1 / 29

Measurement of the tt production cross section at D Ø using t + jets events

Measurement of the tt production cross section at D Ø 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

imaldonado
Download Presentation

Measurement of the tt production cross section at D Ø using t + jets events

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

  2. 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

  3. tgH+b • SM is flavor blind, however even the simplest extension of the SM Higgs sector requires two Higgs doublets (H+ andH-) • 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

  4. 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

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

  6. t decay modes Type 2 Type 3 Type 1

  7. 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

  8. 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

  9. MET significance • 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 significance combines the probability densities of reconstructed physical objects (jets, electrons and unclustered scalar energy) to give the total likelihood of physical

  10. Results of the preselection • WgtnALPGEN 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.

  11. 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

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

  13. 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

  14. 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

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

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

  17. Systematic uncertainties

  18. b-tagging systematics

  19. Combined cross section

  20. 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

  21. Backup Slides

  22. t decay modes (details) The t lepton has several decay channels, classified by the number of charged particles (tracks) associated with it: • electron + muon (tgenentor 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)

  23. 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

  24. Tagged sample per type

  25. 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 ):

  26. 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, sWarethe top and W masses (175 GeV and 80 GeV respectively) and resolution values (45 GeV and 10 GeV respectively). M3jand 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

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

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

  29. 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

More Related