sample validation

We compare the events produced by different Monte-Carlo generators in order to identify and characterize the main systematic errors relevant for the measurement of . Besides our Madgraph All b samples we make also use of the following signal samples:

TABLE 1 - SIGNAL SAMPLES USED FOR THIS STUDY
Sample	Cross section (pb)
/tt0j_mT_70-alpgen/CMSSW_1_5_2-CSA07-2231/GEN-SIM-DIGI-RECO	334.51
/tt1j_mT_70-alpgen/CMSSW_1_5_2-CSA07-2211/GEN-SIM-DIGI-RECO	90.23
/tt2j_mT_70-alpgen/CMSSW_1_5_2-CSA07-2232/GEN-SIM-DIGI-RECO	18.75
/tt3j_mT_70-alpgen/CMSSW_1_5_2-CSA07-2212/GEN-SIM-DIGI-RECO	3.16

The comparison is done between inclusive distributions which means that a luminosity weighted sum of the distributions is made for each different conditions (Alpgen, Alpgen-fastsim, Madgraph). For each sample the luminosity is computed as . For each variable the distributions is weighted by and acquires the dimensions of a cross section (pb).

Top production kinematics

Cross sections

Below we compare the cross section yields, at the generator level, for our private Madgraph+PYTHIA 6 samples with other samples. For completion we show the cross section obtained when the jet matching is done using ordered showers. However in the plots shown in the subsequent paragraphs we shall make use of the samples obtained using jet matching with virtuality () ordered showers.

Table 1.1- Cross section yields for dilepton channel at generator level in pb
Event type	0 j	1 j	2 j	3 j	4 j	Total	K-factor
Madgraph + PYTHIA 6 ordered showers w/	11.00	7.97	3.53	2.10	n.a.	24.6	1.54 0.03
Madgraph + PYTHIA 6 ordered showers w/	4.43	3.97	2.54	2.92	n.a.	13.86	2.73 0.05
ALPGEN	15.2	4.1	0.85	0.14	0.04	20.34	1.86 0.03

Note that despite the large differences in the cross sections for Madgraph+PYTHIA6 obtained with different methods of jet matching the inclusive kinematics distributions for production is not affected, as it should. We also not that, depending on the parameters chosen for matching, the contribution of each jet multiplicity to the total cross section will be different. For more details see the sample validation report from MatchChecker utility. Questions:

• why does the cross section decrease so much when ordered showers are used?
• how does the jet matching procedure efficiency affect the cross section?

Kinematics

We proceed to compare the top production kinematics. You can find the basic plots in the following table. We have normalized each distribution by the luminosity of the sample used to build it and, as so, the counts are shown in units of cross section (pb).

Table 2.1 - Top kinematics at MC level (GEN)
spectrum	distribution	for the pair	between and	invariant mass of the pair

Jets

Kinematics

Table 3.1 - Jet kinematics at RECO level
Variable	RECO	RECO + matched to b-parton from top decay
Jet multiplicity		n.a.
emf (electromagnetic fraction of the energy deposit of the jets)
(b-tag discriminant for the high efficiency track counting algorithm

There is an overall good agreemenent between jet multiplicities generated by Alpgen and Madgraph. The main differences are seen in the electromagnetic fraction distribution and are most likely due to FastSim.

Leptons

Table 4.1 - Lepton kinematics at RECO level for the tt~0j samples
Lepton	Electron		Muon
Variable	RECO	RECO + matched	RECO	RECO + matched
Lepton multiplicity		n.a.		n.a.
			n.a.	n.a.
tracker iso
calo iso

From this plots we conclude that there's a good agreement between the samples. Some comments:

• there are some differences in lepton multiplicities
• the low electronic spectrum is understimated by FastSim
• for the distribution of electrons we can clearly see similar drops in FullSim and FastSim in the ECAL barrel to endcap transition ()
• there's an underestimation of the the low E/p values for electrons in FastSim

MET

Below we show the comparison of the MET. The main conclusion is that FastSim yields a softer spectrum than full simulation but is in good agreement in the region .

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-- PedroSilva - 04 Apr 2008
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