart
M. Jeitler
A. M. Sirunyan
A. Tumasyan
E. Asilar
J. Brandstetter
E. Brondolin
J. Erö
M. Friedl
R. Frühwirth
V.M. Ghete
C. Hartl
N. Hörmann
J. Hrubec
A. König
I. Krätschmer
D. Liko
I. Mikulec
Dinyar Rabady
N. Rad
B. Rahbaran
H. Rohringer
Johann Strauß
W. Waltenberger
C.-E. Wulz
O. Dvornikov
В. Макаренко
V. Mossolov
J. Suarez Gonzalez
V. Zykunov
N. Shumeiko
S. Alderweireldt
E.A. De Wolf
M. Van De Klundert
H. Van Haevermaet
N. Van Remortel
A. Van Spilbeeck
S. Abu Zeid
N. Daci
I. De Bruyn
K. Deroover
S. Moortgat
L. Moreels
A. Olbrechts
Q. Python
W. Van Doninck
I. Van Parijs
H. Brun
G. De Lentdecker
Giuseppe Fasanella
A. Grebenyuk
G. Karapostoli
T. Lenzi
A. Léonard
J. Luetic
T. Maerschalk
A. Marinov
A. Randle-Conde
T. Seva
C. Vander Velde
P. Vanlaer
R. Yonamine
F. Zenoni
T. Cornelis
D. Dobur
A. Fagot
M. Gul
I. Khvastunov
Deniz Poyraz
S. Salva
R. Schöfbeck
M. Tytgat
W. Van Driessche
E. Yazgan
N. Zaganidis
H. Bakhshiansohi
O. Bondu
S. Brochet
G. Bruno
A. Caudron
Dinyar Rabady
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