Single Top Polarization analysis

Group info

  • Members: Joosep Pata, Andres Tiko, Matthias Komm, Steffen Roecker (students), Dmitri Konstantinov, Liis Rebane, Thorsten Chwalek (postdocs), Andrea Giammanco, Mario Kadastik, Jeannine Wagner-Kuhr (staff)
  • Mailing list: cms-stop-pol@cernNOSPAMPLEASE.ch

Useful papers

Models to investigate

Flavor-Changing Neutral Currents (FCNC) in tgq (q=u,c) coupling

The best limits come from ATLAS ( ref.):

  • K_tgu/Λ < 0.0069 TeV-1
  • K_tgc/Λ < 0.016 TeV-1
A different kind of search, with the same topology as we will investigate, has been performed by D0 ( ref.) obtaining these limits:

  • K_tgu/Λ < 0.013 TeV-1
  • K_tgc/Λ < 0.057 TeV-1
The D0 analysis is performed with 2.3/fb, with a Bayesian Neural Network, optimized for the processes in the figure below in the lepton + 2 jets topology. See the references in the Introduction for a nice list of new-physics models that can give an effective FCNC coupling of this kind.

FCNC tgq interactions at leading order, from D0's paper:

fcnc_tgq.jpg

The CDF ( ref.1, ref.2) and ATLAS experiments optimize instead for the diagram qg->t and therefore they investigate the lepton + 1 jet topology, see figure below (from ATLAS):

Additional jets can come from gluon radiation, therefore our kind of analysis (which needs a second jet to define the approximate spin axis) can be also sensitive to this diagram.

Comparing D0 (lepton + 2 jets) with 2.3/fb and CDF (lepton + 1 jet) with 2.2/fb, one sees that for a similar statistics the strongest limits come from D0. Therefore, the lepton + 2 jets selection might be intrinsically more sensitive to FCNC signals in the tgq coupling.

Suggestion by Lev Dudko:

since there are no any interference between Ktcg/L and Ktug/L couplings
and cross section depends quadratically from these couplings it is
enough to generate two samples for each process. One with one coupling
and another sample for the second coupling and use one of the value for
the coupling. All other values one can simulate with the same sample
with quadratic renormalization to the new value of the coupling.
Therefore, it is very simple, you can take one sample, use quadratic
parameter of the FCNC sample normalization (e.g. in distribution of the
cos_theta) and apply Theta package to find the limit for this quadratic
coupling. 

Flavor-Changing Neutral Currents (FCNC) in tγq (q=u,c) coupling

For this kind of coupling, it is difficult to improve over HERA limits from γq->t search. An alternative strategy pursued in hadron colliders is the search for t->γq decays in ttbar events (see an old MC study in CMS).

Flavor-Changing Neutral Currents (FCNC) in tZq (q=u,c) coupling

For this kind of coupling, it is difficult to improve over LEP limits from Z->tq search (see paper by ALEPH). An alternative strategy pursued in hadron colliders is the search for t->Zq decays in ttbar events (see the latest study from ATLAS and from CMS)

Anomalous tWb couplings

Latest results are from D0 ( ref.)

Samples with generic (non-left-handed) tWb couplings are being produced in Moscow.

Useful links

General Work Plan

Analysis at 7 TeV with ~1/fb

  • Reproduce TOP-11-021 selection numbers in both data and MC
  • Produce FastSim samples for models with A < 100%
  • Set up statistics macros to extract A and set upper limits on non-SM models
  • Extract from dedicated control samples the abundance and the cos θ* shape for W + light jets, ttbar, QCD
  • Evaluate all the systematics (see this wiki)
  • Get the results. No need to keep the analysis "blind" at this stage, as the main result will be the 8 TeV one. In case we will decide to use the full 7 TeV dataset, the additional statistics will be handled with the same work plan as for 8 TeV below.
Question to be answered once all data-driven background estimations and all systematics are included in the analysis: is the current definition of the θ* angle the most optimal for this analysis? What about using the "beam-line basis" instead of the "spectator basis"? (See Mahlon, Parke 2000)
  • Which of the two gives the best ΔA and the best limits when running on MC only? (Use pseudo-data diced from the overall MC expectation.)
  • Is the data-MC agreement equally satisfactory for both?
  • Is the model dependence for the W + heavy flavor background roughly the same?

Synchronization to 2011

To be performed as specified in https://twiki.cern.ch/twiki/bin/viewauth/CMS/SingleTopSync2011

The datafiles on phys are copied to /hdfs/local/stpol/sync2011

Joosep START42_V17 Lepton Veto Jet Cut MTW B-tagging
Monte Carlo, muon sel. 1183 565 263 182
Monte Carlo, electron sel. 805 426 155 101

Joosep START42_V13 Lepton Veto Jet Cut MTW B-tagging
Monte Carlo, muon sel. 1183 563 263 183
Monte Carlo, electron sel. 805 419 154 100

Synchronization of the 4_2_X code to the Naples group

Process the SbarChannel dataset /Tbar_TuneZ2_s-channel_7TeV-powheg-tauola/Summer11-PU_S4_START42_V11-v1/AODSIM and try to get the following numbers after the cuts:

globalTag=START42_V17 and doResol=True in TChannel_cfg.py

lepton id lepton jet met btag
mu 8156 3838 2103 1456
ele 5508 2560 1079 752

Correlation between costheta in the eta beamline basis and the spectator jet basis

Plots are here: http://phys.hep.kbfi.ee/~joosep/stpol/costheta_corr/

Done using UserCode/STPol/util_scripts/costheta_corr.py

Forward jet selection bias

Plots are here: http://phys.hep.kbfi.ee/~joosep/stpol/fwdJet_selection_bias/ The forward jet selection is (abs(fwdJetEta)<4.5 && abs(fwdJetEta)>2.5 && fwdJetPt>30)

The probability is calculated using the Kolmogorov test, the areas are normalized to 1.

Forward jet eta

Plots are here: http://phys.hep.kbfi.ee/~joosep/stpol/fwdJet_plots/

Analysis at 8 TeV

Note: please don't take the 7 and 8 TeV analyses as necessarily sequential. As soon as 8 TeV data arrive, it is mandatory to look at those (to validate many things: the quality of the detector and of the reconstruction, the effect of the worse pile-up conditions, to check the scaling of the backgrounds from 7 to 8 TeV) even if the 7 TeV analysis is not complete yet. Ideally, things should be done in parallel; priorities would be rediscussed at each of our weekly meetings.

  • Check data-MC agreement (in rate and in cos θ* shape) in the control samples for W + light jets, ttbar, QCD
  • Perform a MC only analysis to assess the expected sensitivity of the analysis. (Use pseudo-data diced from the overall MC expectation.)
  • Re-optimize if needed, using the control samples to quantify the non-single-top backgrounds
  • Use FastSim for non-SM signals, SM backgrounds that don't arrive quickly enough, systematic variations around the generation parameters of the SM backgrounds
  • Keep the analysis blind. In our case this means that we should abstain from looking at cosθ* in the single-top-dominated region until we are really confident that we understand the background-dominated regions and we are considering at least the main systematic uncertainties that can affect the shape of this observable and the rate of events.

Processed datasets for code HEP-KBFI/stpol

List of datasets

DYJets /DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
GJets1 /GJets_HT-200To400_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
GJets2 /GJets_HT-400ToInf_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_BCtoE1 /QCD_Pt_20_30_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_BCtoE2 /QCD_Pt_30_80_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_BCtoE3 /QCD_Pt_80_170_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_BCtoE4 /QCD_Pt_170_250_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_BCtoE5 /QCD_Pt_250_350_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_BCtoE6 /QCD_Pt_350_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM START53_V20::All  
QCD_EM1 /QCD_Pt_20_30_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_EM2 /QCD_Pt_30_80_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_EM3 /QCD_Pt_80_170_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_EM4 /QCD_Pt_170_250_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_EM5 /QCD_Pt_250_350_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_EM6 /QCD_Pt_350_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
QCD_Mu /QCD_Pt_20_MuEnrichedPt_15_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
SingleElectron _RunABCD /SingleElectron/Run2012D-22Jan2013-v1/AOD FT_53_V21_AN4::All  
SingleMu _RunABCD /SingleMu/Run2012D-22Jan2013-v1/AOD FT_53_V21_AN4::All  
Tbar_s /Tbar_s-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
Tbar_t_mass166_5 /TBarToLeptons_t-channel_mass166_5_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
Tbar_t_mass178_5 /TBarToLeptons_t-channel_mass178_5_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TbarToLeptons _t-channel /TBarToLeptons_t-channel_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
Tbar_t_scaledown /TBarToLeptons_t-channel_scaledown_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
Tbar_t_scaleup /TBarToLeptons_t-channel_scaleup_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
Tbar_t /Tbar_t-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
Tbar_tW /Tbar_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
T_s /T_s-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
TTbar_FullLept2 /TTJets_FullLeptMGDecays_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM START53_V20::All doSkimming=False
TTbar_SemiLept2 /TTJets_SemiLeptMGDecays_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A_ext-v1/AODSIM START53_V20::All doSkimming=False
TTbar /TTJets_MassiveBinDECAY_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TTJets_mass166_5 /TTJets_mass166_5_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TTJets_mass178_5 /TTJets_mass178_5_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TTJets_matchingdown /TTJets_matchingdown_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TTJets_matchingup /TTJets_matchingup_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TTJets_scaledown /TTJets_scaledown_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TTJets_scaleup /TTJets_scaleup_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
T_t_mass166_5 /TToLeptons_t-channel_mass166_5_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
T_t_mass178_5 /TToLeptons_t-channel_mass178_5_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TToBENu _anomWtb-0100 /TToBENu_anomWtb-0100_t-channel_TuneZ2star_8TeV-comphep/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TToBENu _anomWtb-unphys /TToBENu_anomWtb-unphys_t-channel_TuneZ2star_8TeV-comphep/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TToBMuNu _anomWtb-0100 /TToBMuNu_anomWtb-0100_t-channel_TuneZ2star_8TeV-comphep/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TToBMuNu _anomWtb-unphys /TToBMuNu_anomWtb-unphys_t-channel_TuneZ2star_8TeV-comphep/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TToBTauNu _anomWtb-0100 /TToBTauNu_anomWtb-0100_t-channel_TuneZ2star_8TeV-comphep/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TToBTauNu _anomWtb-unphys /TToBTauNu_anomWtb-unphys_t-channel_TuneZ2star_8TeV-comphep/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
TToLeptons _t-channel /TToLeptons_t-channel_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
T_t_scaledown /TToLeptons_t-channel_scaledown_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
T_t_scaleup /TToLeptons_t-channel_scaleup_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
T_t /T_t-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All doSkimming=False
T_tW /T_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets1 /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets2 /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM START53_V20::All  
WJets_excl1 /W1JetsToLNu_TuneZ2Star_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets_excl2 /W2JetsToLNu_TuneZ2Star_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets_excl3 /W3JetsToLNu_TuneZ2Star_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets_excl4 /W4JetsToLNu_TuneZ2Star_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets_matchingdown /WJetsToLNu_matchingdown_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets_matchingup /WJetsToLNu_matchingup_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets_scaledown /WJetsToLNu_scaledown_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WJets_scaleup /WJetsToLNu_scaleup_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM START53_V20::All  
WW /WW_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
WZ /WZ_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  
ZZ /ZZ_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM START53_V20::All  

step1

Here are the datasets processed by the (skim) + PF2PAT + (slim) code. Use the following snippet to get the list of files:

das_cli.py --query="file dataset=/T_t-channel_TuneZ2star_8TeV-powheg-tauola/jpata-stpol_step1_v2_1_noSkim-6d0886f8efd932bc8d37cab903c44a2c/USER instance=cms_dbs_ph_analysis_02" --limit=0

all MC skim, mu, ele DAS
T_t noSkim, ele, mu /T_t-channel_TuneZ2star_8TeV-powheg-tauola/jpata-stpol_step1_v2_1_noSkim-6d0886f8efd932bc8d37cab903c44a2c/USER
Tbar_t noSkim, ele, mu /Tbar_t-channel_TuneZ2star_8TeV-powheg-tauola/jpata-stpol_step1_v2_1_noSkim-6d0886f8efd932bc8d37cab903c44a2c/USER
SingleMu RunA +RunB ele, mu, 5238 pb^-1 /SingleMu/jpata-stpol_step1_v3_1-60389801c9c75bd7ec94ff0c7c5a7358/USER

step1 Feb6 rerun
source dataset destination dataset output lumi from crab [/pb]
/SingleElectron/Run2012A-recover-06Aug2012-v1/AOD /SingleElectron/joosep-step1_Data_Feb6-a67a46c387bb052b77f0782979d2cf48/USER 82
/SingleElectron/Run2012A-13Jul2012-v1/AOD /SingleElectron/joosep-step1_Data_Feb6-2cdd420c4c725097a4330835f90d1ada/USER 808
/SingleElectron/Run2012B-13Jul2012-v1/AOD /SingleElectron/joosep-step1_Data_Feb6-2cdd420c4c725097a4330835f90d1ada/USER 4423
/SingleElectron/Run2012C-24Aug2012-v1/AOD /SingleElectron/joosep-step1_Data_Feb6-2d70b925c06acab65b2731ef9f08c3c1/USER 495
/SingleElectron/Run2012C-PromptReco-v2/AOD /SingleElectron/joosep-step1_Data_Feb6-14d3879a0dccd7e6c1fb317f2674eaf1/USER 6218
/SingleElectron/Run2012D-PromptReco-v1/AOD /SingleElectron/joosep-step1_Data_Feb6-4ad4eefaf926ac722f9a48104acbb5cc/USER 7248
/SingleMu/Run2012A-13Jul2012-v1/AOD /SingleMu/joosep-step1_Data_Feb6-2cdd420c4c725097a4330835f90d1ada/USER 808
/SingleMu/Run2012A-recover-06Aug2012-v1/AOD /SingleMu/joosep-step1_Data_Feb6-2cdd420c4c725097a4330835f90d1ada/USER 82
/SingleMu/Run2012B-13Jul2012-v1/AOD /SingleMu/joosep-step1_Data_Feb6-2cdd420c4c725097a4330835f90d1ada/USER 4429
/SingleMu/Run2012C-24Aug2012-v1/AOD /SingleMu/joosep-step1_Data_Feb6-14d3879a0dccd7e6c1fb317f2674eaf1/USER 495
/SingleMu/Run2012C-PromptReco-v2/AOD /SingleMu/joosep-step1_Data_Feb6-14d3879a0dccd7e6c1fb317f2674eaf1/USER 6387
/SingleMu/Run2012D-PromptReco-v1/AOD /SingleMu/joosep-step1_Data_Feb6-4ad4eefaf926ac722f9a48104acbb5cc/USER 7274

/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 30459503
/GJets_HT-200To400_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /GJets_HT-200To400_8TeV-madgraph/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 10494617
/GJets_HT-400ToInf_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /GJets_HT-400ToInf_8TeV-madgraph/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 1611963
/QCD_Pt_20_30_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_20_30_BCtoE_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 1740229
/QCD_Pt_30_80_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_30_80_BCtoE_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 2048152
/QCD_Pt_80_170_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_80_170_BCtoE_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 1945525
/QCD_Pt_170_250_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_170_250_BCtoE_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 1948112
/QCD_Pt_250_350_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_250_350_BCtoE_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 2026521
/QCD_Pt_350_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM /QCD_Pt_350_BCtoE_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 1948532
/QCD_Pt_20_30_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_20_30_EMEnriched_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 35040695
/QCD_Pt_30_80_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_30_80_EMEnriched_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 33088888
/QCD_Pt_80_170_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_80_170_EMEnriched_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 34542763
/QCD_Pt_250_350_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_250_350_EMEnriched_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 34601322
/QCD_Pt_350_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_350_EMEnriched_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 34080562
/QCD_Pt_20_MuEnrichedPt_15_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /QCD_Pt_20_MuEnrichedPt_15_TuneZ2star_8TeV_pythia6/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 7529312
/Tbar_s-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /Tbar_s-channel_TuneZ2star_8TeV-powheg-tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 139974
/TBarToLeptons_t-channel_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /TBarToLeptons_t-channel_8TeV-powheg-tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 1711403
/Tbar_t-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /Tbar_t-channel_TuneZ2star_8TeV-powheg-tauola/joosep-step1_MC_Feb6-e6b78fe04780b6676ee83481993719dd/USER 1935072
/Tbar_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /Tbar_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 493460
/T_s-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /T_s-channel_TuneZ2star_8TeV-powheg-tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 259961
/TTJets_FullLeptMGDecays_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /TTJets_FullLeptMGDecays_8TeV-madgraph/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 4246444
/TTJets_FullLeptMGDecays_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM /TTJets_FullLeptMGDecays_8TeV-madgraph/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 12119013
/TTJets_SemiLeptMGDecays_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /TTJets_SemiLeptMGDecays_8TeV-madgraph/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 11229902
/TTJets_SemiLeptMGDecays_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A_ext-v1/AODSIM /TTJets_SemiLeptMGDecays_8TeV-madgraph/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 25424818
/TTJets_MassiveBinDECAY_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /TTJets_MassiveBinDECAY_TuneZ2star_8TeV-madgraph-tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 6923750
/T_t-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /T_t-channel_TuneZ2star_8TeV-powheg-tauola/joosep-step1_MC_Feb6-e6b78fe04780b6676ee83481993719dd/USER 3758227
/T_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /T_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 497658
/WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 18393090
/WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 57709905
/WW_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /WW_TuneZ2star_8TeV_pythia6_tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 10000431
/WZ_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /WZ_TuneZ2star_8TeV_pythia6_tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 10000283
/ZZ_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM /ZZ_TuneZ2star_8TeV_pythia6_tauola/joosep-step1_MC_Feb6-243fe90abe1b1cf7bc2119dc7c0b2e28/USER 9799908

Synchronization to 2012 / CMSSW_5_3_4

Analysis steps are the same as described in https://twiki.cern.ch/twiki/bin/view/CMS/TWikiTopRefEventSel#Single_Top_Channels

Tbar_t data file: /store/mc/Summer12_DR53X/T_t-channel_TuneZ2star_8TeV-powheg-tauola/AODSIM/PU_S10_START53_V7A-v1/0000/0077EE51-88DC-E111-88BE-0018F3D09684.root

Muon channel
name processed skim + HLT iso lepton loose muon veto loose electron veto nJets==2 MTW nBTags==1 Remarks
Joosep 10566 3355 626 625 622 244 197 77 Skim, noHLT, TCHP tight, START53_V7A, CMSSW_5_3_4
Joosep 10566 10566 626 625 622 244 197 77 noSkim, noHLT, TCHP tight, START53_V7A, CMSSW_5_3_4
Mario 10566 665 590 589 589 210 167 84 noSkim, HLT (IsoMu24 _eta2p1_v13), Loose PU jet veto, CSV medium, START53_V7F (the recommended tag for analysis), CMSSW_5_3_4
Mario 10566 10566 657 656 656 236 190 94 noSkim, noHLT, rest is the same
Joosep 10566 665 589 588 586 227 182 72 HLT (IsoMu24 _eta2p1_v13), loose PU jet veto, TCHP tight, START53_V7F, CMSSW_5_3_4, rho corr rel iso (muons)
Mario 10566 665 590 589 589 211 168 83 HLT, loose PU veto, CSVM b-tag, MC smearing, START53_V7F, CMSSW_5_3_4, rho corr rel iso

Code

Naples ntuplizer

  • Naples code can be found here
  • Instructions here
CMSSW version: in the first stage, let's stick to 4_2_8 in order to reproduce Naples results. We will have to move to later releases (5_2_X) for the analysis of 2012 data. If we decide to perform the 7 TeV analysis with the full 2011 data set, moving to 4_4_4 is recommended (or to 5_2_X if a re-reco of the 2011 data and MC in this version is ready in time.)

Setting up SingleTop _52X on phys.hep.kbfi.ee

First export the SCRAM_ARCH as

export SCRAM_ARCH=slc5_amd64_gcc462

Now follow the instructions, but instead of CMSSW_5_2_5 use CMSSW_5_2_5_patch1. The datafiles mentioned in the instructions are copied to /hdfs/local/stpol/sync_5_2_X

Producing the trees using trees_wrapper_cfg.py

In order to do step 2 to produce the trees from the ntuples, the script UserCode /STPol/util_scripts/trees_wrapper_cfg.py can be used. Place the script in the CMSSW_4_2_8/src/TopQuarkAnalysis/SingleTop/test directory.

cd CMSSW_4_2_8/src
cvs co UserCode/STPol
cp UserCode/STPol/util_scripts/trees_wrapper_cfg.py TopQuarkAnalysis/SingleTop/test/
cd TopQuarkAnalysis/SingleTop/test/

Also copy the latest version of the file TChannel_cfg.py from the directory TopQuarkAnalysis/SingleTop/test/synch/

cp synch/TChannel_cfg.py ./

Now run the treemaker as

cmsRun trees_wrapper_cfg.py inputFiles_load=infiles.txt outputFile=out.root maxEvents=-1 channel=CHAN

CHAN is taken from the file SingleTopPSetsSummer _cfi.py and removing the Ele/Mu suffix. So when running on the TChannel ntuples, channel=TChannel.

Producing the W-split samples

In order to produce the W-split samples, the input dataset must be the one corresponding to WJets and the channel must be one of

channel=WJets_wlight, channel=WJets_wbb, channel=WJets_wcc

Producing trees from data

To process data, the following changes have to be made in TChannel_cfg:

process.TreesMu.doResol = cms.untracked.bool(False)
process.TreesEle.doResol = cms.untracked.bool(False)
process.TreesMu.doPU = cms.untracked.bool(False)
process.TreesEle.doPU = cms.untracked.bool(False)
MC_instruction = False

channel_instruction = "mu"

for muons or

channel_instruction = "ele"

for electrons

process.WeightProducer +

needs to be commented out from the

channel_instruction

Troubleshooting the naples code on phys for CMSSW_4_2_8

A working tagset seems to be

--- Tag ---    -------- Package --------                        
V03-03-07      DataFormats/METReco                              
V06-04-19-01   DataFormats/PatCandidates                        
V02-03-00      JetMETCorrections/Algorithms                     
V05-00-17-01   JetMETCorrections/Modules                        
V03-01-00      JetMETCorrections/Objects                        
V04-05-07      JetMETCorrections/Type1MET                       
CMSSW_4_2_8    PhysicsTools/PatAlgos                            
V00-05-24      PhysicsTools/PatExamples                         
b4_2_X_cvMEtCorr_30Nov11 PhysicsTools/PatUtils                            
V00-03-24      PhysicsTools/SelectorUtils                       
V08-02-14      PhysicsTools/UtilAlgos                           
V08-03-10      PhysicsTools/Utilities                           
V00-04-11      RecoBTag/PerformanceDB                           
V00-03-31      RecoEgamma/ElectronIdentification                
V03-03-05      RecoLuminosity/LumiDB                            
SingleTop_42X  TopQuarkAnalysis/SingleTop

Error occurred while creating for module of type 'SingleTopLeptonCounter' with label 'countLeptons'
StatusMismatch: Parameter 'minNumberTight' is designated as untracked in the code,
but is not designated as untracked in the configuration file.
Please change the configuration file to 'untracked <type> minNumberTight'.

Change the following things in the source files from untracked to tracked

src/SingleTopLeptonCounter.cc

  minTight_ =  iConfig.getParameter<int>("minNumberTight");
  maxTight_ =  iConfig.getParameter<int>("maxNumberTight");
  minLoose_ =  iConfig.getParameter<int>("minNumberLoose");
  maxLoose_ =  iConfig.getParameter<int>("maxNumberLoose");

python/SingleTopSelectors_cff.py

countLeptons = cms.EDFilter("SingleTopLeptonCounter",
                            looseMuons = cms.InputTag("looseMuons"),
                            looseElectrons = cms.InputTag("looseElectrons"),
                            tightMuons = cms.InputTag("tightMuons"),
                            tightElectrons = cms.InputTag("tightElectrons"),
                            qcdMuons = cms.InputTag("tightMuonsZeroIso"),
                            qcdElectrons = cms.InputTag("tightElectronsZeroIso"),

                            minNumberTight = cms.int32(1),
                            maxNumberTight = cms.int32(1),
                            minNumberLoose = cms.int32(0),
                            maxNumberLoose = cms.int32(0),

                            minNumberQCD = cms.untracked.int32(1),
                            maxNumberQCD = cms.untracked.int32(1),
                            rejectOverlap = cms.untracked.bool(True),
                            doQCD = cms.untracked.bool(True),
                            )

SelectionCuts_Skim_cff.py

minTightLeptons = cms.int32(1)
maxTightLeptons = cms.int32(99)
minLooseLeptons = cms.int32(0)
maxLooseLeptons = cms.int32(99)

Error occurred while creating for module of type 'SingleTopSystematicsTreesDumper' with label 'TreesMu'
Error occurred while creating for module of type 'SingleTopSystematicsTreesDumper' with label 'TreesMu'
---- JetCorrectorParameters BEGIN
No definitions found!!!
---- JetCorrectorParameters END

You need to copy the file from CMSSW_4_2_8/src/TopQuarkAnalysis/SingleTop/test/JEC11_V12_AK5PF_UncertaintySources.txt to CMSSW_4_2_8/src/TopQuarkAnalysis/SingleTop/test/synch

terminate called after throwing an instance of 'boost::exception_detail::clone_impl >'

You need to set the LHAPATH environment variable

export LHAPATH=/cvmfs/cms.cern.ch/slc5_amd64_gcc434/external/lhapdf/5.8.5-cms3/share/lhapdf/PDFsets

python encountered the error: Path 'pathPreselection' contains a module of type 'FastjetJetProducer' which has no assigned label.

Comment the following in SingleTopMC_PF2PAT_cfg.py

process.load("PhysicsTools.PatUtils.patPFMETCorrections_cff")
process.selectedPatJetsForMETtype1p2Corr.src = cms.InputTag('selectedPatJets')
process.selectedPatJetsForMETtype2Corr.src = cms.InputTag('selectedPatJets')
process.patPFJetMETtype1p2Corr.type1JetPtThreshold = cms.double(10.0)
process.patPFJetMETtype1p2Corr.skipEM = cms.bool(False)
process.patPFJetMETtype1p2Corr.skipMuons = cms.bool(False)

and remove producePatPFMETCorrections from the path

process.pathPreselection = cms.Path(
        process.patseq #+  process.producePatPFMETCorrections
        )

crab weirdness introducing a lumi discrepancy

Somehow, the results from crab -report and lumiCalc2.py are inconsisent. Diff between 83a02e9_Jul22 (Mario - old) and Aug4_c6a4b11(Joosep - new). The former was used for the previous presentation at the single top meeting, and for the plots in the AN/PAS. The latter includes MET-PHI corrections, PU reweighting systematics, top/ttbar reweighting by pt.

data block A
label subpath parent int. lumi (/pb)
old not available, added by lumisection diffs  
new ./Aug1/WD_SingleMu_miss /SingleMu/joosep-missing_data-8c29f3a4ed8afc34a59f7c305acd4b13/USER 1094

data block B
labelSorted ascending subpath parent int. lumi (/pb)
new WD_SingleMu2 /SingleMu/joosep-Jul8_51f69b-7cb0fdcb434651e6fe30ffadc793c329/USER 6398
old ./Jul15/WD_SingleMu2 /SingleMu/joosep-Jul8_51f69b-7cb0fdcb434651e6fe30ffadc793c329/USER 4918

data block C
label subpath parent int. lumi (/pb)
old ./Jul15/WD_SingleMu1 /SingleMu/joosep-Jul16_7d17c5-7cb0fdcb434651e6fe30ffadc793c329/USER 6823
new WD_SingleMu1 /SingleMu/joosep-Jul16_7d17c5-7cb0fdcb434651e6fe30ffadc793c329/USER 6784

data block D
label subpath parent int. lumi (/pb)
old WD_SingleMu3 /SingleMu/jpata-Jul16_7d17c5-7cb0fdcb434651e6fe30ffadc793c329/USER 5277
new ./Jul15/WD_SingleMu3 /SingleMu/jpata-Jul16_7d17c5-7cb0fdcb434651e6fe30ffadc793c329/USER 5319

Differences between WD_SingleMu2

new

CMSSW.datasetpath : /SingleMu/joosep-Jul8_51f69b-7cb0fdcb434651e6fe30ffadc793c329/USER
CMSSW.dbs_url : https://cmsdbsprod.cern.ch:8443/cms_dbs_ph_analysis_02_writer/servlet/DBSServlet
CMSSW.get_edm_output : 1
CMSSW.lumi_mask : /home/joosep/singletop/stpol/crabs/lumis/Cert_190456-208686_8TeV_22Jan2013ReReco_Collisions12_JSON.txt
CMSSW.lumis_per_job : 100 
2013-08-04 02:23:54,216 [INFO]  528 jobs created to run on 67196 lumis
/home/joosep/singletop/stpol/crabs/Aug4_c6a4b11/step2/data/iso/Jul15/WD_SingleMu2
Total Events read: 42747328
Total Files read: 1133
Total Jobs : 528
Luminosity section summary file: /home/joosep/singletop/stpol/crabs/Aug4_c6a4b11/step2/data/iso/Jul15/WD_SingleMu2/res/lumiSummary.json
   # Jobs: Done:1
   # Jobs: Retrieved:527

old

CMSSW.datasetpath : /SingleMu/joosep-Jul8_51f69b-7cb0fdcb434651e6fe30ffadc793c329/USER
CMSSW.dbs_url : https://cmsdbsprod.cern.ch:8443/cms_dbs_ph_analysis_02_writer/servlet/DBSServlet
CMSSW.get_edm_output : 1
CMSSW.lumi_mask : /home/mario/Summer13/stpol/crabs/lumis/Cert_190456-208686_8TeV_22Jan2013ReReco_Collisions12_JSON.txt
CMSSW.lumis_per_job : 100
2013-07-22 17:13:32,755 [INFO]  520 jobs created to run on 66059 lumis
/home/mario/Summer13/stpol/crabs/83a02e9_Jul22/step2/data/iso/Jul15/WD_SingleMu2
Total Events read: 55737606
Total Files read: 1480
Total Jobs : 520
Luminosity section summary file: /home/mario/Summer13/stpol/crabs/83a02e9_Jul22/step2/data/iso/Jul15/WD_SingleMu2/res/lumiSummary.json
   # Jobs: Done:3
   # Jobs: Retrieved:517

So somehow, the number of lumis is the same, but the number of events read is different, and thus is the final luminosity! How can that be?

crab -report

lumiCalc2.py -i lumiSummary.json overview

Tallinn analysis code 1 for CMSSW_5_3_X

Access is via github: https://github.com/HEP-KBFI/stpol. Instructions are located on github as well.

Analysis macros and other shared material

Our own private macros must be committed in UserCode/STPol. At the moment this directory is empty, but it will be useful to share macros, scripts, etc.

To check out code from our directory: cvs co UserCode/STPol; this creates a directory UserCode/STPol inside the directory where you are located.

Plenty of instructions to use cvs are available on the web, but here follow the few essential ones:

To commit a file or a directory:

cvs add [yourfile]
cvs commit -m 'brief description' [yourfile]

The cvs add command is only needed when the file is new on cvs.

If you are already working on an old version of this directory and you know there are updates, type cvs update.

See also this how to

(We will want to use "tags" at some point, but let's start with the basics...)

GRID utilities

The users and passwords have been distributed to everyone. The server name is phys.hep.kbfi.ee. To get access to Grid and CMSSW tools you should add this to your .bash_profile file to be included at every login:

export SCRAM_ARCH=slc5_amd64_gcc434
export LCG_GFAL_INFOSYS=bdii.balticgrid.org:2170

source /opt/software/cms/cmsset_default.sh
export CVSROOT=:ext:mario@cmscvs.cern.ch:/cvs_server/repositories/CMSSW

replacing mario with your CERN username in the CVSROOT environment. To use CRAB you first do cmsenv in some CMSSW software area and then you can source it:

source /opt/software/CRAB_2_7_8/crab.sh

This version of CRAB doesn't have the 500 job limitation if you want to submit without a CRAB server. However over 2500 jobs might be problematic as job ID lists will exceed command line limits etc that are way harder to debug out of CRAB. It's possible, but then we should coordinate as one needs to modify some parts of CRAB temporarily.

For local storage access (there is no CASTOR access from Tallinn) you have /hdfs/ mounted that is the whole storage. You can access anything that's already transferred to Estonia under /hdfs/cms/store/... including your stageout directory that is for example /hdfs/cms/store/user/mario/... The storage is Hadoop meaning that files that are in there can be either written from scratch or read. You cannot open files in read/write mode.

You can also use VNC on phys, but we recommend using a client that enables ssh tunneling as the default VNC protocol sends cleartext passwords. On Mac the best and fastest possible VNC (that actually allows live working on remote machine with close to 0 lag if the network is decent) is Jolly's Fast VNC. It's not free, but it costs only a few USD on Mac App Store and is well worth the money due to the speed increase as well as all the ssh tunneling etc features. For other OS's you'll have to figure it out on your own smile

GRID with remoteGlidein

Get a proper clean environment, then initialize crab:

source /opt/software/CRAB_2_8_3/crab.sh

In crab.cfg you must have

[CRAB]
scheduler = remoteGlidein
use_server = 0

[GRID]
se_white_list = kbfi

GRID with local submission from *.hep.kbfi.ee

You need to use a modified version of CRAB:

source /opt/software/CRAB2/crab.sh

Also, the following modifications are necessary in crab.cfg

[CRAB]
jobtype = cmssw
scheduler = pbsv2withsrm
use_server = 0

[PBSV2WITHSRM]
forceTransferFiles = 1
workernodebase = /home/USERNAME
use_proxy = 1

You can check whether the jobs are running using qstat.

Datasets

An essential tool for finding out the datasets you need is the DAS webpage or the corresponding command-line instructions. See the FAQs
You can also use DBS queries. Example:

dbs --search --query='find file where dataset like /T_TuneZ2_t-channel_7TeV-powheg-tauola/Summer11-PU_S4_START42_V11-v1/AODSIM'

this lists the names of all the files corresponding to that dataset. Type dbs --help to know more. See also these instructions.

Accessing the desired run range in real data requires the use of JSON files. Their use is explained here (and links within). The repository of officially validated JSON files is here.

Checking for local datasets in Tallinn using the DAS CLI

das_cli.py --query="dataset site=T2_EE_Estonia" --limit=0 | grep "/Tbar_TuneZ2_s-channel_7TeV-powheg-tauola"

or to find the Summer11+START42 datasets

das_cli.py --query="dataset dataset=/T_TuneZ2_s-channel_7TeV-powheg-tauola/Summer11*START42*AODSIM" --limit=0

Checking the sites of a dataset

das_cli.py --query="site dataset=/T_TuneZ2_s-channel_7TeV-powheg-tauola/Summer11-PU_S4_START42_V11-v1/AODSIM" --limit=0

Getting the list of files for a (local) dataset that has been stored on the instance cms_dbs_ph_analysis_02

das_cli.py --query="file dataset=/SingleMu/atiko-SingleTopPol-Summer11-v42_OldScript_data-75dcb0b28b0100c77354e3c05053de97/USER instance=cms_dbs_ph_analysis_02" --limit=0

8 TeV analysis:

5_3 datasets:

/T_t-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/T_t-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM
/Tbar_t-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/T_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/Tbar_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/T_s-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/Tbar_s-channel_TuneZ2star_8TeV-powheg-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM

/TTJets_MassiveBinDECAY_TuneZ2star_8TeV-madgraph-tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM
/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM

/WW_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/WZ_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/ZZ_TuneZ2star_8TeV_pythia6_tauola/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM

/QCD_Pt_20_MuEnrichedPt_15_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM

/QCD_Pt_20_30_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_30_80_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_80_170_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_170_250_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_250_350_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_350_BCtoE_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v2/AODSIM

/QCD_Pt_20_30_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_30_80_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_80_170_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_170_250_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_250_350_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/QCD_Pt_350_EMEnriched_TuneZ2star_8TeV_pythia6/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM

/GJets_HT-200To400_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM
/GJets_HT-400ToInf_8TeV-madgraph/Summer12_DR53X-PU_S10_START53_V7A-v1/AODSIM

/SingleMu/Run2012A-13Jul2012-v1/AOD
/SingleMu/Run2012B-13Jul2012-v1/AOD
/SingleMu/Run2012C-PromptReco-v1/AOD
/SingleMu/Run2012C-PromptReco-v2/AOD

/SingleElectron/Run2012A-recover-06Aug2012-v1/AOD 190782 - 190949

/SingleElectron/Run2012A-13Jul2012-v1/AOD 190456 - 193621
/SingleElectron/Run2012B-13Jul2012-v1/AOD 193834 - 196531
/SingleElectron/Run2012C-24Aug2012-v1/AOD 198022 - 198523
/SingleElectron/Run2012C-PromptReco-v1/AOD 197770 - 198913
/SingleElectron/Run2012C-PromptReco-v2/AOD 198934 - 202998

The 24th Aug rereco is only a subrange of 2012C v1 so probably a recovery of something. The recover-06Aug2012 seems to be the 2012A ECAL corruption recovery (looking at run ranges). So we need to use them all and just make sure the overlaps are removed. The 13 Jul, 6th aug and 24th aug rerecos have their separate JSON's that should be handled accordingly and the prompt recos need to use the golden JSON and remove the rereco sections.

FastSim 8TeV samples

Some missing Datasets were produced by Dmitri using FastSim. The results are collected in the following table. SInce the RECO filter was applied, the effective number of generated events necessary for correct normalization is to be determined. The correct CMSSW.dbs_url to use in crab.cfg is

CMSSW.dbs_url= https://cmsdbsprod.cern.ch:8443/cms_dbs_ph_analysis_02_writer/servlet/DBSServlet

name dataset effective # of gen. events ntuple merged tuple
t-channel /T_t-channel_TuneZ2star_8TeV-powheg-tauola_CAF_EDM/dkonst-T_t-channel_TuneZ2star_8TeV-powheg-tauola-AOD-FASTSIM_5_2_6_filter-f4dff057d52a2128cc15dd525ba19b60/USER 0.087238665 /T_t-channel_TuneZ2star_8TeV-powheg-tauola_CAF_EDM/jpata-TChannel_ntuples_v2-c7fb5b868024440b562f1d714504aa0d/USER srm://ganymede.hep.kbfi.ee:8888/srm/v2/server?SFN=/hdfs/local/stpol/joosep/ntuples/FastSim/ntuples_FastSim_T_t.root
WJets1 /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_EDM_1/dkonst-WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_AOD-FASTSIM_5_2_6_filter_1-fdf9c3be443855829751ee3dedf96c91/USER ??? /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_EDM_1/jpata-ntuples_v1_WJets1-c7fb5b868024440b562f1d714504aa0d/USER srm://ganymede.hep.kbfi.ee:8888/srm/v2/server?SFN=/hdfs/local/stpol/joosep/ntuples/FastSim/ntuples_FastSim_WJets1.root
WJets2 /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_EDM_2/dkonst-WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_AOD-FASTSIM_5_2_6_filter_2-fdf9c3be443855829751ee3dedf96c91/USER ??? /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_EDM_2/jpata-ntuples_v1_WJets2-c7fb5b868024440b562f1d714504aa0d/USER srm://ganymede.hep.kbfi.ee:8888/srm/v2/server?SFN=/hdfs/local/stpol/joosep/ntuples/FastSim/ntuples_FastSim_WJets2.root
WJets3 /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_EDM_3/dkonst-WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_AOD-FASTSIM_5_2_6_filter_1-fdf9c3be443855829751ee3dedf96c91/USER ??? /WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball_EDM_3/jpata-ntuples_v1_WJets3-c7fb5b868024440b562f1d714504aa0d/USER srm://ganymede.hep.kbfi.ee:8888/srm/v2/server?SFN=/hdfs/local/stpol/joosep/ntuples/FastSim/ntuples_FastSim_WJets3.root

Systematic samples with 7 to 8 TeV PDF reweighing

Since MC samples for 8 TeV for some systematics were not available, the TopMonteCarloReweighting tool was used to reweight Fall11 7 TeV samples using CMSSW_4_2 and the corresponding SingleTop _42X code.

name 7 TeV dataset reweighted dataset (on cms_dbs_ph_analysis_02) merged tuple (on T2_EE_Estonia)
T_t default /T_TuneZ2_t-channel_7TeV-powheg-tauola/Fall11-PU_S6_START42_V14B-v1/AODSIM ??? srm://ganymede.hep.kbfi.ee:8888/srm/v2/server?SFN=/hdfs/local/stpol/joosep/ntuples/PDFreweight/ntuples_T_t_default.root
T_t scaleup /T_TuneZ2_scaleup_t-channel_7TeV-powheg-tauola/Fall11-PU_S6_START42_V14B-v1/AODSIM /T_TuneZ2_scaleup_t-channel_7TeV-powheg-tauola/jpata-systematics_reweight_7to8TeV_v3_T_t_scaleup-c75044d3a7593caf1221e3b610b44154/USER srm://ganymede.hep.kbfi.ee:8888/srm/v2/server?SFN=/hdfs/local/stpol/joosep/ntuples/PDFreweight/ntuples_T_t_scaleup.root
T_t scaledown /T_TuneZ2_scaledown_t-channel_7TeV-powheg-tauola/Fall11-PU_S6_START42_V14B-v1/AODSIM /T_TuneZ2_scaledown_t-channel_7TeV-powheg-tauola/jpata-systematics_reweight_7to8TeV_v3_T_t_scaledown-c75044d3a7593caf1221e3b610b44154/USER srm://ganymede.hep.kbfi.ee:8888/srm/v2/server?SFN=/hdfs/local/stpol/joosep/ntuples/PDFreweight/ntuples_T_t_scaledown.root
Tbar_t default /Tbar_TuneZ2_t-channel_7TeV-powheg-tauola/Fall11-PU_S6_START42_V14B-v1/AODSIM ??? ???
Tbar_t scaleup /Tbar_TuneZ2_scaledown_t-channel_7TeV-powheg-tauola/Fall11-PU_S6_START42_V14B-v1/AODSIM ??? ???
Tbar_t scaledown /Tbar_TuneZ2_scaledown_t-channel_7TeV-powheg-tauola/Fall11-PU_S6_START42_V14B-v1/AODSIM ??? ???
TTJets default /TTJets_TuneZ2_7TeV-madgraph-tauola/Fall11-PU_S6_START42_V14B-v2/AODSIM ??? ???
TTJets matchingup /TTjets_TuneZ2_matchingup_7TeV-madgraph-tauola/Fall11-PU_S6_START42_V14B-v2/AODSIM /TTjets_TuneZ2_matchingup_7TeV-madgraph-tauola/jpata-systematics_reweight_7to8TeV_v3_TTJets_matchingup-c75044d3a7593caf1221e3b610b44154/USER ???
TTJets matchingdown /TTjets_TuneZ2_matchingdown_7TeV-madgraph-tauola/Fall11-PU_S6_START42_V14B-v2/AODSIM /TTjets_TuneZ2_matchingdown_7TeV-madgraph-tauola/jpata-systematics_reweight_7to8TeV_v3_TTJets_matchingdown-c75044d3a7593caf1221e3b610b44154/USER srm://ganymede.hep.kbfi.ee:8888/srm/v2/server?SFN=/hdfs/local/stpol/joosep/ntuples/PDFreweight/ntuples_TTJets_matchingdown.root
TTJets scaleup /TTjets_TuneZ2_scaleup_7TeV-madgraph-tauola/Fall11-PU_S6_START42_V14B-v1/AODSIM /TTjets_TuneZ2_scaleup_7TeV-madgraph-tauola/jpata-systematics_reweight_7to8TeV_v3_TTJets_scaleup-c75044d3a7593caf1221e3b610b44154/USER ???
TTJets scaledown /TTjets_TuneZ2_scaledown_7TeV-madgraph-tauola/Fall11-PU_S6_START42_V14B-v2/AODSIM /TTjets_TuneZ2_scaledown_7TeV-madgraph-tauola/jpata-systematics_reweight_7to8TeV_v3_TTJets_scaledown-c75044d3a7593caf1221e3b610b44154/USER ???

Orso's EDM-ntuples for 8 TeV

Due to their size the latest tuples are on the Naples storage element which can be accessed as follows.

voms-proxy-init -voms cms
lcg-ls -b -D srmv2 -T srmv2 "srm://cmsse02.na.infn.it:8446/srm/managerv2?SFN=/dpm/na.infn.it/home/cms/store/user/oiorio/2012/Summer12/MergedJul24/"
lcg-cp -b -D srmv2 -T srmv2 "srm://cmsse02.na.infn.it:8446/srm/managerv2?SFN=/dpm/na.infn.it/home/cms/store/user/oiorio/2012/Summer12/MergedJul24/remote_file.root" /path/to/local/file.root

7 TeV analysis

As written above, at least in a first stage we want to use 7 TeV data and MC to make sure that we are synchronized with the cross section analysis of TOP-11-021.
Therefore, data and MC samples must be the same as listed in slides 5 and 75 of the TOP-11-021 approval talk (in principle also in tables 1 and 2 of AN-2011-229).
This means that CMSSW_4_2_8 must be used, and only the first 1.14/fb in the muon channel and 1.51/fb in the electron channel will be analyzed. This corresponds to the following JSON files:

  • Cert_160404-163869_7TeV_May10ReReco_Collisions11_JSON_v3.txt
  • Cert_160404-180252_7TeV_PromptReco_Collisions11_JSON.txt
  • Cert_170249-172619_7TeV_ReReco5Aug_Collisions11_JSON_v3.txt
The complete dataset names for the MC samples in Table 2 are obtained by adding /Summer11-PU_S4_START42_V11-v1/AODSIM (e.g., /T_TuneZ2_t-channel_7TeV-powheg-tauola/Summer11-PU_S4_START42_V11-v1/AODSIM) Is this true? 42_V11 no longer exists in Tallinn, instead there is 42_V14B.

The MC datasets from the analysis present in Tallinn (under the conditions of tag=START42 and either Fall11 or Summer11) are

/T_TuneZ2_t-channel_7TeV-powheg-tauola
/Tbar_TuneZ2_t-channel_7TeV-powheg-tauola
/T_TuneZ2_s-channel_7TeV-powheg-tauola -> /T_TuneZ2_s-channel_7TeV-powheg-tauola/Fall11-PU_S6_START42_V14B-v1/AODSIM
/Tbar_TuneZ2_s-channel_7TeV-powheg-tauola
/T_TuneZ2_tW-channel-DR_7TeV-powheg-tauola
/Tbar_TuneZ2_tW-channel-DR_7TeV-powheg-tauola
/TTJets_TuneZ2_7TeV-madgraph-tauola
/WJetsToLNu_TuneZ2_7TeV-madgraph-tauola
/DYJetsToLL_TuneZ2_M-50_7TeV-madgraph-tauola
/QCD_Pt-20_MuEnrichedPt-15_TuneZ2_7TeV-pythia6
/QCD_Pt-80to170_EMEnriched_TuneZ2_7TeV-pythia7

And the ones missing are:

/WW_TuneZ2_7TeV_pythia6_tauola
/WZ_TuneZ2_7TeV_pythia6_tauola
/ZZ_TuneZ2_7TeV_pythia6_tauola
/QCD_Pt-20to30_BCtoE_TuneZ2_7TeV-pythia7
/QCD_Pt-30to80_BCtoE_TuneZ2_7TeV-pythia6
/QCD_Pt-80to170_BCtoE_TuneZ2_7TeV-pythia6
/QCD_Pt-20to30_EMEnriched_TuneZ3_7TeV-pythia6
/QCD_Pt-30to80_EMEnriched_TuneZ2_7TeV-pythia6
/GJets_TuneD6T_HT-40To100_7TeV-madgraph
/GJets_TuneD6T_HT-100To200_7TeV-madgraph
/GJets_TuneD7T_HT-200_7TeV-madgraph

All the MC datasets processed with

 SingleTopMC_PF2PAT_cfg.py 

are available here and data here.

FCNC samples:

  • t,j -> b,l,nu,j with tug coupling.(MCDB 3655)
/TJetToBLNuJet_FCNC_tug_TuneZ2_7TeV-comphep-EDM/dkonst-TJetToBLNuJet_FCNC_tug_TuneZ2_7TeV-comphep-FASTSIM-92a8e0ecc98e6ae221fc036cdde0c771/USER
dbs_url= https://cmsdbsprod.cern.ch:8443/cms_dbs_ph_analysis_02_writer/servlet/DBSServlet

  • t,j -> b,l,nu,j with tcg coupling.(MCDB 3655) 1 job is still running.

  • t,j -> b,l,nu,j with tug and tcg (MCDB 3654) are still running
FCNC datasets after step one are here

Unfolding

Documentation about the KIT-style unfolding, as used in the ttbar A_C analysis (courtesy by Jeannine and collaborators):

TSVDUnfolding:

RooUnfold:

Statistics Committee interim note on unfolding:

MET-phi modulation studies

Private productions with Fast Simulation

Eventually, we will request official samples of non-SM signals from interesting models to be produced with Full Simulation. But before requesting an official production we need to validate the generation parameters, and anyway they will take time before being ready.
Ad interim, then, we should use FastSim for private productions.

In this section we will list and describe several configuration files (to be stored somewhere in our UserCode /STPol directory).

It is useful to use the cmsDriver script to create standard configuration files.
To be coherent with 4_2_X samples from the "Summer11" production, the following string must be used (in 4_2_8):

cmsDriver.py GEN-fragment --step GEN,FASTSIM,HLT:GRun --beamspot Realistic7TeV2011Collision --conditions START42_V11::All --pileup FlatDist10_2011EarlyData_50ns --geometry DB --datamix NODATAMIXER --eventcontent AODSIM --datatier AODSIM

Documentation

The URL of the svn web browser for our documents is
https://svnweb.cern.ch/cern/wsvn/tdr2/?. Your AN is under notes.

Instructions for retrieving the template version and building it are now
available on the wiki at
https://twiki.cern.ch/twiki/bin/view/CMS/Internal/TdrProcessing There are
additional hints in the template document itself, which is available
formatted as
https://svnweb.cern.ch/cern/wsvn/tdr2/papers/XXX-08-000/trunk/XXX-08-000_temp.pdf 
Please note the use of our standard definitions for particle names
and commonly used HEP terms as shown in the appendices. BibTeX hints are in
both the tex and bib files. A more thorough treatment of many CMS document
production tasks may be found at
https://svnweb.cern.ch/cern/wsvn/tdr2/utils/branches/dev/general/notes_for_authors.pdf
 (for the development version). The general CMS style guide is
currently located at
https://twiki.cern.ch/twiki/bin/view/CMS/Internal/PubGuidelines, and the
publications wiki page is
https://twiki.cern.ch/twiki/bin/viewauth/CMS/Internal/Publications

Analysis Note 2012/448

> svn co -N svn+ssh://svn.cern.ch/reps/tdr2 myDir # where myDir is a placeholder for a name of your choice
> cd myDir
> svn update utils
> svn update -N notes
> svn update notes/AN-12-448
> eval `./notes/tdr runtime -csh` # for tcsh. use -sh for bash.
> cd notes/AN-12-448/trunk
# (edit the template, then to build the document)
> tdr --style=an b AN-12-448

You can commit your changes with
> svn commit -m "commit message"
New files will first need to be added with
> svn add NewFileNames
before they can be committed.

Note: I committed a script MAKENOTE for compiling without having to remember the exact command line.

PAS TOP-13-001

> svn co -N svn+ssh://svn.cern.ch/reps/tdr2 myDir # where myDir is a placeholder for a name of your choice
> cd myDir
> svn update utils
> svn update -N notes
> svn update notes/TOP-13-001
> eval `./notes/tdr runtime -csh` # for tcsh. use -sh for bash.
> cd notes/TOP-13-001/trunk
# (edit the template, then to build the document)
> tdr --style=pas b TOP-13-001

You can commit your changes with
> svn commit -m "commit message"
New files will first need to be added with
> svn add NewFileNames
before they can be committed.

Note: I committed a script MAKEPAS for compiling without having to remember the exact command line.

I also committed a couple of shell scripts (.sh) to compare some files that are supposed to be the same in AN and PAS, and to copy from AN to PAS.

Wiki of answers to reviewers

PasTop13001QA

PaperTop13001QA

To-do-list towards the final paper

  • Why so much QCD in muon channel? [Joosep]
  • Check if more statistics can be produced for the MC-limited systematic samples, especially for Wjets and Zjets
  • Move from TCHP to CSV at step 2 [Joosep]
  • BDT anti-QCD [Morten]
    • QCD estimation based on fit to its output [Andres]
  • Specialized anti-Wjets and anti-ttbar BDTs [Mario?, Morten?]
    • 2D fit in the plane of their two outputs [Steffen]
    • or, in alternative, train super-BDT using as input the outputs of the specialized BDTs (including the anti-QCD one?)
  • Find a solid way to choose the optimal cut (not necessarily a rectangular cut, in case of the 2D plane)
  • "Real" linearity check with anomalous comphep samples
  • Find optimal binning size [Steffen]
  • Combine muon+electron channels without using BLUE, i.e. immediately after unfolding [Steffen,Thorsten]
  • Verify that TopFit is well behaving, and resurrect anomalous limits [Matthias]
  • Resurrect cut-based cross-check analysis (based on C instead of eta_j'?) [Andres, Steffen]
  • Separate measurements for top and antitop (in addition, not as replacement to the global result.)

From the ARC, Sep.26:

     ---> the difference of event selection between the electron and muon channels are inducing some strong differences between the 2 channels (MT vs MET) for example the tight MET cut on electron induce high sensitivity to some systematics like JER. For publication, we would like suggest to harmonize the selection between the two channels, and possibly using cut on MT for both channels.
     --->  There is some lack of statistics in some systematic samples => These statistical fluctuations seem to affect more the electron channel, as its  selection efficiency is lower. For publication, we would like to suggest to produce more MC events where it is needed (hoping there is enough computing resources).
    ---> while a conservative approach was followed by the authors, we would like to see some more investigation on the mis-modeling of the costheta* distribution by madgraph. For publication, we would like to suggest to work on better understanding of the mis-modeling of the costheta* distribution by, possibly, make details MC studies/comparisons (comparisons with other generators, investigate effects of matching, propagations of spin information etc...). 
    ---> Concerning TopFit, the correlations of measurements in the limit calculation are neglected. This is a feature of the program (analysts have no hand on it). This assumption, which is done also in W-helicity measurement by ATLAS and CMS if I understood perperly,  is made clear in the text. For publication, we would like to see with the authors and Aguilar if correlations can be introduced in a decent amount of time.
    ---> We would also suggest to investigate the reliability of jet-ID up to |eta|
    ---> The usage of a the CSV tagger should help to remove more backgrounds with a possible increase the signal statistic. The determination of the best working point might be needed.
    ---> We understood that the BDT selection would benefit from a re-optimization.
    ---> As discussed (and proposed) by the authors, the QCD background normalization in the second background fit should be fixed to the estimation of the first background fit.
    ---> In the combination of the top polarization, it might help to investigate better the correlations between the systematics.
    ---> Some synchronization with the W helicity in single-top could be investigated.

From Jeremy, Sep.27:

That would be great if you
could at least redo the nice analysis from Nadjieh. In particular,
instead of inverting the isolation cut on electron isolation >0.1, one
could try to investigate how the mTW bias is behaving by bins of
isolation, like   0.1 < iso < X. There might be some intervals with smaller
bias.
Also, the fact that Nadjieh is looking at the 2jets0tag category make
the sample enriched in jet reconstructed as electrons, while there could
be a significant effect of btagging for the fraction of non-prompt
electron from heavy hadron decays. The bias can be smaller in the signal
region.
One could also investigate a combination of a loose MET cut and a
tighter mWT cut, which would have to be optimized.

From Jeannine, August 8, 2014

1) I've only noticed several issues/problems with the QCD modeling:
a) Looking at Figure 27 it makes no sense to have one QCD template and one template for non-QCD processes. There is quite some separation power for DY, EW V production,top. So, I suggest to perform a 4 template fit, giving the SM processes the usual width to float. Please report also the scale factors for the SM process.
b) Looking at Figure 28, inparticular at BDT_antiQCD in the region above the cut value, the contamination from non QCD processes is by far too high. So we basically have no idea how to extrapolate from the cut region as there is certainly a sizable uncertainty on the contamination. How can we trust the QCD estimation in the BDT_antiQCD>cut region given this contamination issue? Furthermore, how can we trust any QCD shape in the region BDT_antiQCD>cut and even worse the correlations between variables as it is needed for the selection BDT? How can we trust BDT_W,tt for QCD?
c) Concerning table 7-10, the number that really matters, is the number of QCD events (plus uncertainty) after applying the BDT_anti-QCD cut. How does the number change when the non-QCD contamination is altered? How does it change when the QCD MC (isolated region) is used?
d) How can we trust the cosTheta* shape of QCD at all? Does it probably peak at -1? How can we exclude that?
Just thinking loud, would it help to use QCD MC (isolated, anti-iso sel) in the 2j0t region with different cuts on BDT_antiQCD (e.g 0...0.6 in steps of 0.1)? Furthermore, could we learn something from ttbar all-hadronic events (jet mimics a lepton), for example by doing the same check as for QCD MC?
The W+jets modeling was already carefuly attacked in the PAS and the new studies will certainly add more knowledge about the W+jets mismodeling, so I have no comments on this right now.
2) One comment on the BDT trainings, figure 5 and 11, for both BDTs it seems that there is overtraining. In case of the BDT_anti-QCD this is true for signal (KS-test < 5%), in case of BDT_W,tt this is true for background (KS test=0). Is it feasible to find a BDT setting that does not overtain?
3) Looking at Figure 9 it seems that the BDT_W,tt output has a small peak in the signal region. That is something what one would like to avoid. Which background (tW, QCD, Q+jets, ttbar) causes this peak?

On fig. 9, only ttbar and W+jets are included in the background. The templates for all subcomponents will be plotted. In general, this "second peak" has been discussed some time ago , the reason seems to be that for some events, the BDT is unable to deduce them from signal and the gradient boosting does not reweight those trees down by a large enough factor. The style (hatching) of Fig. 9 will also be changed.

4) Figure 24 and 25 (BDT,W,tt in the 2j0t and the 3j2t regions) look ok, as the observed deviation is covered by syst. It would be nice to have at least in the appendix the dta-mc comparison for all BDT_W,tt input variables. In principle also the correlation of the most important input variables and towards BDT_W,tt has to be checked, are they the same for data and MC (see suggestion from Andrea: check correlation between MT-BDT).
5) Fitting:
a) The W+jets template is a bit spiky. What subset causes the spikes? Can we safely ignore this part (e.g. Wc+1p) without introducing a kin. bias? The current smoothing studies are a good idea, I think.
b) the single top scale factor for mu is 1.22. How does this compare to the published single top cross section measurement at 8TeV? Is it consistent?

Joosep will plot the subcomponent templates, however, itís just mostly an issue of nominal MC becoming depleted also in W+2,3, for which we have no excellent approach.

6) Correlation of BDT_W,tt and cosTheta*:
Looking at figure 48 and 49 it is clear that a cut on BDT_W,tt results in ttbar and W+jets shapes that look more single top like. I think many variables used in the BDT_W,tt are correlated to cosTheta*, hence the correlation between BDT_W,tt and cosTheta* is even stronger for the BDT output. As long as the correlation between BDT_W,tt and cosTheta* (and better also the correlation of all variables entering the BDT to cosTheta*) is in data the same as predicted this is ok. However, this assumption has to be carefully checked in different control regions. I suggest to extend the MTW-BDT correlation study suggested today by Andrea towards cosTheta* and the BDT_W,tt output and its input variables and also towards different control regions. Furthermore, I suggest to show data-mc plots for cosTheta* in the 2j0t and 3j2t region for different BDT_W,tt cut values (do we always get reasonable data MC agreement?).

Joosep will add additional plots with cut points.

7) Comphep study and neyman construction:
It seems that the difference between Powheg and Comphep SM is for some distributions larger than the difference between the ano coupling samples. How is the Newman construction done? Does it use Comhep SM for the unfolding or Powheg? Is the use of Powheg in the migration matrix the reason why there is a bias for the SM case, although the pull distributions are all fine for the SM case?

Talks in CMS meetings

-- AndreaGiammanco - 16-Mar-2012

Topic attachments
I Attachment History Action Size Date Who Comment
PNGpng 2j0t_BDT.png r1 manage 42.7 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
PNGpng 2j0t_cosTheta.png r1 manage 34.9 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
PNGpng 2j0t_cosTheta_data_W.png r1 manage 27.0 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
PNGpng 2j0t_metPhi_data_W.png r1 manage 27.6 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
PNGpng 2j0t_metPhi_top.png r1 manage 31.5 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
PNGpng 2j1t_BDT.png r1 manage 56.0 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
PNGpng 2j1t_metPhi.png r1 manage 28.6 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
PNGpng 2j1t_metPhi_data_W.png r1 manage 30.0 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
PNGpng 2j1t_metPhi_top.png r1 manage 32.3 K 2013-08-13 - 15:10 JoosepPata met phi modulation studies
JPEGjpg fcnc_tgq.jpg r1 manage 111.5 K 2012-03-21 - 12:30 AndreaGiammanco FCNC tgq interactions at leading order, from D0's paper

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