# Presentation: 415383

## B-Tagging at CDF and DØLessons for LHC

- Thomas Wright
- University of Michigan
- For the CDF and DØ Collaborations
- Hadron Collider Physics Symposium
- May 26, 2006

## Introduction

- Lots of interesting physics involves high-pT b-quarks
- Top production - BR(tWb) ~ 100%
- Higgs searches
- For mH < 135 GeV/c2, Hb_b_ is the most common decay
- SUSY b_b_g  b_b_A b_b_b_b_ at high tan
- Sparticle searches – sbottom, stop decays into b+X
- Fortunately, there are ways to tell if a jet is a b-jet
- Outline
- Unique characteristics of b-jets
- CDF/DØ detector subsystems relevant to b-tagging
- B-tagging algorithms
- Efficiency and fake rate measurements
- Recent algorithmic advancements
- High luminosity and thoughts on the LHC
- Conclusions

- HCP 2006

- T. Wright

## Signatures of B-Jets

- High b-hadron mass
- 5.3 GeV/c2
- Relatively long lifetime
- 1.5 ps  c = 450 m
- Hard fragmentation
- b-hadron retains ~70% of b-quark momentum
- Put ‘em all together and you get
- High-pT tracks
- Large impact parameters
- Secondary vertices (few mm)
- Lepton production
- ~10% b   l
- Also ~10% c/_c_ l
- High-pT tracks
- High-pT relative to b-jet

- HCP 2006

- T. Wright

## The CDF Detector

- COT: 96-layer wire drift chamber
- 4 axial, 4 stereo superlayers
- 1.4 T magnetic field
- “Central” lepton ID out to ||<1.1
- Silicon tracker
- 95 cm long Layer 00
- Radiation hard
- 3 SVX-II barrels, each 29 cm long

- L00 – singled-sided, r = 1.2 cm
- SVX-II – 5 double-sided layers
- L0: r – rz, r=2.5 cm
- L1: r – rz, r=4.5 cm
- L2: r – 1.2° stereo, r=6.5 cm
- L3: r – rz, r=8.5 cm
- L4: r – 1.2° stereo, r=10.5 cm
- Total sensor area 6 m2
- 720k electronics channels

- HCP 2006

- T. Wright

## The DØ Detector

- Central Fiber Tracker
- 8 layers of scintillating fiber (axial and stereo)
- 20 < r < 51 cm in 2 T B-field
- Unified muon system covers ||<2
- Silicon tracker
- 6 barrels, 4 layers each, ~1 m
- Disks extend coverage to ||<3
- 790k electronics channels

- Original silicon starts at r = 2.7 cm
- Layers 1+3: r – rz
- Layers 2+4: r – 2° stereo
- Central disks 15° stereo
- Forward disks 7.5° stereo
- New radiation-hard Layer 0
- Impact parameter resolution improves going to r = 1.6 cm
- Mitigates possible Layer 1 efficiency loss as dose increases

- HCP 2006

- T. Wright

## Common Issues

- Reference for impact parameter calculations
- Tevatron beam profile is ~30 m in xy
- Can improve by computing event-by-event primary vertex
- Fit all tracks to a common point – discard outliers – iterate
- Final resolution is 10-30 m depending on event topology
- Poorly-reconstructed tracks are a killer – quality cuts are critical
- Both experiments use silicon hit multiplicity and fit 2
- Remove KS/ decay products
- Raising pT cuts helps control fake tag rate
- Inactive detector regions and data/simulation mismatch
- CDF: model inactive silicon ladders in the simulation run-by-run
- DØ: everything relative to “taggable” jets (couple of  silicon tracks) – get taggability rate from data (~80%)
- Both experiments apply a scale factor to simulation efficiency to match what’s seen in the data (0.7 – 0.9, depending on tagger)

- HCP 2006

- T. Wright

## Soft Lepton Tagging

- Tag b-tags by identifying a lepton from b or c decay
- CDF & DØ both do it for muons
- ID requirements somewhat different than high-pT case
- Can’t use calorimeter energy
- Track-stub angular matching is more effective
- Typical ID efficiency 80-90%
- Per-jet efficiency ~10%
- Mis-ID rates ~0.5% per track
- Electrons are more difficult
- Had it in Run I
- Under development at CDF

- CDF

- Soft lepton taggers use different information than lifetime taggers
- Can use overlap rate for calibration

- HCP 2006

- T. Wright

## Impact Parameter Taggers

- Count displaced tracks (DØ)
- three 2 or two 3
- sign IP’s against jet direction
- Jet probability (CDF & DØ)
- Joint probability for all tracks to come from primary vertex
- Track resolution derived from negative IP tracks
- Use only positive IP tracks in probability calculation
- Displaced vertex (CDF & DØ)
- Fit displaced tracks (above pT cuts) to a common vertex
- Prune tracks and cut on fit 2
- Cut on Lxy significance
- All algorithms can be tuned by adjusting cuts – 2-6 operating points

- DØ

- DØ

- CDF

- HCP 2006

- T. Wright

## Efficiency Measurement (CDF)

- Based on 8 GeV/c electron and muon data samples
- Tag away jet to enhance b-fraction
- Generate matching MC samples
- Method A: muon pTrel fits
- Fit muon pTrel against jet in tagged and untagged jet
- Extract numbers of b-jets in each and compute efficiency
- Systematics ~3%, mostly from modeling of pTrel templates
- Method B: electron double-tags
- Infer non-b component from electron jet single-tag rate and conversion sample
- Systematics ~5%, mostly from mistag subtraction

- HCP 2006

- T. Wright

## Efficiency Measurement (CDF)

- Systematics quoted earlier for each method were only the “internal” ones
- Additional systematics related to extrapolation to physics samples (in particular, b-jets from top)
- Jet ET dependence
- Convolute binned scale factor with ET spectrum from top
- 7% uncertainty
- Similar procedure for jet 
- 1% uncertainty
- 2% uncertainty assigned for differences between semileptonic/generic B-decays
- Total uncertainty on data/MC scaled factor : 7.3%

- HCP 2006

- T. Wright

## Efficiency Results (CDF)

- CDF displaced vertex tagger
- Top pair simulation, scaled by data/MC tag efficiency ratio
- Width of the bands shows the systematic errors

- HCP 2006

- T. Wright

## Efficiency Measurement (DØ)

- Based on low-pT muon sample
- Require away jet similar to CDF
- Define a muon tag: pTrel > 0.7
- Count events with
- Muon tag
- B-tag (any of the IP taggers)
- Both muon tag and b-tag
- Same three, when away jet is tagged
- From these rates, can solve for
- Muon tag efficiency
- B-tag efficiency
- Sample b-fractions
- Systematic uncertainties ~3%
- Data statistical errors dominate at high jet ET (similar to CDF’s 7% from convoluting with top b-jet spectrum)

- JLIP

**total uncertainty**

- HCP 2006

- T. Wright

## Efficiency Results (DØ)

- TRFb = MC efficiency, scaled by data/MC efficiency ratio
- Jet probability tagger for various cut values
- Combine ET and  parametrizations into a 2D function
- Used to predict tag rates in Monte Carlo samples

- HCP 2006

- T. Wright

## Fake Tag Rates

- Fake tags (mistags) mostly from misreconstructed tracks
- +/- symmetry
- Estimate fake rates by
- Using tracks with negative signed impact parameters
- Using displaced vertices behind the primary w.r.t. the jet direction
- Both experiments use parametrizations of “negative” tag rates (in ET, , etc) to predict mistag rate in data samples
- Complications
- Negative tags from heavy flavor (~10-15%)
- Mistag rate not exactly symmetric – stray KS/ and interactions with detector material
- Fit POS-NEG excess in pseudo-c to estimate (~40%)
- Net effect ~30% enhancement over negative tage rate

- CDF

- HCP 2006

- T. Wright

## Fake Tag Results (CDF)

- CDF displaced vertex tagger
- Negative tag rates, scaled by the asymmetry factor 1.3
- Bands show the systematic errors assigned (~15%)

- HCP 2006

- T. Wright

## Fake Tag Results (DØ)

- Jet probability tagger for various cut values
- Includes asymmetry factor (close to unity due to cancellation of the two effects)
- Uncertainties are 5-15% depending on operating point (looser tag = smaller uncertainty)

- HCP 2006

- T. Wright

## Multivariate Algorithms

- Taggers are correlated, but not 100%
- Can gain by combining them
- CDF has a simple “combined tagger” – logical OR of displaced vertex and jet probability taggers
- Gain 15-25% efficiency, at cost of factor two mistag rate
- Use more information than just the tagger outputs
- Displaced vertex tagger gives you more than just yes/no
- Many vertex properties discriminate signal/background
- Both experiments have new multivariate taggers
- CDF: start with displaced vertex tag, try to reject charm/light while preserving b-tags
- DØ: no displaced vertex prerequisite – can optimize for better purity or enchanced efficiency

- HCP 2006

- T. Wright

## Multivariate Tagger (CDF)

- Two 16-variable neural networks
- Vertex mass, Lxy, 2, pT
- High-IP track pT, multiplicity
- Jet probability
- and so much more!
- Train one to separate b-vs-light, the other b-vs-c
- Choose cuts to preserve 90% of b
- Reject 45% of c, 65% of light
- Already in use
- Top cross section
- WH search
- Similar, dedicatedalgorithm forsingle-top search

- HCP 2006

- T. Wright

## Multivariate Tagger (DØ)

- 7-variable neural network
- Vertex mass, Lxy/, 2
- Number of vertices/jet
- Jet total and displaced track multiplicities
- Jet probability
- Vertex tagger uses a “super-loose” tune to get info on more jets
- Train to separate b-vs-light
- Can improve efficiency or mistag by 25%, up to a factor of two in the efficiency/purity extremes
- Efficiency and fake rates have been measured in data
- Ready for analysis use

- HCP 2006

- T. Wright

## B-Tagging at High Luminosity

- Starting to study effects of high luminosity on b-tagging (results are extremely preliminary)
- Nvtx ~ luminosity
- At 3E32 cm-2s-1, <Nvtx> = 4
- MC study of top events with extra minimum-bias overlaid indicates that efficiency decreases
- High tracker occupancy
- Hits merge together
- Pattern recognition harder
- Negative tag rates in data rise
- Silicon hit merging?
- Another interaction nearby?
- Disabling dE/dx pulse shaping on innermost COT layers should help
- Revisit track quality cuts

- CDF

- CDF

- HCP 2006

- T. Wright

## Some LHC Thoughts (from a non-LHC’er)

- B-tagging at a hadron collider has many years’ history to draw upon
- CDF/DØ learning how to deal with multiple interactions
- May be useful for LHC
- Pixel+strip inner detectors will handle occupancy better
- Get your calibration triggers in
- Low-pT leptons
- Jets at various thresholds
- Likely have to prescale a lot
- Don’t let them get turned off at high luminosity!
- Measure everything in data
- But, a well-tuned simulation comes in pretty handy

- Yesterday’s discovery is today’s calibration
- Measure b-tag efficiency (or data/MC scale factor) in top events?
- Parametrize acceptance and backgrounds in SF, require single- and double-tagged top cross sections equal – get tt and SF
- Just about feasible at Tevatron - @LHC ?

- HCP 2006

- T. Wright

## Conclusion

- B-tagging is a critical component of the Tevatron physics program
- Both experiments have robust and well-understood tools
- We are still building upon them and making improvements
- Entering a new luminosity regime
- Some work ahead to understand/minimize the effects
- Tevatron experience should be useful at LHC
- B-tagging is a fun and challenging topic
- Design/calibration of taggers has a lot of physics in it
- Not a solved problem – still room for good ideas

- HCP 2006

- T. Wright