Top Pair Production Cross Section in the Missing ET + jets channel Public Page




Authors

G. Busetto, Giorgio Cortiana, J. Donini, T. Dorigo


INFN & University of Padova, Italy



Read read the article (Phys.Rev.Lett.96:202002,2006)
Write to the authors



Summary


We study events collected by a multi-jet trigger and selected using optimized kinematical criteria that contain jets identified in the Silicon VerteX detector as originating from b-quarks.

In a new approach, significant missing transverse energy and related geometrical properties, rather than lepton identification requirements, are used to discriminate the top quark pairs production from other background processes. Moreover, b-jet identification parametrized probabilities, measured directly from data, are used to predict the overall amount of background-produced b-jets in the kinematically selected sample.

Using 311 pb-1 of collected data, we obtain a top pair production cross section measrement of 5.8 +1.2-1.2 (stat) +0.9-0.7 (syst) pb assuming a top quark mass of 178 GeV/c2.

The acceptance calculation for these results assumes that the top mass is 178 GeV, the currently published world average. The dependence on the input top mass is shown in the figure below.


EPS

Background prediction method


The analysis rest on a method-I background prediction, that is on an overall background amount calculation. The main idea is that the probability for a jet to be identified as a b-jet is different for the ttbar pairs (our signal) and for the concurring background processes. This difference can be used to distinghisg them in the collected data.

The tagging probability for background processes is calculated using data events depleted of signal and parametrized as a function of the jet transverse energy, jet number of tracks a the missing transverse energy projection along the jet direction.

b-jet identification tagging rates (using the secondary vertex tagging algorithm) as a fucntion of the jet Et, jet number of tracks and missing energy projection along the jet direction calculated using 3-jet data events.
 EPS


We can applied the tagging rate parametrization in the form of a 3-dimensional matrix, to estimate the number of tags in the categories of events with 3, 4, 5, 6 ,7 and 8 jets, to be compared to the number of positive tags observed:

Top (botttom): observed and matrix-predicted number (average number) of positive tagged jets by jet multiplicity in the multijet data before kinematical selection.
 EPS

Kinematical selection optimization and matrix checks


The set of cuts to be applied in order to isolate top decays from the multijet background has been optimized by accounting for the expected positive tagged jets from Monte Carlo and the number of background tags provided by the matrix application to data. We scanned 1,000 set of cuts on missing et significance, aplanarity and minimum delta phi between the missing et and jet directions. By minimizing the statistical relative error on a cross section measurement we ended up with the following top five selection.



The impact of the best selection on Monte Carlo and Data sample is shown in the following table:



Once we have a defined kinematical selection predition we can check the tagging matrix prediction in control samples obtained from the data:

Matrix control region definition in the minDphi, missing et significance plane
 EPS

Tagging matrix checks in terms of observed over expected tags ratio in different control region as a function of the event jet multiplicity.
 EPS

Systematics


The summary of all the systematics sources of uncertainty is listed the following table:



Plots


Kinematical selected + >= 1 SecVtx Tags sample

Number of positive SecVtx tagged jets as a function of the jet multiplicity in the sample after the optimized kinematical selection. Data are represented by dots, the solid grey histogram shows the tagging matrix background prediction while the red and green lines represent the signal + background expectation for the inclusive and tau+jets ttbar decays respectively normalized to the theoretical cross section of 6.1 pb.
 EPS
Number of positive SecVtx tagged jets as a function of the jet multiplicity in the sample after the optimized kinematical selection. Data are represented by dots, the solid grey histogram shows the tagging matrix background prediction while the red and green lines represent the signal + background expectation for the inclusive and tau+jets ttbar decays respectively normalized to the measured cross section of 5.9 pb.
EPS
2-component fits to tagged data

2-c fit to the missing transverse energy distribution of tagged and kinematically selected data to the sum of signal and background templates. The light blue shaded area represent the fit result and its associated error while the purple and green histograms represent the signal and background templates respectively, both normalized to the fit results.
 EPS
2-c fit to the delta phi distribution between missing energy and tagged jet in the tagged and kinematically selected data to the sum of signal and background templates. The light blue shaded area represent the fit result and its associated error while the purple and green histograms represent the signal and background templates respectively, both normalized to the fit results.
EPS

Signal fraction in the tagged and kinematically selected sample obtained by tags counting and kinematical fits. All the determination are compatible with each other.
EPS


Last modified: Wed Oct 25 14:16:04 CEST 2006