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Evidence for Evidence for Single Top Quark Production Single Top Quark Production Reinhard Schwienhorst Reinhard Schwienhorst MSU high energy seminar, 1/9/2007 Outline Motivation Preparation Optimized Event Analysis

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Evidence for Evidence for Single Top Quark Production Single Top Quark Production

MSU high energy seminar, 1/9/2007

Reinhard Schwienhorst Reinhard Schwienhorst

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Reinhard Schwienhorst, Michigan State University

Outline

  • Motivation
  • Preparation
  • Optimized Event Analysis
  • Sensitivity
  • Cross section measurement
  • |Vtb|
  • Conclusions/Outlook

Emphasis on what's new and different compared to previous analyses

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Motivation What is single top and why does it matter?

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Reinhard Schwienhorst, Michigan State University

Top Quark properties:

  • Mass, strong coupling

King of the Fermions t q q gluon t

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Top Quark properties:

New physics?

  • Coupling to Higgs?
  • Modified weak coupling?
  • SUSY? Coupling to new particles?
  • Mass, strong coupling
  • Charge, Spin
  • Electroweak interactions

– Charged current (W boson)

  • Total width
  • CKM matrix

– Neutral current (Z boson)

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W boson

Really don't know: Study in single top quark production

top quark

Top Quark properties:

  • Coupling to Higgs?
  • Modified weak coupling?
  • SUSY? Coupling to new particles?
  • Mass, strong coupling
  • Charge, Spin
  • Electroweak interactions

– Charged current (W boson)

  • Total width
  • CKM matrix

– Neutral current (Z boson)

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Top quark electroweak charged current interaction

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SM single top quark production

q q' W t b s-channel t-channel u d b t W b t W g Associated production TeV: LHC: σtot = 3 pb σtot = 326 pb

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Reinhard Schwienhorst, Michigan State University

New physics

Flavor Changing Neutral Current

q t q c Z, γ, g q q' W' t b

New heavy boson

b t W g

Modified Wtb coupling

s-channel t-channel Associated production

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Tevatron signature

q q' W b

s-channel

“tb”

t

b ν l

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Tevatron signature

q q' W

s-channel

“tb”

Cao, RS, Yuan PRD71, 054023 (2005)

g b t

b ν l

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Tevatron signature t-channel

q q' b t W

“tqb”

b b ν l

Cao, RS, Benitez, Brock, Yuan, PRD72, 094027 (2005)

g

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Results, Run I and Run II

Plus 7 PhDs so far

tqb 95% upper limit

< 5.0 pb < 58 pb < 22 pb < 25 pb < 5.0 pb < 5.0 pb

2005 “Search for Single Top Quark Production using likelihood discriminants,” DØ Note 4825 (2005).

< 4.4 pb

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Tevatron single top goals

  • Discover single top quark production!
  • Measure production cross sections

→ CKM quark mixing matrix element Vtb

  • Look for physics beyond the standard model

– Coupled to the heavy top quark

  • Study top quark spin correlations
  • Understand as background to many searches

Production cross sections: NLO calculation: 0.88 pb (±8%) 1.98 pb (±11%) current 95% CL limits, DØ: < 5.0 pb < 4.4 pb CDF: < 3.1 pb < 3.2 pb s-channel t-channel

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Preparation How do we collect a sample

  • f candidates?
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DØ

CDF

Batavia, Illinois

Experimental setup: Fermilab Tevatron in Run II

Proton-antiproton collider CM energy 1.96TeV → Energy frontier Instantaneous luminosity >250E30cm-2s-1

− ∼4 interactions per crossing, 1.7M crossing per second

→ Luminosity frontier

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Silicon Tracker Fiber Tracker

Apparatus: Run II DØ Detector

Muon System Calorimeter

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910 pb-1 analysis December 2006 370 pb-1 analysis July 2005 230 pb-1 analysis March 2005,

  • Phys. Lett. B
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Improvements

  • More than twice as much data
  • Improved W+jets background modeling
  • Fully reprocessed dataset

– New calibrations, lower thresholds, ...

  • Neural Network b-quark tagging
  • Split analysis into

12 separate channels

➔ By lepton, jet multiplicity,

tag multiplicity

  • Combined s+t search

– Assuming SM ratio

  • f cross sections
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(b) quark jet

Single top quark event selection

t

W

High-momentum lepton (ET > 15 GeV) Missing (unbalanced) energy (> 15 GeV) b-quark jet

  • Leading jet:

ET > 25 GeV

  • Second jet:

ET > 20 GeV

  • 0-2 additional jets

(ET > 15 GeV)

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W+jets Top quark pairs Single top

Event Sample Composition

(~ 1 ev pb)

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Data-background comparison

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Optimized Event Analysis How do we find the needle in the haystack?

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Multivariate Methods

Bayesian Neural Networks Boosted Decision Trees Matrix Elements

Output: signal probability Input: discriminating variables

Event energy Quark jet angle Reconstructed top spin P(signal) .....

Method: multivariate analysis

Reconstructed top mass

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  • Event kinematics

– H (total energy) – HT (transverse energy) – M (invariant mass) – MT (transverse mass) – Summing over various

  • bjects in the event
  • Angular variables

– Jet-jet separation – Jet pseudorapidity (t-channel) – Top quark spin – Sphericity, aplanarity

Discriminating Variables

49 variables total

Object kinematics

Jet pT for different jets

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Decision Trees

  • Boosting: average over many trees (~100)

– Iterative tree building: train each new tree focusing more and more on misclassified events HT>212

  • Send each event down the tree
  • Each node corresponds to a cut

– Divide sample in two: Pass↔Fail

  • A leaf corresponds to a node

without branches – Defines purity = NS/(NS+NB) from MC sample

  • Training: optimize Gini improvement

– Gini = 2 NS NB /(NS + NB)

  • Output: purity

for each event Pass Fail P F pt<31.6 P F Mt<352 purity 1

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Bayesian Neural Networks

  • NN with three layers

– 24 in put nodes (variables) – 40 hidden nodes – Each node has a weight

  • Bayesian Idea:

explore all possible weights

  • Average over 100 individual neural networks

– Each network gets a weight based on training performance

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Matrix Elements

  • Calculate signal discriminant directly for each event
  • Signal/Background probabilities are calculated from

the differential cross section

  • Calculate differential cross section for each event

based on Feynman diagram and event kinematics

  • Integrate over ME and measured momenta
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Measurement Procedure

Multivariate Output Bayesian posterior For each, measure peak position

  • Separate optimization for each process

– s-channel, t-channel

  • Different processes, sensitivity to new physics

– s+t combined

  • Assuming ratio of SM XS

– Maximize sensitivity to SM single top

σ

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Measurement Procedure

Multivariate Output Bayesian posterior For each, measure peak position

  • Separate optimization for each process

– s-channel, t-channel

  • Different processes, sensitivity to new physics

– s+t combined

  • Assuming ratio of SM XS

– Maximize sensitivity to SM single top

σ

Focus on this for the remainder of the talk!

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Ensemble Tests

– Draw ~1,000,000 “pseudo-data” sets of events from the signal+background MC

  • Bootstrap with replacement
  • Several different signal XS values

– Repeat full statistical analysis and measure σ for each

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Sensitivity, p-value

  • P-value: fraction of 0-signal ensembles measuring σ

above observed value

  • Expected p-value: fraction of 0-signal ensembles

measuring σ above SM value

  • Expected p-values:
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Test model on data

  • W+jets sample

= 2 jets, low event energy (HT (l,j) < 175 GeV)

Top quark pairs

= 4 jets, high event energy (HT (l,j) > 300 GeV)

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Results Let Data speak!

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Bayesian Neural Network

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Matrix Element

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Boosted Decision Trees

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Reconstructed top quark mass

Low DT region High DT region Signal DT region

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Summary

Submitted to PRL

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Vtb

Vtb Vtb CKM Matrix

– Weak interaction eigenstates are not mass eigenstates

Top quark must decay to a W plus a d, s, or b quark

Vtd

2 + Vts 2 + Vtb 2 = 1 → Vtb > 0.999

New physics that couples to the top quark:

Vtd

2 + Vts 2 + Vtb 2 + Vtx 2 = 1

Only weak constraints on Vtb

  • Measurement: |Vtb × fL1|

– Add uncertainties for Mtop, scale, PDF – Assume SM top quark decay

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Probability density for |Vtb fL1|2

|Vtb fL1|2

  • SM: coupling fL1 = 1

– Modified, additional couplings beyond SM

  • Assume SM coupling: |Vtb| > 0.68 at 95 % C.L.
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Separate s-channel and t-channel analyses

  • Train filters individually for s-channel and t-channel
  • Repeat statistical analysis
  • DT result:
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Conclusions/Outlook

  • We have 3.4 σ evidence for single top quark

production –|Vtb| > 0.68 at the 95 % C.L.

  • Outlook:

– Further analysis improvements – 5σ discovery – Separate s-channel from t-channel – Tevatron dataset will increase ×5 in next 2 years