Northern Illinois University / NICADD Measurement of the tt production cross section at DØ using t + jets events Mikhail Arov, Northern Illinois University / NICADD For DØ Collaboration

Slices of the “top quark pie” By ignoring this channel we lose up to 15 % of our top events! There are as many as the and But are there really? t+jets e+jets m + jets

tgH+b SM is flavor blind, however even the simplest extension of the SM Higgs sector requires two Higgs doublets (H+ and H-) The H+ is not flavor blind. It has Yukawa coupling to leptons, preferring the heaviest – t ! In fact BR(H+gtn) >> BR(W+gln) So if charged Higgs is lighter than top, then BR(ttgt+jets) becomes enhanced due to presence of tgH+b

Importance of t channels Addition of new tt modes orthogonal to explored ones. It decreases the measurement uncertainty on s Crucial test of the SM prediction of lepton universality. The results can signal new physics! If not we can use it to constrain the parameter space Charged Higgs search is the next logical extension of this analysis

Signal characteristics q 4 jets 2 b jets Hadronic t Missing ET b W+ q t p p t nt W- Hadrons b t- nt

t decay modes Type 1 Type 2 Type 3

t ID at DØ At DØ t are identified in their hadronic modes as narrow (0.3 DR cone) jets, isolated and matched to a charged track. Hence, the 3 t candidate types are defined (roughly corresponding to the decay channels: Type 1 contains only one charged track Type 2 has one charged track and an one or more electromagnetic clusters Type 3 has more than one track (multi-prong decays) Neural Net is trained to select the “good” candidates

Dataset and preselection Since a t candidate at DØ is essentially a narrow jet, our event signature is very similar to the tt g all hadrons channel. Therefore we used the dataset collected with multijet trigger. Preselection cuts were: No isolated electrons or muons Missing ET significance > 3 Njets > 3

MET significance significance combines the probability densities of reconstructed physical objects (jets, electrons and unclustered scalar energy) to give the total likelihood of physical Probability densities of these objects are assumed to form Normal distributions, defined by the energy resolution of this object: The probability distribution is obtained as their linear combination and is also parameterized by a Gaussian: Thus the significance is defined as

Results of the preselection Wgtn ALPGEN MC samples were normalized to the published W+4j cross section of 4.5±2.2 pb. The ALPGEN value of 5.54 pb was used for tt (just as a cross check, we are measuring this value after all!) We were able to reject the bulk of the QCD background, but S:B of 1:6500 is way too low! Next we apply the b-tagging and t ID.

b-tagging and t ID results Secondary Vertex b-tagging algorithm was used Instrumental background (multijet QCD) is responsible for most of the candidate events in both types of t candidates. We need a reasonably reliable method of estimating it 9.32<<269 a S:B is very low at this stage and additional selection is needed. Topological NN (using MLPfit) was used for that On the following slide we will describe the strategy we employed to address both issues

Analysis flow Preselected dataset b - veto tagged dataset Signal tagged dataset b - veto tagged dataset t - veto tagged dataset Used for measurement Used for QCD Used for NN training

t fake rate Type 2 Type 3 We assume that all t candidates in the b-veto sample are really jets faking t Therefore, we divide the PT and h distributions for t by the ones for the jets and fit, to obtain the t fake rate! Type 1 was discarded (low signal, high fake rate) Type 2 and 3 taus are treated as separate analysis channels from now on

QCD multijet prediction The “QCD background” in this case is composed of the events with no real t lepton in them, but with one or more 0.95 NN t candidate (fakes) We assume that the probability for a jet to fake a t is . Then the probability that at least one of the jets in the event fakes t can be computed as following: Summing up such probabilities over the tagged data we obtain the QCD background prediction

And the resulting NN distributions Control plots of selected input variables and the resulting NN distributions Type 2 Type 2 And the resulting NN distributions Type 2 Type 3

Finally – the measurement ! The cross section is defined as For type 2: And for type 3:

Systematic uncertainties

b-tagging systematics

Combined cross section

Conclusions & Outlook DØ performed the first measurement of s(t + jets) on the 350 pb-1. The dominant uncertainty is statistical one, so a huge improvement is expected at 1 fb-1 and we are working. H+ search is in the works. The final answer for this analysis is

Backup Slides

t decay modes (details) The t lepton has several decay channels, classified by the number of charged particles (tracks) associated with it: electron + muon (tgenent or tgmnmnt), BR=35% charged hadron (tgp-nt), BR=12% charged hadron + ≥1 neutral particle (i.e. tgrntgnp0+p-nt), BR=38% 3 charged hadrons + ≥1 neutral hadrons, BR=15% (so called “3-prong” decays)

Dataset breakdown by trigger version The trigger (4JT10) underwent several modifications throughout Run II, reflected on the next slide In 4JT12 jet threshold was raised to 12 GeV In a HT cut of 120 GeV JT2_4JT12L_HT added

Tagged sample per type

Fit function The fitting function was the chosen to be: The PT fitting function has been picked so that it would describe the data well and at the same time would be saturated at high PT (that is we require that ):

NN variables HT – the scalar sum of all jet PTs (and t candidates) Sphericity and Aplanarity – these variables are formed from the eigenvalues of the normalized Momentum Tensor. These are expected to be higher in the top pair events then in a typical QCD event Centrality, defined as where HE is the sum of energies of the jets (and t candidates) Top and W mass likelihoods – c2-like variable. where Mt , MW, st, sW are the top and W masses (175 GeV and 80 GeV respectively) and resolution values (45 GeV and 10 GeV respectively). M3j and M2j are invariant masses of the 3 and 2 jets respectively, picked so to minimize L PT and Secondary Vertex Lifetime Significance of the leading tagged jet

NN Cut optimization Type 3 Type 2 The signal significance is defined as Type 2 Type 3

NN application results Type 2 Type 3 Same plots, “zoomed” at high NN values:

Combined cross section We combined both channels by minimizing the negative log-likelihood function defined by the following formula: where Then the combined cross section is