search for WZ and ZZ in MET+ B JETS

Motivation

Diboson production has been observed at the Tevatron using generic jets. Doing the same thing with heavy flavor jets is much more difficult. Here we attempt to measure the diboson cross-section specifically of WZ and ZZ events using a selection with large E/T and two b jets as an additional discriminant. Due to limited energy resolution we cannot distinguish between WZ and ZZ events so what we measure is a sum of these processes in our selection window. As no cut on the number of charged leptons in the event is performed, we are also sensitive to decays of the gauge bosons with e, μ or τ leptons. We extract the signal from the background using the invariant mass distribution of the two jets in the event in a simultaneous fit of the region with no b tags and with two b tags. The extraction of the signal does not use the theoretical calculation of the V+jets integral cross section, whose invariant mass shape is cross- checked with γ+jets events from data, thereby considerably reducing the systematic uncertainty on the shape of this main background.

Trigger and dataset

The VV production and decay into hadronic final states are topologically similar to the VH production and decay which is the most promising Higgs discovery channel at low Higgs mass. Also, study of the diboson production is sensitive to extra gauge couplings not present in the Standard Model.

We start with a suite of MET based triggers and measure the trigger efficiency based on Z→μμ data. The latter is a good standard candle for MET processes because muons are minimum ionizing particles that deposit little energy in the calorimeter so from the calorimeter standpoint it looks like real MET is present in the event. Of course muonic decays of Z are easily identifiable with the muon chambers. We will do a dijet mass fit so we want to ensure the trigger has little turnon effect above our low mass boundary which is 40GeV.

There are four main classes of backgrounds we consider:

1. Electroweak (EWK): these are V+jet processes and is derived from MC.
2. Multijet: these are generic QCD jet production which can result in MET through mismeasurements of jets
3.Top: this includes both ttbar and single top production and is evaluated from MC
4.WW: This is indistinguishable from the signal in the non-btagged region. Is evaluated from MC

The expected different contributions are shown here together with the expected signal in the two search regions:

Although the normalization of the EWK background is allowed to completely float in the final fit, there is still the question of how well we understand the shape.

For this we use γ+jets data since there are similarities in the kinematics of this process and the V+jets process. In order to account for any differences in kinematics though between γ+jets and V+jets we correct the γ+jets data based on the difference between γ+jets MC and V+jets MC. This way, any production difference is taken into account, however, detector effects, PDF uncertainties, ISR/FSR, etc. cancel when using γ+jets data. After we apply this correction to the γ+jets data there is little difference between this and our V+jets MC and this difference determines our systematic uncertainty on the shape of the V+jets background shape.

For the multijet background we first try to reject as much as possible and then we use a data driven approach for the remaining contribution. The rejection is done mainly with the MET significance and Δφ (the angle between MET and the closest jet above 5GeV). The Δφ distribution is shown below (left for untagged and right for tagged regions), the analysis cut is made at 0.4

Once we cut away most of the mu

ltijet background we define another variable sensitive to this, the angle between the MET and trkMET (the missing track PT as measured in the tracking chamber). For real MET, like MET from neutrinos the two vectors will be aligned. However, for fake MET, the trkMET will not necessarily point to the same direction as MET. We can define our multijet enhanced region by selecting events for which the angle between MET and trkMET is greater than 1. The EWK MC is normalized to the peak region and checked based on Z→μμ data. To determine the shape of the QCD background we look in the sideband and correct for the difference between the sideband and the signal region with MC. For the two tagged region we do not have enough statistics to measure a shape so we use the same shape as in the no tag region.

Optimization

We optimize the bness cuts for the best sensitivity. The most optimal cuts turn out to be 0.85 and 0.0 for the two jets under consideration:

Luminosity of the sample

We determined the luminosity of the sample by counting the number of Z decays to muons that pass all our analysis cuts in our MET sample and the same number in the well understood muon triggered data. We find 5.2 fb-1 as the total effective luminosity. This also has the trigger efficiency folded in, so it is really the luminosity times trigger efficiency.

Results

After all cuts are applied we find 231232 and 1108 diboson candidate events in the no tag and double tagged regions respectively. The final dijet mass fit is an unbinned extended maximum

likelihood with all systematics treated as nuissance parameters and allowed to float in the fit within their predetermined uncertainties. The EWK normalization is also freely floating in the fit with no constraints. The table shows the results of this fit. All correlations are taken into account in the fit. The single top, ttbar and WW are constrained to the theoretical cross sections. We can translate the observed number of events into a cross section measurement of 5.0+3.6-2.5 in agreement with the SM prediction of 5.08pb. At 95%CL we can determine that the WZ+ZZ cross section to be less than 13pb.

The following table lists the systematic uncertainties affecting this measurement:

The limit is determined using a Feldman Cousins technique, shown below:

Additionally, we perform the same analysis using only double tagged events. A priori studies show that this channel alone is less powerful than the combined channels as expected. The results of the double tagged channel fit is shown below together with the FC band:

Backgrounds

B tagging

We identify b jets with on a multivariate algorithm based on a two stage neural network. The first NN is trained to separate tracks coming from B hadron decays vs other tracks based on track specific quantities (impact parameter, rapidity wrt jet axis, etc.).The output of this first stage is called track bness. All tracks are ordered in track bness and for each jet the first 5 tracks are considered. The track bness for these tracks together with other jet specific quantities (e.g. Lxy) are used in the second NN which determines the jet bness. The jet bness for b jets vs non b jets is shown here. To characterize the performance of the tagger as well as measured any differences between data and MC (scale factors) and their associated uncertainties we use ttbar and Z+jet events. The idea being that the former is enriched in b jet events and the latter in non b jet events. In order to measure the efficiency and the mistag rates the proper sample composition is evaluated.

The scale factors for the efficiency and the mistag rates together with their associated uncertainties are shown below: