1
THE LHCB TRACKS RECONSTRUCTION IN RUN 2: STRATEGY AND PERFORMANCE Laurent Dufour 1 , Renata Kopeč2 , Alex Pearce 3 , Maarten van Veghel 1 on behalf of the LHCb collaboration 1 Nikhef National Institute for Subatomic Physics, the Netherlands 2 Physikalisches Institut, Heidelberg University, Germany 3 CERN, Switzerland 39 th ICHEP, Seoul, July 2018 LHCB DETECTOR 1 [1] [2] RECONSTRUCTION IMPROVEMENTS IN RUN 2 Major improvements in the pattern recognition algorithms Factor of 2 speed-up, without loss in performance Extensive use of machine-learning techniques Example: Improved fake-track reduction Fake tracks: not corresponding to a real particle’s trajectory Sped up by O(90%): allow the use in the online event selection Ghost rate in online event selection reduced from 22% to 14% 2 ] 2 [MeV/c π K m 1800 1850 1900 ) 2 candidates / (4 MeV/c 0 500 1000 1500 2000 2500 3000 3500 LHCb preliminary π K 0 all D fakes [4] MEASUREMENT OF TRACKING EFFICIENCY All data selected and stored in software trigger: “TurCal” [5] Oine-quality event reconstruction available online Detector calibration ran online: oine-quality data Data immediately available for analyses Eciency from data using tag-and-probe method Track parameter inference independent of standard track re- construction Exploit two-particle decays First track from the decay is fully reconstructed (tag track) Second track is reconstructed excluding the probed subdetec- tor (probe track) Tracking eciencies easily accessible using “TrackCalib” tool Transparent and easy eciency estimation User-defined track-quality cuts, binning and variables Available for all users MUON TRACKING EFFICIENCY J / ! μ + μ - decay is used [3] μμ pair ideal to probe the whole tracking system J / gives a clear signal in the detector J / coming from B + ! J / X (data) and B + ! J / K (MC) Detached J / for clean signal Unbiased selection by dedicated trigger Long Method T-station method Velo method Final method = Long method + (VELO method T-station method) 3 η 2 2.5 3 3.5 4 4.5 ε 0.86 0.88 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 LHCb preliminary Data (50ns) 2015 Data (50ns) 2012 ] c [GeV/ p 20 40 60 80 100 120 140 160 180 200 ε 0.86 0.88 0.9 0.92 0.94 0.96 0.98 1 1.02 1.04 LHCb preliminary Data (50ns) 2015 Data (50ns) 2012 ELECTRON TRACKING EFFICIENCY Electrons have a considerably dierent behaviour compared to muons Significant energy loss (bremsstrahlung) along trajectory Decreases reconstruction eciency downstream of VELO New method for measuring reconstruction eciencies for electrons: Kinematically constrained VELO tracks originating from B + ! J / (! e + e - )K + Ecient VELO reconstruction (98%) Applicable also to muons & hadrons ) 2 c Candidates / ( 5 MeV/ LHCb simulation preliminary 100 200 300 400 500 600 700 800 900 ] 2 c [MeV/ ± K ψ / J m 5200 5400 5600 Kinematics Direction inferred from VELO segment Probe momentum inferred from J / mass constraint Use B + mass with J / mass constraint to distinguish between signal and background REFERENCES [1] A. A. Alves Jr. et al. [LHCb collaboration], JINST 3 (2008) S08005 [2] R. Aaij et al. [LHCb collaboration], Int. J. Mod. Phys. A30 (2015) 1530022 [3] R. Aaij et al. [LHCb Collaboration], JINST 10, no. 02, P02007 (2015) [4] M. De Cian et al., LHCb-PUB-2017-011 (2017) [5] S. Benson et al., J. Phys.: Conf. Ser. 664 (2015) 082004

The LHCb tracks reconstruction in Run 2: strategy and ... · THE LHCB TRACKS RECONSTRUCTION IN RUN 2: STRATEGY AND PERFORMANCE Laurent Dufour1, Renata Kopená2, Alex Pearce3, Maarten

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Page 1: The LHCb tracks reconstruction in Run 2: strategy and ... · THE LHCB TRACKS RECONSTRUCTION IN RUN 2: STRATEGY AND PERFORMANCE Laurent Dufour1, Renata Kopená2, Alex Pearce3, Maarten

THE LHCB TRACKS RECONSTRUCTION INRUN 2: STRATEGY AND PERFORMANCELaurent Dufour1, Renata Kope�ná2, Alex Pearce3, Maarten van Veghel1on behalf of the LHCb collaboration

1Nikhef National Institute for Subatomic Physics, the Netherlands2Physikalisches Institut, Heidelberg University, Germany3CERN, Switzerland

39th ICHEP, Seoul, July 2018

LHCB DETECTOR1 [1] [2]

RECONSTRUCTION IMPROVEMENTS IN RUN 2⇤ Major improvements in the pattern recognition algorithms⇤ Factor of 2 speed-up, without loss in performance⇤ Extensive use of machine-learning techniques⇤ Example: Improved fake-track reduction⇤ Fake tracks: not corresponding to a real particle’s trajectory⇤ Sped up by O(90%): allow the use in the online event selection⇤ Ghost rate in online event selection reduced from 22% to 14%

2

]2 [MeV/cπKm1800 1850 1900

)2ca

ndid

ates

/ (4

MeV

/c

0

500

1000

1500

2000

2500

3000

3500

LHCbpreliminary

π K→0all Dfakes

[4]

MEASUREMENT OF TRACKING EFFICIENCY⇤ All data selected and stored in software trigger: “TurCal” [5]⇤ O�ine-quality event reconstruction available online⇤ Detector calibration ran online: o�ine-quality data⇤ Data immediately available for analyses

⇤ E�ciency from data using tag-and-probe method⇤ Track parameter inference independent of standard track re-

construction⇤ Exploit two-particle decays⇤ First track from the decay is fully reconstructed (tag track)⇤ Second track is reconstructed excluding the probed subdetec-

tor (probe track)

⇤ Tracking e�ciencies easily accessible using “TrackCalib” tool⇤ Transparent and easy e�ciency estimation⇤ User-defined track-quality cuts, binning and variables⇤ Available for all users

MUON TRACKING EFFICIENCY⇤ J/ ! µ+µ� decay is used [3]⇤ µµ pair ideal to probe the whole tracking system⇤ J/ gives a clear signal in the detector

⇤ J/ coming from B+ ! J/ X (data) and B+ ! J/ K (MC)⇤ Detached J/ for clean signal⇤ Unbiased selection by dedicated trigger

Long Method T-station method Velo method

Final method = Long method + (VELO method � T-station method)

3

η2 2.5 3 3.5 4 4.5

ε

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04 LHCb preliminary

Data (50ns) 2015

Data (50ns) 2012

]c [GeV/p20 40 60 80 100 120 140 160 180 200

ε

0.86

0.88

0.9

0.92

0.94

0.96

0.98

1

1.02

1.04 LHCb preliminary

Data (50ns) 2015

Data (50ns) 2012

ELECTRON TRACKING EFFICIENCYElectrons have a considerably di�erent behaviour compared to muons⇤ Significant energy loss (bremsstrahlung) along trajectory⇤ Decreases reconstruction e�ciency downstream of VELO

New method for measuring reconstruction e�ciencies for electrons:Kinematically constrained VELO tracks originating fromB+ ! J/ (! e+e�)K+

⇤ E�cient VELO reconstruction(⇡98%)

⇤ Applicable also to muons &hadrons

)2 c

Can

dida

tes /

( 5

MeV

/

LHCb simulation preliminary

100

200

300

400

500

600

700

800

900

]2c[MeV/±K�/Jm5200 5400 5600

Kinematics⇤ Direction inferred from VELO

segment⇤ Probe momentum inferred

from J/ mass constraint⇤ Use B+ mass with J/ mass

constraint to distinguishbetween signal andbackground

REFERENCES[1] A. A. Alves Jr. et al. [LHCb collaboration], JINST 3 (2008) S08005[2] R. Aaij et al. [LHCb collaboration], Int. J. Mod. Phys. A30 (2015) 1530022[3] R. Aaij et al. [LHCb Collaboration], JINST 10, no. 02, P02007 (2015)[4] M. De Cian et al., LHCb-PUB-2017-011 (2017)[5] S. Benson et al., J. Phys.: Conf. Ser. 664 (2015) 082004