ATLFAST CORRECTORS VERSION 15.6.1.2 FOR 10TEV

Efficiencies and Contaminations

I have produced a revised set of efficiencies and contaminations for e, gamma and jets using athena version 15.6.1.2. Here I will present the new efficiencies and investigate the cause of efficiencies and contaminations changes. I will start by giving details on how to produce the efficiencies and contaminations.

Producing Efficiencies and Contaminations

Checking Out And Setting Up AnalysisSkeleton.py

Before we can produce the efficiencies and contaminations we must check out the effmisid package. Once you have set up CMT and CVS we can checkout effmisid package (consult logfile ATLFAST-EFF-CON.txt for a quick guide on how to do this).

When checking out effmisid remember to make a new directory to check effmisid into.

Once effmisid is checked out you will find the following files.

• Analysis2.cxx
• Analysis2.h
• AnalysisSkeleton.cxx
• AnalysisSkeleton.h
• mytry.C
• mytry_eta.C
• AnalysisSkeleton_jobOptions.py

I will describe briefly the purpose of the files. Analysis2.cxx and Analysis2.h create histograms of the ntuples from the truth and reconstructed containers. mytry.C and mytry_eta.C plot the efficiencies and contaminations from the histograms. mytry.C and mytry_eta.C also produces the .dat files that are used in AtlfastC.

AnalysisSkeleton.cxx and AnalysisSkeleton.h are responsible for making the ntuple from a AOD dataset (e.g. Z->ee). You must copy these two files to src and UserAnalysis directories in the athena PhysicsAnalysis package you set up. Once These files are copied, compile CMT by using

CMT bro gmake

. We are now ready to run athena with our new AnalysisSkeleton. First, we must copy AnalysisSkeleton_jobOptions.py to our run directory.

• IMPORTANT- You will have to included a bug fix in the AnalysisSkeleton_jobOptions.py, as the container name for Tower jets has change in version 15 from version 14. The line of code that you have to insert is shown below.

import JetRec.ParticleJetCompatibility

We can now run over a sample and start to produce efficiencies. I have included a logfile below that outlines the steps for producing efficiencies.

• Logfile for producing Atlfast efficiencies and contaminations

Electron Efficiencies and Contaminations using a Z->ee dataset

The efficiencies presented here are produced using version 15.6.1.2 of athena. I will compare these efficiencies with version 14.5.0 efficiencies produced by Catherine Wright and version 15 efficiencies from the e/gamma group.

Loose Electrons

Fig 1.1 Fig 1.2 Fig 1.3 Fig 1.4 Fig1.5

Fig 1.6 Fig1.7 Fig1.8

Medium Electrons

Fig2.1 Fig2.2 Fig2.3 Fig2.4 Fig2.5

Fig2.6 Fig2.7 Fig2.8

Tight Electrons

Fig3.1 Fig3.2 Fig3.3 Fig3.4 Fig3.5

Fig3.6 Fig3.7 Fig3.8

Electron Efficiencies and Contaminations using a ttbar dataset

Loose Electrons

Fig4.1 Fig4.2 Fig4.3 Fig4.4 Fig4.5

Fig4.6 Fig4.7 Fig4.8

Medium Electrons

Fig5.1 Fig5.2 Fig5.3 Fig5.4 Fig5.5

Fig5.6 Fig5.7 Fig5.8

Tight Electrons

Fig6.1 Fig6.2 Fig6.3 Fig6.4 Fig6.5

Fig6.6 Fig6.7 Fig6.8

Photon Efficiencies and Contaminations using a H->gamgam dataset

Photon Efficiency

Fig4.2

Photon to Electron Contamination

Fig5.1 Fig5.2 Fig5.3 Fig5.3 Fig5.4

Fig5.5

Photon to C4 Jet Contamination

Fig6.1 Fig6.2

Photon to Muid Muon Contamination

Fig7.1 Fig7.2

C4 Jet Efficiencies and Contaminations using JetJet datasets

Timing Study

A timing Study for Atlfast and AtlfastC was carried out in Version 14.5.0 and Version 15.6.1.2. The samples used in this study where ttbar and Z->ee EVGEN samples. The EVGEN datasets where then put into POOLtoAtlfasttoAOD.py job option that produces an Atlfast AOD. With the AOD we create a corrected AOD using AtlfastC_AODtoAOD.py job option, resulting in an AOD with applied efficiencies to replicate the full simulation AODs.

It must also be noted that we can use the PythiatoAtlfasttoAOD.py job option to produce an Atlfast AOD.

Running POOLtoAtlfasttoAOD.py

I will now discuss the steps that where taken to produce an Atlfast AOD (I have included a Logfile below).

Changes to POOLtoAtlfasttoAOD.py

• Remember only EVGEN datasets can be read into POOLtoAtlfasttoAOD.py.

• Input dataset to Atlfast_ReadPOOLFile.py, which is located in POOLtoAtlfasttoAOD.py (need to get_file Atlfast_ReadPOOLFile.py)

• Add ChronoStat service at the end of POOLtoAtlfasttoAOD.py (This outputs the running time of Atlfast and all the Algorithms used).

# Use auditors
theApp.Dlls += [ "GaudiAud" ]
#
# write out a summary of the time spent
# write out a short message upon entering or leaving each algorithm
#
theAuditorSvc.Auditors  += [ "NameAuditor" ]
ChronoStatSvc = Service ( "ChronoStatSvc")
#ChronoStatSvc.NumberOfSkippedEventsForMemStat = 50
theAuditorSvc.Auditors  += [ "MemStatAuditor" ]
MemStatAuditor = theAuditorSvc.auditor( "MemStatAuditor" )
theApp.AuditAlgorithms=True 
MemStatAuditor.OutputLevel = INFO
#theApp.AuditServices=True

Running AtlfastC_AODtoAOD.py

I will now discuss the steps that where taken to produce an AtlfastC AOD (I have included a Logfile below).

Changes to AtlfastC_AODtoAOD.py

• Edit the input of AtlfastC_AODtoAOD.py to the output of POOLtoAtlfasttoAOD.py.

Timing Table

Results of the Timing Study

Version   |  Sample   |  ATLFAST  |  ATLFASTC  | ATLFASTC(All ALG EFF ON)
------------------------------------------------------------------------
14.5.0        Z->ee
15.6.1.2      Z->ee
         
14.5.0        ttbar
15.6.1.2      ttbar

Timing Samples

Information on the EVGEN and AOD datasets.

AMI Z->ee

• mc08.106050.PythiaZee_1Lepton.evgen.EVNT.e347

AMI ttbar

• mc08.105206.AcerMCttbarHerwig.evgen.EVNT.e429

Location of EVGEN datasets

• Z->ee

/data/atlas07/mwright/V14-Zee-EVGEN-MIKE/

• ttbar

/data/atlas04/mwright/ATLFAST/ttSamples/

Location of Atlfast AODS

• Z->ee

/data/atlas07/mwright/ATLFAST/Timings/Zee/AtlFast/

• ttbar

/data/atlas04/mwright/ATLFAST/ttSamples/ttAtlfastOutput

Running AtlFast And AtlFastC Logfiles

• Running Atlfast with PooltoAtlfasttoAOD.py JO
• Running AtlFastC with AtlfastC_AODtoAOD.py JO

-- MichaelWright - 2010-03-03