Article
Reference
Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and b -Quark Jets in pp Collisions at s√=1.96 TeV
CDF Collaboration
CLARK, Allan Geoffrey (Collab.), et al.
Abstract
We report on a search for the standard model Higgs boson produced in association with a W or Z boson in pp collisions at s√=1.96 TeV recorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2.1 fb−1. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of a b hadron.
We find good agreement between data and background predictions. We place 95%
confidence level upper limits on the production cross section for several Higgs boson masses ranging from 110 GeV/c2 to 150 GeV/c2. For a mass of 115 GeV/c2 the observed (expected) limit is 6.9 (5.6) times the standard model prediction.
CDF Collaboration, CLARK, Allan Geoffrey (Collab.), et al . Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and b -Quark Jets in pp Collisions at s√=1.96 TeV. Physical Review Letters , 2010, vol. 104, no. 14, p. 141801
DOI : 10.1103/PhysRevLett.104.141801
Available at:
http://archive-ouverte.unige.ch/unige:38642
Disclaimer: layout of this document may differ from the published version.
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Search for the Higgs Boson Using Neural Networks in Events with Missing Energy and b -Quark Jets in p p Collisions at ffiffiffi
p s
¼ 1:96 TeV
T. Aaltonen,24J. Adelman,14B. A´ lvarez Gonza´lez,12,wS. Amerio,44b,44aD. Amidei,35A. Anastassov,39A. Annovi,20 J. Antos,15G. Apollinari,18A. Apresyan,49T. Arisawa,58A. Artikov,16J. Asaadi,54W. Ashmanskas,18A. Attal,4 A. Aurisano,54F. Azfar,43W. Badgett,18A. Barbaro-Galtieri,29V. E. Barnes,49B. A. Barnett,26P. Barria,47c,47aP. Bartos,15
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0031-9007=10=104(14)=141801(7) 141801-1 Ó 2010 The American Physical Society
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(CDF Collaboration)
1Institute of Physics, Academia Sinica, Taipei, Taiwan 11529, Republic of China
2Argonne National Laboratory, Argonne, Illinois 60439, USA
3University of Athens, 157 71 Athens, Greece
4Institut de Fisica d’Altes Energies, Universitat Autonoma de Barcelona, E-08193, Bellaterra (Barcelona), Spain
5Baylor University, Waco, Texas 76798, USA
6aIstituto Nazionale di Fisica Nucleare Bologna, Bologna, Italy
6bUniversity of Bologna, I-40127 Bologna, Italy
7Brandeis University, Waltham, Massachusetts 02254, USA
8University of California, Davis, Davis, California 95616, USA
9University of California, Los Angeles, Los Angeles, California 90024, USA
10University of California, San Diego, La Jolla, California 92093, USA
11University of California, Santa Barbara, Santa Barbara, California 93106, USA
12Instituto de Fisica de Cantabria, CSIC-University of Cantabria, 39005 Santander, Spain
13Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
14Enrico Fermi Institute, University of Chicago, Chicago, Illinois 60637, USA
15Comenius University, 842 48 Bratislava, Slovakia; Institute of Experimental Physics, 040 01 Kosice, Slovakia
16Joint Institute for Nuclear Research, RU-141980 Dubna, Russia
17Duke University, Durham, North Carolina 27708, USA
18Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
19University of Florida, Gainesville, Florida 32611, USA
20Laboratori Nazionali di Frascati, Istituto Nazionale di Fisica Nucleare, I-00044 Frascati, Italy
21University of Geneva, CH-1211 Geneva 4, Switzerland
22Glasgow University, Glasgow G12 8QQ, United Kingdom
23Harvard University, Cambridge, Massachusetts 02138, USA
24Division of High Energy Physics, Department of Physics, University of Helsinki and Helsinki Institute of Physics, FIN-00014, Helsinki, Finland
25University of Illinois, Urbana, Illinois 61801, USA
141801-2
26The Johns Hopkins University, Baltimore, Maryland 21218, USA
27Institut fu¨r Experimentelle Kernphysik, Karlsruhe Institute of Technology, D-76131 Karlsruhe, Germany
28Center for High Energy Physics: Kyungpook National University, Daegu 702-701, Korea;
Seoul National University, Seoul 151-742, Korea;
Sungkyunkwan University, Suwon 440-746, Korea;
Korea Institute of Science and Technology Information, Daejeon 305-806, Korea;
Chonnam National University, Gwangju 500-757, Korea;
Chonbuk National University, Jeonju 561-756, Korea
29Ernest Orlando Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
30University of Liverpool, Liverpool L69 7ZE, United Kingdom
31University College London, London WC1E 6BT, United Kingdom
32Centro de Investigaciones Energeticas Medioambientales y Tecnologicas, E-28040 Madrid, Spain
33Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
34Institute of Particle Physics: McGill University, Montre´al, Que´bec, Canada H3A 2T8;
Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6;
University of Toronto, Toronto, Ontario, Canada M5S 1A7; and TRIUMF, Vancouver, British Columbia, Canada V6T 2A3
35University of Michigan, Ann Arbor, Michigan 48109, USA
36Michigan State University, East Lansing, Michigan 48824, USA
37Institution for Theoretical and Experimental Physics, ITEP, Moscow 117259, Russia
38University of New Mexico, Albuquerque, New Mexico 87131, USA
39Northwestern University, Evanston, Illinois 60208, USA
40The Ohio State University, Columbus, Ohio 43210, USA
41Okayama University, Okayama 700-8530, Japan
42Osaka City University, Osaka 588, Japan
43University of Oxford, Oxford OX1 3RH, United Kingdom
44aIstituto Nazionale di Fisica Nucleare, Sezione di Padova-Trento, I-35131 Padova, Italy
44bUniversity of Padova, I-35131 Padova, Italy
45LPNHE, Universite Pierre et Marie Curie/IN2P3-CNRS, UMR7585, Paris, F-75252 France
46University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
47aIstituto Nazionale di Fisica Nucleare Pisa, I-56127 Pisa, Italy
47bUniversity of Pisa, I-56127 Pisa, Italy
47cUniversity of Siena, I-56127 Pisa, Italy
47dScuola Normale Superiore, I-56127 Pisa, Italy
48University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
49Purdue University, West Lafayette, Indiana 47907, USA
50University of Rochester, Rochester, New York 14627, USA
51The Rockefeller University, New York, New York 10021, USA
52aIstituto Nazionale di Fisica Nucleare, Sezione di Roma 1, I-00185 Roma, Italy
52bSapienza Universita` di Roma, I-00185 Roma, Italy
53Rutgers University, Piscataway, New Jersey 08855, USA
54Texas A&M University, College Station, Texas 77843, USA
55aIstituto Nazionale di Fisica Nucleare Trieste/Udine, I-34100 Trieste, I-33100 Udine, Italy
55bUniversity of Trieste/Udine, I-33100 Udine, Italy
56University of Tsukuba, Tsukuba, Ibaraki 305, Japan
57Tufts University, Medford, Massachusetts 02155, USA
58Waseda University, Tokyo 169, Japan
59Wayne State University, Detroit, Michigan 48201, USA
60University of Wisconsin, Madison, Wisconsin 53706, USA
61Yale University, New Haven, Connecticut 06520, USA (Received 24 November 2009; published 8 April 2010)
We report on a search for the standard model Higgs boson produced in association with aWorZboson inppcollisions at ffiffiffi
ps
¼1:96 TeVrecorded by the CDF II experiment at the Tevatron in a data sample corresponding to an integrated luminosity of 2:1 fb1. We consider events which have no identified charged leptons, an imbalance in transverse momentum, and two or three jets where at least one jet is consistent with originating from the decay of abhadron. We find good agreement between data and background predictions. We place 95% confidence level upper limits on the production cross section for several Higgs boson masses ranging from110 GeV=c2to150 GeV=c2. For a mass of115 GeV=c2the observed (expected) limit is 6.9 (5.6) times the standard model prediction.
DOI:10.1103/PhysRevLett.104.141801 PACS numbers: 14.80.Bn, 13.85.Rm
The Higgs boson is the last particle of the standard model (SM) of particle physics that remains to be discov- ered. The existence of the Higgs boson is expected to be the direct physical manifestation of the mechanism that pro- vides mass to fundamental particles [1]. Expectations from electroweak data collected at the Tevatron, LEP, and SLD indirectly constrain the Higgs boson mass to mH <
157 GeV=c2 at 95% confidence level (C.L.) [2]. Direct searches at LEP have excluded mH<114:4 GeV=c2 at 95% C.L. [3]. Upper limits on the production cross section from searches in the region110< mH<135 GeV=c2 re- main well above the standard model prediction [2], and greatly benefit from improvements of the experimental sensitivity. In this mass region, bb is the main decay mode. The b quarks fragment into jets of hadrons, and the signal can be reconstructed as a resonance in the invariant mass distribution of the two jets. Large multijet backgrounds can be reduced by searching for a Higgs boson (H) with an associated vector bosonV(V ¼W,Z).
This Letter presents a search for the standard modelVH associated production in events withb-quark jets and large missing transverse energy with data corresponding to an integrated luminosity of 2:1 fb1. This analysis signifi- cantly increases the acceptance for signal with respect to previous Tevatron searches [4,5] and introduces advanced analysis methods. We considerZHproduction, whereZ! and the neutrinos () escape detection, orZ!‘‘when both charged leptons (‘) are undetected or are identified as jets. ForWH production we are sensitive to events where W !eorW !when the charged lepton is identified as a jet, andW !‘when‘is undetected. TheWHevents accepted by this analysis contain 50%W !, 30%W ! and 20%W !e. Critical challenges for this analysis are to achieve a high signal-to-background (S=B) ratio and to model the multijet background production accurately.
We employ artificial neural networks (ANNs) [6] to im- prove the event selection and signal discrimination and implement a novel data-driven determination of the multi- jet background.
CDF II is a multipurpose detector that is described in detail elsewhere [7,8]. Jets are reconstructed from energy depositions in the calorimeter towers using a jet clustering cone algorithm [9] with a cone size of radiusffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi R¼
ðÞ2þ ðÞ2
p ¼0:4. In addition to standard jet energy corrections [9], we further correct using momentum mea- surements provided by the tracker, using a method similar to that described in [10]. The more precise measurement of the jet energies improves the candidate Higgs boson mass resolution by10%and increases the signal acceptance by 10%. Both the magnitude and direction of E6 T are recomputed after the jet energies are corrected.
The events used in this search are selected by a three- level trigger system that selects events withE6 T and two jet clusters. After offline reconstruction, the event selection requiresE6 T>50 GeV, and the transverse energiesEJT1and EJT2 of the two jets with the highest transverse energy, J1
and J2 (‘‘leading jets’’), satisfy the conditions ET >
35 GeV and EJT2>25 GeV. We consider an event to have three jets if the ET of the third leading jet, J3, is greater than 15 GeV. Events with four or more jets with ET>15 GeV andjj<2:4are rejected. Events passing these criteria are denoted as the ‘‘pretagged’’ sample. After these selections, the expected S=B ratio is around 1=20 000.
We veto events with at least one pT>10 GeV=c iso- lated electron or muon [11], deliberately using fairly loose identification criteria. These selections ensure that the sample used in this analysis is statistically independent from the one utilized in the search forWHin a final state containing an identified charged lepton [12].
Large backgrounds originating from light-flavor jet pro- duction can be reduced by identifying bjets in the candi- date events. Because of their relatively long lifetime,band c hadrons can travel a few millimeters from the primary vertex before decaying into lighter hadrons. Jets originat- ing from a b quark can be identified (‘‘tagged’’) by the
SECVTXalgorithm [13], which reconstructs vertices that are significantly displaced from thepp interaction point, and theJETPROBalgorithm [14], which classifies jets using the probability that tracks within the jet are consistent with originating from the primary vertex. To enhance the ex- pected signal significance we subdivide the sample into three independent categories: events with two jets tagged by SECVTX (SVþSV), events with one jet tagged by
SECVTX and another by JETPROB (SVþJP) and events with only one jet tagged bySECVTX(SV).
The selected sample is dominated by background from the production of multijet (MJ), top quark (pair and elec- troweak production),WorZplus jets, andWW,WZorZZ events. Significant E6 T in multijet events appears whenb quarks decay semileptonically or when jet energies are mismeasured. In both cases 6~ET is often aligned with ~EJT2. Therefore, events with ð6~ET; ~EJT2Þ<0:4, no identified leptons, and 50< E6 T<70 GeV are used to measure the rates with which the heavy-flavor jets (HF, originating from a bor cquark) from multijet production and light- flavor jets mistakenly identified as bjets (‘‘mistags’’) are tagged. The tagging rate (TR) is parametrized as a function of HT [8] of the event and ET, , and of the jet. The observable is defined as ¼cP
ipiT;track=ET where piT;trackincludes tracks within a jet with a significant impact parameter and 0:5< piT;track<200 GeV=c. Jets originat- ing from b quarks are expected to have a large . The multijet background in the single (double) tagged sample is determined by the probability to tag one (two) jet(s) from the pretagged (single-tagged) sample [11,15], after sub- tracting all Monte Carlo (MC) simulated contributions.
The validity of the tagging rate modeling is verified in various control regions, which are defined below. The remaining backgrounds are estimated using PYTHIA [16]
simulations, and single top production is simulated with 141801-4
MADEVENT [17]. The signal MC samples are generated withPYTHIA. The normalizations of the MC samples are described in [11].
We start the selection of the signal region by requiring no identified charged leptons, E6 T >50 GeV, ð6~ET; ~EJT1Þ 1:5, andð6~ET; ~EJT2;3Þ 0:4. These selec- tion criteria remove 10% of the signal in the pretag sample while reducing the backgrounds by approximately an order of magnitude. We employ an ANN, denoted as ANNMJ, using kinematic variables to separate signal from multijet background. To discriminate against events with E
6 T due to mismeasurements in the calorimeter, we use the momentum imbalance in the tracker,P6 trT [8]. The magni- tude of E6 T P6 trT, the angle between them, the azimuthal angles betweenE6 T,P6 trT and the jet directions, and several other less discriminating variables are used as inputs to ANNMJ[11]. The distribution ofANNMJ, shown in Fig.1, peaks atþ1for the signal and at1for the backgrounds that are due to mismeasured jets. Selecting events with
ANNMJ0 rejects over 50% of the total background and retains 95% of the signal, yielding an S=B ratio of 1=250, which is similar to the one obtained in theWH search [12]. This region is defined as the signal region and is analyzed for the presence of the Higgs boson signal.
In order to avoid potential bias in the search, we test our understanding of the SM background in several control regions where the amount of signal events is negligible.
The control region called EWK, sensitive to electroweak processes and top production, contains events with at least one lepton andð6~ET; ~EJT2Þ 0:4. We also define several control regions dominated by multijet processes where we have no identified leptons. The region denoted as MJ1 contains events with ð6~ET; ~EJT2Þ<0:4 and E6 T 70 GeV. The region denoted as MJ2 contains events with ð6~ET; ~EJT1Þ 1:5, ð6~ET; ~EJT2;3Þ 0:4, and ANNMJ<
0:5. The predictions of the multijet background are tested in MJ1 and MJ2. The distributions of kinematic variables,
ANNMJ
-1 -0.5 0 0.5 1
Events
0 20 40 60 80 100 120
-1 -0.5 0 0.5 1
0 20 40 60 80 100
120 Data
Multi-jet
Top Pair+Single Top Diboson Z/W+h.f.
Background Uncertainty
=115 GeV/c2 5, mH
× VH
FIG. 1 (color online). The distribution ofANNMJfor double- tagged events.
2) ) (GeV/c ,J2
m(J1
Events
0 50 100 150 200 250 300 350 400 450 0
10 20 30 40
50 Data
Multi-jet Top Pair+Single top Diboson Z/W+h.f.
Background Uncertainty
=115 GeV/c2 5, mH
× VH
FIG. 2 (color online). Dijet invariant mass distribution for double-tagged events in signal region.
(a)
(b)
FIG. 3 (color online). The distribution of ANNsig for (a) single- and (b) double-tagged events.
such as the invariant mass of the two leading jetsmðJ1; J2Þ, have been found to be in agreement with observations in the control regions [11].
To achieve a greater separation between signal and background we deploy a second ANN, denoted as ANNsig, for discriminating the remaining backgrounds from the expected signal. Six input variables are used in ANNsig: the invariant mass of the two leading jetsmðJ1; J2Þ (Fig.2), the invariant mass of theE6 Tand all jets,HTE6 T, H6 T E6 T,TRACKMET[18] and the maximumRð~EJTi; ~EJTkÞ.
The variableTRACKMETis the output of a ANN developed using tracking information to enhance the separation of events with real E6 T. The most discriminating variable of theANNsigismðJ1; J2Þ.
The distribution ofANNsigis shown in Fig.3for single- and double-tagged events. The number of signal and back- ground events after the final selection are shown in TableI.
Since no significant excess is observed, we compute 95%
C.L. upper limits for the Higgs boson production cross section times the branching fraction BðH!bbÞ. For mH ¼115 GeV=c2 we expect a total of 4.0 (3.5) signal events with one (two)b-tagged jets [19].
We analyze the binnedANNsigdiscriminant distribution to test for a WH or ZH signal in the presence of SM backgrounds. The systematic uncertainties included in the calculation are classified as correlated (uncorrelated) depending on if they do (do not) affect both signal and the background processes [11,18]. The uncorrelated system- atic uncertainties are the multijet normalization (between 5.5% and 20.6%) and MC statistical fluctuations.
Additionally we assign the following uncertainties due to cross sections: 15.9% and 15.2% to single top in sand t channels, 8.6% to top pair, 11.5% to diboson and 40% to WþHFandZþHFThe shapes obtained by varying the TR probabilities by1are applied as systematic uncer- tainties to each bin ofANNsig. The correlated systematic
uncertainties are the following: luminosity measurement (6.0%), b-tagging efficiency in MC simulations (between 4.3% and 12.4%), trigger efficiency (<3%), lepton veto efficiency (2%), parton distribution function uncertainty (2%) and 3.8%–13.0% for jet energy scale (JES) [9]. We also assign systematic uncertainties on the shape ofANNsig due to JES and trigger efficiency uncertainties. Initial- and final-state-radiation systematic uncertainties (between 1%
and 5%) are applied to the signal predictions.
Including all the uncertainties, the expected and ob- served upper limits at the 95% C.L. on VH production cross section times branching fraction BrðH!bbÞ are shown in TableII. Expected limits are obtained by gener- ating pseudoexperiments from the expected SM ANNsig shapes to calculate the median ZH andWH contribution which could be excluded at the 95% C.L. in the zero signal hypothesis. The limits are computed using the Bayesian likelihood method [20] with a flat prior probability for the signal cross section and Gaussian priors for the uncertain- ties on acceptance and backgrounds. We combine the search channels SVþSV, SVþJP, and SV by taking the product of their likelihoods and simultaneously varying the correlated uncertainties. The observed limits agree with the expected ones.
In summary, we have performed a direct search for the SM Higgs boson decaying intob-jet pairs using data with integrated luminosity of2:1 fb1accumulated in Run II by the CDF II detector. The combination of all improvements described above increases the sensitivity of this search by a factor of 2 with respect to [4], and by 30% with respect to [5] once the difference in luminosity is accounted for.
We thank the Fermilab staff and the technical staffs of the participating institutions for their vital contributions.
This work was supported by the U.S. Department of Energy and National Science Foundation; the Italian Istituto Nazionale di Fisica Nucleare; the Ministry of Education, Culture, Sports, Science and Technology of Japan; the Natural Sciences and Engineering Research Council of Canada; the National Science Council of the Republic of China; the Swiss National Science Founda- tion; the A. P. Sloan Foundation; the Bundesministerium fu¨r Bildung und Forschung, Germany; the World Class University Program, the National Research Foundation of observed events in the signal region for different b-tagging
categories. The uncertainties contain both MC statistical error and systematic uncertainties.
Process SVþSVorSVþJP SV
Multijet 120:121:3 941:286:0
Single top 15:73:0 43:27:9
Top pair 54:57:9 124:517:0
Diboson 9:21:8 35:66:8
WþHF 32:014:7 296:9129:5
ZþHF 22:111:5 107:045:8
Total prediction 25439 1548:4168:1
Observed 253 1443
Expected signal formH¼115 GeV=c2
ZH!bb 1:80:2 2:10:2
WH! ð‘Þbb 1:60:2 1:80:2 ZH! ð‘‘Þbb 0:070:01 0:090:01
with ratios to SM cross section.
mH Expected Observed Ratio Ratio
(GeV=c2) (pb) (pb) expected observed
110 1.3 1.5 4:9þ2:11:4 5.8
115 1.2 1.5 5:6þ2:41:6 6.9
120 1.2 1.5 7:2þ2:92:1 8.9
130 1.0 1.4 10:3þ4:32:9 14.4
140 0.9 1.0 18:6þ7:85:4 21.0
150 0.8 1.0 43:3þ19:012:4 49.8
141801-6
Korea; the Science and Technology Facilities Council and the Royal Society, UK; the Institut National de Physique Nucleaire et Physique des Particules/CNRS; the Russian Foundation for Basic Research; the Ministerio de Ciencia e Innovacio´n, and Programa Consolider-Ingenio 2010, Spain; the Slovak R&D Agency; and the Academy of Finland.
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