The results of the first analysis to show evidence for production of single
top quarks are presented. Using 0.9 fb-1 of data collected with the D0 detector
at the Fermilab Tevatron, the analysis is performed in the electron+jets and
muon+jets decay modes, taking special care in modeling the large backgrounds,
applying a new powerful b-quark tagging algorithm and using three multivariate
techniques to extract the small signal in the data. The combined measured
production cross section is 4.8 +- 1.3 pb. The probability to measure a cross
section at this value or higher in the absence of a signal is 0.027%,
corresponding to a 3.5 standard deviation significance.Comment: 6 pages, 4 figures. Presented at 42nd Rencontres de Moriond on
  Electroweak Interactions and Unified Theories, La Thuile, Italy, 10-17 Mar
  200

Garcia-Bellido, Aran

English

arXiv

The results of the first analysis to show evidence for production of single top quarks are presented. Using 0.9 fb-1 of data collected with the D0 detector at the Fermilab Tevatron, the analysis is performed in the electron jets and muon jets decay modes, taking special care in modeling the large backgrounds, applying a new powerful b-quark tagging algorithm and using three multivariate techniques to extract the small signal in the data. The combined measured production cross section is 4.8 +- 1.3 pb. The probability to measure a cross section at this value or higher in the absence of a signal is 0.027%, corresponding to a 3.5 standard deviation significance

UNT Digital Library

Evidence for single top quark production at DØ
Ara´n Garc´ıa-Bellido
Department of Physics, University of Washington,
Seattle, WA 98195, USA
The results of the first analysis to show evidence for production of single top quarks are
presented. Using 0.9 fb−1 of data collected with the DØ detector at the Fermilab Tevatron,
the analysis is performed in the electron+jets and muon+jets decay modes, taking special
care in modeling the large backgrounds, applying a new powerful b-quark tagging algorithm
and using three multivariate techniques to extract the small signal in the data. The combined
measured production cross section is 4.8± 1.3 pb. The probability to measure a cross section
at this value or higher in the absence of a signal is 0.027%, corresponding to a 3.5 standard
deviation significance.
1 Introduction
The top quark is a very special fermion: it is by far the heaviest elementary particle discovered
so far. Its large mass gives it a prominent role in the mechanism of electroweak symmetry
breaking, since the Higgs boson coupling to fermions is proportional to their mass, and hence
top quarks and Higgs bosons have a coupling strength of order unity. Top quarks also decay
before they hadronize and thus pass their kinematic properties to the decay products, that can
be then used to study the nature of “bare” quarks. The study of this elusive quark has provided
us with some new insights into its properties recently, like its charge of 2/3e, its dominant decay
to a W boson and a bottom quark, and its production cross section and mass, these last two
being measured with ever increasing precision since its discovery.
Top quarks were first observed produced in tt¯ pairs via the strong interaction at the Tevatron
collider in 1995. In the standard model (SM), top quarks are also expected to be produced via
the exchange of a W boson in s- or t-channel. The final state in these channels thus consists
of one “single” top quark together with a b quark in the s-channel (tb) and an additional light
quark in the t-channel (tqb). Single top quarks can also be produced in association with a
W boson (tW ), but the cross section for this process at the Tevatron is very small and will
FERMILAB-CONF-07-144-E
be ignored here. The next-to-leading order prediction for the s-channel single top quark cross
section is σ(pp¯ → tb + X) = 0.88 ± 0.11 pb, and for the t-channel process, the prediction is
σ(pp¯ → tqb + X) = 1.98 ± 0.25 pb 1.
Both the CDF and DØ collaborations have performed searches for this process in the past 2.
In Run II, the best 95% C.L. upper limits published to date are σ(pp¯ → tb + X) < 6.4 pb and
σ(pp¯ → tqb + X) < 5.0 pb 3. The analysis presented here, described in more detail in Ref. 4,
draws many techniques and experience from the previous DØ analyses, where it was made clear
that multivariate techniques are necessary to be sensitive to the SM production cross section
with limited data statistics.
2 Event selection
The data used in this search was collected from 2002 to 2005 with triggers that required an
electron or a muon and at least one jet. The average trigger efficiency for e+jets events is 86%
and 87% in the t- and s-channels, and for µ+jets, 82% and 87% in t- and s-channels signal
samples respectively. Events are required to have exactly one isolated electron (muon) with
pT > 15 GeV (18 GeV) within |η| < 1.1 (2.0), and 6ET > 15 GeV. Events are also required to
contain two, three or four jets, using a cone algorithm with radius R =
√
(∆y)2 + (∆φ)2 = 0.5
(where y is rapidity and φ is azimuthal angle) to cluster energy deposits in the calorimeter.
The leading jet has pT > 25 GeV and |η| < 2.5, the second leading jet has pT > 20 GeV and
|η| < 3.4, and subsequent jets have pT > 15 GeV and |η| < 3.4.
The selection requirements described above achieve a summed signal to background ratio
of around 1:180, with an acceptance of around 5.0% and 4.5% for s- and t-channel events
respectively. To enhance the signal content of the selection, at least one jet in the event is
required to be identified as a b-quark jet. A neural network 5 has been used to identify jets
originating from long-lived b hadrons. The variables used to identify such jets rely on the
presence and characteristics of a secondary vertex and tracks with high impact parameters inside
the jet. These variables, ranked in order of separation power, are: (i) decay length significance
of the Secondary Vertex Tagger (SVT); (ii) weighted combination of the tracks’ IP significances;
(iii) JLIP probability (that the jet originates from the primary vertex based on the Jet LIfetime
Probability algorithm); (iv) χ2 per degree of freedom of the SVT secondary vertex; (v) number
of tracks used to reconstruct the secondary vertex; (vi) mass of the secondary vertex; and (vii)
number of secondary vertices found inside the jet. For a 0.5% light-jet (mis)tag rate, we obtain
a 50% average tag rate in data for b jets with |η| < 2.4.
By requiring events to have at least one b-tagged jet, the signal to background ratio is
enhanced to 1:22 on the sum of all channels, and the most sensitive channel, with two jets and
one b-tagged jet, reaches a signal to background ratio of 1:10. The acceptance after b-tagging
is reduced to 3.2% in the s-channel and 2.1% in the t-channel. The final event yields after
b-tagging are given in Table 1, shown separated only by jet multiplicity. Figure 1 shows the
data-background agreement in six basic distributions for all the channels combined.
3 Background normalization and agreement with data
Looking at Tab. 1, it is evident that if we are to reliably extract such a small signal from such
large backgrounds (around 62 expected signal events from a total of 1,398 data events, where the
error on the total background prediction is larger than the expected signals) we need to make
sure the backgrounds are properly modeled in both their kinematics and overall normalization.
The tt¯ background is normalized to the integrated luminosity times the predicted tt¯ cross
section of 6.8+0.6
−0.5 pb
6. The W+jets background, together with the multijet background, is
Table 1: Numbers of expected and observed events in 0.9 fb−1 for e and µ, 1 b tag and 2 b tag channels combined.
The total background uncertainties are smaller than the component uncertainties added in quadrature because
of anticorrelation between the W+jets and multijet backgrounds resulting from the background normalization
procedure.
Source 2 jets 3 jets 4 jets
tb 16 ± 3 8 ± 2 2 ± 1
tqb 20 ± 4 12 ± 3 4 ± 1
tt¯→`` 39 ± 9 32 ± 7 11 ± 3
tt¯→`+jets 20 ± 5 103 ± 25 143 ± 33
Wbb¯ 261 ± 55 120 ± 24 35 ± 7
Wcc¯ 151 ± 31 85 ± 17 23 ± 5
Wjj 119 ± 25 43 ± 9 12 ± 2
Multijets 95 ± 19 77 ± 15 29 ± 6
Total background 686 ± 41 460 ± 39 253 ± 38
Data 697 455 246
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T
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Figure 1: Data-background agreement distributions for all channels combined for the lepton pT, 6ET , leading jet
pT, second leading jet pT, the invariant mass of all jets, and the invariant mass of the reconstructed W together
with the b-tagged jet. The hashed bands show the ±1 standard deviation uncertainty on the background.
normalized to the data in each channel (defined by lepton flavor and jet multiplicity) before
b-tagging.
A second normalization to data is performed in order to determine how much of the total
W+jets sample is actually made of heavy-flavor jets, i.e. the fraction of Wbb¯ and Wcc¯ in the
total W+jets sample. Wc+jets is included in our model together with other W+light-quark
jets, i.e.: inside Wjj in Tab. 1. The heavy-flavor fraction is determined in our selected data on
those events in which the neural network b-tagger fails to find a b jet of the required quality.
This sample of events is not used for the signal measurement and has approximately the same
heavy-flavor composition as the signal sample. We find that a constant scale factor of 1.5± 0.45
applied to the Wbb¯ and Wcc¯ components is necessary to achieve a good description of the data.
The uncertainty assigned to this factor covers the expected dependence on event kinematics and
the assumption that the scale factor is the same for Wbb¯ and Wcc¯.
This constant heavy-flavor scale factor which absorbs higher order effects 7, was found to
give overall a very good description of the data. It was checked that the most sensitive variables
had well described shapes, specifically those distributions expected to suffer the largest shape
dependence from higher order corrections, like the invariant mass of the two leading jets and the
pT of the b-tagged jet. Two control samples, one enriched in W+jets events and the other in tt¯
events, were also used to check for shape disagreements in the background model description of
the data, and overall good agreement was found.
4 Systematic errors
The dominant contributions to the uncertainties on the backgrounds come from: normalization
of the tt¯ background (18%), which includes a term to account for the top quark mass uncertainty;
normalization of the W+jets and multijet backgrounds to data (17–27%), which includes the
uncertainty on the heavy-flavor fraction of the model; and the b-tagging probabilities (12–17%
for double-tagged events). The uncertainty on the integrated luminosity is 6%; all other sources
contribute at the few percent level. The uncertainties from the jet energy scale corrections and
the b-tagging probabilities affect both the shape and normalization of the simulated distributions.
The 30% error assigned to the heavy-flavor fraction is by far the dominant uncertainty in the
final cross section measurement. The implied uncertainty in the cross section is nevertheless not
directly 30% because it only affects two sources of the background (before b-tagging is applied)
and it gets further reduced when taking into account the first normalization of W+jets and QCD
to data, such that in the end, the total uncertainty on the sum of W+jets and QCD yields is
between 17 and 27% (depending on the channel), including the heavy-flavor factor uncertainty.
5 Final separation methods and cross section measurements
Three separate multivariate techniques have been employed in DØ to extract the signal from
the data: Boosted Decision Trees 8, Matrix Elements discriminants 9 and Bayesian Neural Net-
works 10. The output distributions in the most sensitive channel, shown in Fig. 2 for the three
methods, also demonstrate good overall agreement between data and background.
In order to extract the maximum information from the discriminant outputs, instead of cut-
ting on the outputs and counting events, the full distributions are fed into a Bayesian statistical
analysis to measure the single top quark production cross section. The expected and observed
cross section results are summarized in Fig 3. The uncertainties include statistical and system-
atic components combined. The data statistics contribute 1.2 pb to the total 1.4 pb uncertainty
on the tb+tqb cross section for the DT analysis. The significance is measured re-running the
analysis on 70,000 pseudo-datasets generated with all the uncertainties on the background model
taken into account, but including only background sources. Thus we obtain the probability for
the background-only hypothesis to fluctuate up to give the measured (or SM) value of the tb+tqb
cross section or greater.
To verify the kinematics of the selected events in the most discriminant region of the DT
outputs, the t-channel characteristic distribution of Q(lepton)×η(untagged leading jet) is plotted
in different slices of the DT output in Fig. 4. Requiring higher DT outputs clearly selects more
signal-like data and the distinct asymmetric signal shape can be seen taking form.
The three analyses are highly correlated since they all use the same signal and background
models and data, with almost the same systematic uncertainties. The correlation between
the three methods has been measured in fake pseudo data-sets (which include the systematic
uncertainties on our background model), with the SM single top cross section. The best linear
unbiased estimator (BLUE) has been applied to the three measured values and their correlations
to give a combined measured cross section of σ(pp¯ → tb + X, tqb + X) = 4.8 ± 1.3 pb, which
corresponds to a significance of 0.027% (or 3.5 standard deviations).
tb Discriminant
0 0.2 0.4 0.6 0.8 10
20
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220 tb Discriminant : e+jets w/ =2 Jets and =1 TagKS: 1 Data
tb
tqb
Wbb
wcc
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QCD
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BNN_output
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10
20
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80
100
CC_EqOneTag_EqTwoJet Data
s+t
Wbb
WccWlp
ttbar+lj
ttbar+llFake lepton
D0 Run II Priliminary 910 pb-1
Figure 2: Output distributions in the electron channel with two jets, one of them b-tagged, for the Decision Tree
discriminant (left), for the Matrix Element tq discriminant (center), and for the Bayesian Neural Net discriminant
(right).
-5 0 5 10 15
 DØ Run II                                                   0.9 fb-1
σ(pp_  → tb+tqb) [pb]
Decision trees
Matrix elements
Bayesian NNs
Combination
Z. Sullivan, PRD 70, 114012 (2004), mt = 175 GeV
N. Kidonakis, PRD 74, 114012 (2006), mt = 175 GeV
4.9 +1.4
-1.4 pb
4.6 +1.8
-1.5 pb
5.0 +1.9
-1.9 pb
4.8 +1.3
-1.3 pb
σ(tb + tqb) [pb] Significance
Expected Observed Expected Observed
DT 2.7+1.6
−1.4 4.9± 1.4 2.1σ 3.4σ
ME 3.0+1.8
−1.5 4.6
+1.8
−1.5 1.8σ 2.9σ
BNN 3.2+2.0
−1.8 5.0± 1.9 1.3σ 2.4σ
Figure 3: The observed results including the combination (left); and the expected and observed cross sections
and significance for the three different multivariate analyses (right).
6 Measurement of |Vtb|
We use the decision tree measurement of the tb+tqb cross section to derive a first direct mea-
surement of the strength of the V − A coupling |Vtbf
L
1 | in the Wtb vertex, where f
L
1 is an
arbitrary left-handed form factor 11. We measure |Vtbf
L
1 | = 1.3 ± 0.2. This measurement as-
sumes |Vtd|
2 + |Vts|
2  |Vtb|
2 and a pure V−A and CP-conserving Wtb interaction. Assuming
in addition that fL1 = 1, we obtain 0.68 < |Vtb| ≤ 1 at 95% C.L.. These measurements make no
assumptions about the number of quark families or CKM matrix unitarity.
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Figure 4: Data-background distribution of Q(lepton)×η(untagged leading jet) for three different cuts on the
tb + tqb DT output: low (DT<0.3, left plot), high (DT>0.55, middle plot), and very high (DT>0.65, right plot).
7 Summary
We have performed a search for single top quark production using 0.9 fb−1 of data collected
by the DØ experiment at the Tevatron collider. We find an excess of events over the back-
ground prediction in the high discriminant output region from three analyses and interpret it
as evidence for single top quark production. The excess has a combined significance of 3.5 stan-
dard deviations and the combined first measurement of the single top quark cross section is:
σ(pp¯ → tb + X, tqb + X) = 4.8± 1.3 pb.
Acknowledgments
I thank the organizers of the Rencontres de Moriond for the enjoyable and fruitful atmosphere
of the meeting; and the Marie Curie program of the European Union for funding my accommo-
dation at La Thuile.
References
1. Z. Sullivan, Phys. Rev. D 70, 114012 (2004).
2. Cfr. article by B. Stelzer in these proceedings; D. Acosta et al. (CDF Collaboration),
Phys. Rev. D 71, 012005 (2005).
3. V.M. Abazov et al. (D0 Collaboration), Phys. Lett. B 622, 265 (2005); V.M. Abazov et
al. (D0 Collaboration), Phys. Rev. D 75, 092007 (2007)
4. V. M. Abazov et al. (D0 Collaboration), Phys. Rev. Lett. 98, 181802 (2007)
5. T. Scanlon, “b-tagging and the search for neutral supersymmetric Higgs bosons at D0,”
FERMILAB-THESIS-2006-43.
6. N. Kidonakis and R. Vogt, Phys. Rev. D 68, 114014 (2003).
7. F. Febres Cordero, L. Reina, and D. Wackeroth, Phys. Rev. D 74, 034007 (2006); J. Camp-
bell et al., hep-ph/0611348.
8. Additional information can be found here:
http://www-d0.fnal.gov/Run2Physics/top/public/fall06/singletop/
9. DØ Conference Note 5392; and article by T. Gadfort in these proceedings.
10. DØ Conference Note 5397.
11. G.L. Kane, G.A. Ladinsky, and C.-P. Yuan, Phys. Rev. D 45, 124 (1992); A.S. Belyaev,
private communication.


Evidence for single top quark production at D0

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Evidence for single top quark production at D0

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