Particle Identification in LHCb

Funai XingUniversity of Oxford

On behalf of LHCb collaboration

Physics at LHC 20102010.06.07 Hamburg

1. Ring Imaging CHerenkov (RICH) detectors

2. Muon Systems

3. Calorimeters

4. Summary

Contents

2010-06-07 2PLHC 2010, Hamburg, Germany LHCb PID - XING

LHCb PID sub-systems

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 3

e, ɣ and hadrons μK, π, p

1. RICH

K, π separation is crucial to many LHCb analyses.

1. RICH

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 5

Hybrid Photo Diodes (HPDs)196 (RICH1) + 288 (RICH2)

RICH 1

without RICH with RICH

10 10

1. RICH - Radiators

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 6

RICH1 RICH2

C4F10 gasn=1.0014 Up to ~70 GeV/c

CF4 gasn=1.0005 Up to ~100 GeV/c

Silica Aerogeln=1.03 1-10 GeV/c

3 radiators 1-100 GeV coverage

RICH aligned with tracking system; Clear K and π rings seen:

1. RICH – Cherenkov Rings

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 7

Take all photons from all tracks, in all radiators and maximise the Likelihood function:

Take all PIDs to be π (or seed with a previous iteration) and estimate background parameter bpixel per HPD;

Calculate likelihood of a given pixel distribution;

Iterate until converge:◦ Change PID hypothesis, one track at a time◦ Recalculate likelihood for a given hypothesis◦ Assign new PID that maximises the likelihood

With signal photons “identified”, update background estimate and iterate

ΔlogL per track and hypothesis ⇨ PID.

1. RICH – PID Algorithms

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 8

To maintain the integrity of the LHCb physics performance, it is essential to monitor the PID efficiency and mis-ID rates.

1. RICH - Calibration

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 9

Will become main channels for kaon performance monitoring at nominal luminosities.

(tag and probe)

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 10

0)(log KL

5)(log KL

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 11

0)(log pKL

5)(log pKL

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 12

0)(log pL

5)(log pL

Applying RICH PID to data:

1. RICH – PID in Data

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 13

without RICH with RICH

f →KK ?

2. Muon Systems

Several key measurements of LHCb rely on μ-ID: e.g. Bs→ μ+μ- and Bd→ K*0μ+μ-

Muon systems provides μ-ID to very high purity; 5 tracking stations, each subdivided in 4 regions

with different granularities; Equipped with Multi Wire Proportional Chambers

(MWPCs) and Gas Electron Multipliers (GEMs). Total thickness of LHCb hadron absorber (muon

shield): ~ 23l

2. Muon Systems

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 15

Muon identification:

Extrapolate tracks and find hits in a Field of Interest;

Find muon candidates requiring hits in different stations depending on momentum;

Calculate a probability using the position of the hits in different stations.

2. Muon Systems

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 16

Calibration: J/Ψ→μ+μ- (tag & probe):◦ Identify one muon with the muon system (Tag)

and the other muon by MIPs in the calorimeters (Probe);

◦ Use the probe muon to estimate μ-ID efficiency.

2. Muon Systems

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 17

ε() = 97.3 ± 1.2 %

Also use KS and Λ to test mis-ID rates:

2. Muon Systems

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 18

LHCb 2010preliminary

LHCb 2010preliminary

π→μMis-ID: (2:38 0:02)%

p→μMis-ID : (0:18 0:02)%

3. Calorimeters

They provide identification of e, ɣ and hadrons as well as the measurement of their energies and positions.

Electron e/p: mean ~ 99.7%, sigma ~10.76%.

Important for neutral particle identification.

3. Calorimeters

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 20

π0→γγ

η,ω→πππ0

Progress being made on all fronts on calibrating the PID sub-systems;

Expect further improvements with better tracking alignments;

More channels can be utilised for calibration at nominal luminosity.

Summary

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 21

Backup slides

• The functional form describing the signal and background contributions of ɸ invariant-mass distributions are known but not those in ΔlogL, p etc.

• However, since ΔlogL and p of a daughter track are uncorrelated to the mother invariant-mass, one can utilise

“sWeights”:◦ • Following a fit to the invariant-mass distribution, can assign a

weight (sWeight) to each candidate defining its probability to be signal or background

◦ • Can then use these weights to “unfold” the background and signal contributions to the daughter track DlogL distributions

◦ • The “unfolded” distributions are then referred to as “sPlots”

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 23

sPlots and sWeights

sPlots and sWeights

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 24

• Test method on Monte Carlo

• Top, unfolded ΔlogL distribution

• Bottom, unfolded momentum distribution

• Excellent agreement to MC true

• Method therefore applied to data

• Used for both:• Kaons from ɸ• protons from Λ

DLL Distributions

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 25

J/Ψ Fit

2010-06-07PLHC 2010, Hamburg, Germany LHCb PID - XING 26