# Presentation: 367563

## Top Quark Pair Production at 1.96 GeV  using Lepton + Jets events at CDF

**Joao Guimaraes da Costa**
**Harvard University**
**(for the CDF Collaboration)**

**HEP2005    Lisboa, Portugal**

- Top Cross Section in the Lepton+Jets Sample --- Joao Guimaraes           HEP2005

- July 23, 2005

**Notes:**
The Physics of the Top Quark at CDF
From the Bottom to the Top: Exploring the electroweak energy scale

## Motivation

- Top quark: The young member of the SM family
- Discovered in 1995 but still almost everything to learn
- Is the W+jets event excess pure tt production?
- Want to measure top properties, but first ....
- Need large top quark datasets
- Understand the W+Jets sample
- Learn the backgrounds

- The Tevatron

|  | Luminosity (pb-1) |
| --- | --- |
| Delivered | > 1000 |
| CDF to tape | ~ 900 |
| Today’s results update | ~ 350 |
| Published | ~ 200 |

- Measure top cross section
- Test of QCD predictions                  Test of SM  New physics?
-                                                                Check different decay modes

- Measure top cross section

**Notes:**
Top quark: Still the young member of the SM family
Discovered in 1995 but almost everything to learn
Want to measure top properties: mass, helicity, spin, charge 
but....
Need large top quark datasets
Option 1: LHC 
Option 2: Tevatron

## Top Quark Pair Production at the Tevatron

- Top pairs produced via strong interaction

- Cross section increases: 1.295  0.015

- ~15% theoretical uncertainty

- ~85%

- g

- g

- ~15%

- Run  2
- (√s = 1.96 TeV)

| Mtop                       (GeV/c2) | 
(pb) |
| --- | --- |
| 170 | 7.8 |
| 175 | 6.7 |
| 178 | 6.1 |

- Run  1
- (√s = 1.8 TeV)

- Theoretical uncertainty: ~ 15%
-  PDFs
-  Renormalization/factorization scale

- M. Cacciari et al. JHEP 0404:068 (2004)
- N. Kidonakis and R. Vogt, Phys. Rev. D 68 114014 (2003)

**Notes:**
Dominant uncertainties at NLL:
 αs value
 renorm/factorization scale (5%) 
 PDFs (7%)

## Event Signatures from tt Decay

- Final state given by the W boson decays

- Br(W  leptons) = 1/3
- Br(W  quarks)  = 2/3

- Always:
- 	2 b quarks +
- 	2 W bosons

-  BR = 44%
-  S/B ~ 1/5

-  BR = 5%
-  S/B ~1.6 – 3.0

-  BR = 30%
-  S/B ~ 1/5 – 5

-  New today (next talk)
-  BR = 21%  15%

*Br(t **** Wb) ~ 100%*

- Assuming:
- Mtop = 178 GeV/c2

## The CDF Run II Detector

-  **SVX II**
** ****5 double sided layers**
** ****r-********-z measurement**
** ****ISL**
** ****Increases coverage to |********| < 2**
** ****Impact parameter resolution**
** ****SVX/ISL: 40 ********m (incl. beam width)**
** ****L00**
** ****On beampipe**
** ****I.P. resolution improvement**
** ****20% for 1 GeV tracks**

## Lepton+Jets Event Selection

- High PT electron or muon
- ET  or PT > 20 GeV
- Lepton isolated from jets
- Large missing energy from neutrino
- MET>20 GeV
- ≥ 3 high ET>15 GeV jets
- MT(W) > 20 GeV
- HT > 200 GeV
- ≥ 1 b-tag
- ≥ 2 b-tags

- or

- Possible additional jets from
- gluon radiation (ISR, FSR)

**318 pb****-1**

**b-jet**

**jet**

**jet**

**b-jet**

**l**

****

**W + Jets Sample**

## Secondary Vertex B-Tagging Algorithm

-  Tracking improvements
-  Silicon L00
-  More forward tracks ||>1
-  Algorithm optimization
-  Loosen track selection
-  Tighten vertex quality requirements

- 20% b-jet efficiency increase

- ~ 20% b-jet efficiency increase
- ~ 30% mistag increase/jet

- New offline/ Updated tagger

- Tight/Loose Secondary Vertex Tagger

## Top Cross Section: Tight / Loose Tagger

- Acceptance and efficiency from Pythia MC
- Efficiency corrected with data/MC SF

|  | Top Tagging Efficiency/Evt (%) |  |  |
| --- | --- | --- | --- |
|  | Tight  | Loose | Gain |
| 1-tag | 60  3 | 69  4 | 15% |
| 2-tag | 16  4 | 23  4 | 44% |

- Backgrounds:
- Wbb,Wcc,Wc
- ALPGEN+HERWIG MC
- Normalized to pretag W+jets data
- W+light (mistags)
- Mistag matrix from jet sample
- Applied to pretag W+jets data
- Non-W
- From data
- Electroweak (single top, WW, WZ, Z->  
- From Pythia MC
- Small contribution

## Top Cross Section (Tight Tagger)

| Sample | Events | tt fraction | (tt ) |
| --- | --- | --- | --- |
|   1 b-tag | 138 | 81% |  |
|   2 b-tags | 33 | 91% |  |

- Expectation for
- mtop = 178 GeV

**Measured **
**cross section**

- Signal region

- Systematics

- B-Tagging: 5.2%
- Lepton Isolation: 5%
- W+Heavy Flavor: 4.4%
- Luminosity: 5.9%
**Total: 11%**

**Notes:**
Add expected S/B ratio at 6.1 pb

## Top Cross Section (Loose Tagger)

| Sample | Events | tt fraction | (tt ) |
| --- | --- | --- | --- |
|   1 b-tag | 174 | 73% |  |
|   2 b-tags | 54 | 92% |  |

- Expectation for
- mtop = 178 GeV

**Measured **
**cross section**

- Signal region

- ≥2 b-tags

- Systematics

- B-Tagging: 13.4%
- Lepton Isolation: 5%
- W+Heavy Flavor: 3.0%
- Luminosity: 5.9%
**Total: 17%**

**Notes:**
Add expected S/B ratio at 6.1 pb

## Top Cross Section Using Kinematics in a Neural Net

- Method uses pretag sample
- Independent of b-tagging
- Top kinematics and event shape information combined in a NN
- Updated result
- 194 pb-1                      347 pb-1
- Lepton + Jets Selection
- No HT or MT cuts
- Additional QCD CUT:
-  cut: 0.5 < (MET-leading jet) < 2.5 for MET < 30 GeV

-  3-Jet Sample:
-     a priori most sensitive
-  4-Jet Sample:
-     better S:B  cross check

##  The Neural Network

-  The Neural Network

- Seven input variables
*H**T*
- Aplanarity
- Maximum jet **
- *E**T *(Jets 3, 4, and 5)
- *p**Z*/ *E**T*
- Minimum dijet invariant mass
- Minimum dijet separation (*R*)

-  Signal:
-  PYTHIA *tt* MC
-  Background:
-  ALPGEN+HERWIG
*   **W* + 3*p* and *W* + 4*p* MC
-  Other backgrounds are ignored in the training

**Notes:**
Make a nice NN plot with nodes and stuff?

## NN Analysis Results

- tt and W-background float
- multijet fixed to 4.6%

| Sample | Events | Fitted tt | (tt ) |
| --- | --- | --- | --- |
| W +  3 jets | 936 | 148.2  20.6 | 6.0  0.8  1.0 pb |
| W +  4 jets | 210 | 80.9  15.0 | 6.1  1.1  1.4 pb |

| Systematics | Total |
| --- | --- |
| Jet Et Scale | 8.3% |
| W+jets Q^2 Scale | 10.2% |
| ttbar PDF | 4.4% |
| Total | 16.4% |

- Fit NN output from data to NN templates

**Templates**

## Cross Section Dependence on Top Mass

- Summer 2005 World Average Top Mass
-  172.7  2.9 GeV/c2
- (hep-ex/0507091)

- Theoretical prediction:

- Acceptance and efficiency depend on top mass

- Default:
-  mtop = 178 GeV

## Summary

| Events | Relative Uncertainty |
| --- | --- |
| 936 | 21% |
| 174 | 16% |
| 138 | 16% |
| 54 | 23% |
| 33 | 27% |

- Old: ~200 pb-1

- New: ~350 pb-1

| Relative Uncertainty |
| --- |
| 28% |
| --
28% |
| --
47% |

- Overlap: single/double tag

- Overlap: loose/tight tagger

- 31% loose
- 24% tight

- 79% single
- 61% double

## Conclusions

- Experimental uncertainty has reached
- the theory uncertainty level

- Multiple tagging:
-   120 double tagged top events in 1 fb-1
-  Full reconstruction of events
-  More precise measurement of top mass
-  Study of top properties

**Starting Probe of**

**1 fb****-1 ****winter 2006**

**QCD**
**New Physics**

- Measurement limited by systematic uncertainties

## BACKUP SLIDES

## Impact Parameter Resolution with L00

- In material (hybrids) region

- In silicon region

## HT Optimization

## Secondary Vertex Taggers

- JET 50

- 20% b-jet efficiency increase

## Tagger Efficiency

- 20% efficiency increase in data

**Efficiency per jet**

**Efficiency per top event**

## Systematic Uncertainties (Tight Tagger) 

**Notes:**
Merge with previous slide.

## Cross Checks Summary

##  The Neural Network

- Seven input variables
*H**T*
- Aplanarity
- Maximum jet **
- *E**T*(Jets 3,4, and 5)
- *pZ*/ *ET*
- Minimum dijet invariant mass
- Minimum dijet separation (*R*)
- NN structure
- Seven input nodes
- One hidden layer with seven nodes
- One output node
- signal target = 1, background = 0
- Feed-forward network

## Systematics

|  |  3 Jets |  |  |   4 Jets |  |  |
| --- | --- | --- | --- | --- | --- | --- |
| Effect | Acceptance | Shape | Total | Acceptance | Shape | Total |
| Jet Et Scale | 3.0% | 5.4% | 8.3% | 8.6% | 3.3% | 11.8% |
| W+jets Q^2 Scale |  | 10.2% | 10.2% |  | 16.0% | 16.0% |
| QCD fraction |  | 0.9% | 0.9% |  | 1.8% | 1.8% |
| QCD shape |  | 1.0% | 1.0% |  | 2.5% | 2.5% |
| Other EWK |  | 1.0% | 1.0% |  | 1.1% | 1.1% |
| ttbar PDF | 1.5% | 2.9% | 4.4% | 2.4% | 2.3% | 4.7% |
| ttbar ISR | 0.4% | 1.2% | 1.6% | 2.0% | 0.6% | 2.6% |
| ttbar FSR | 0.8% | 0.7% | 1.5% | 0.7% | 0.2% | 0.8% |
| ttbar generator | 1.7% | 0.9% | 2.6% | 4.4% | 0.2% | 4.5% |
| Lepton ID/trigger | 1.3% |  | 1.3% | 1.3% |  | 1.3% |
| Lepton Isolation | 5.0% |  | 5.0% | 5.0% |  | 5.0% |
| Luminosity |   |   | 5.8% |   |   | 5.8% |
| Total |   |   | 16.4% |   |   | 22.8% |

## NN Training and Templates 

- Trained using Root_JetNet

- (4)
- Make templates of the NN output distribution for signal and all backgrounds

- (3)
- Use PYTHIA *tt* MC to model signal
-  Use ALGEN+HERWIG *W* + 3*p* and      *W* + 4*p* MC to model background
-  Other backgrounds are ignored in the training

## Fit NN output from data to NN templates to determine tt fraction

- tt and W-background float
- QCD fixed to 4.6%

| Sample | Events | Fitted tt | (tt ) |
| --- | --- | --- | --- |
| W +  3 jets | 936 | 148.2  20.6 | 6.0  0.8  1.0 pb |
| W +  4 jets | 210 | 80.9  15.0 | 6.1  1.1  1.4 pb |

## Cross Section Dependence on Top Mass

**Tight Secondary Vertex**

**Loose Secondary Vertex**

## Cross Section Dependence on Top Mass

- Summer 2005 World Average Top Mass
-  172.7  2.9 GeV/c2
- (hep-ex/0507091)

## Center of Mass Energy Dependence

- Both cross section results are consistent
- with top mass measurement (172.7 GeV)

## Extra Lepton+Jets Cross Section Measurements

**SLT Cross Section**

**Jet Probability **

**To be updated soon**

## Soft Muon Tagger Cross Section

**200 pb****-1**

**To be updated soon**

- Top Event Tag Efficiency: 15%
- False Tag Rate: 3.6%/jet

**Soft Muon Tagger**