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Single Top Polarization analysis

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

Mahlon, Parke, "Single top quark production at the LHC: Understanding spin" (2000) - theoretical definition of the angular observables
TOP-11-021 - single top t-channel cross section measurement at 7 TeV in CMS with 1.1/fb (muon channel) and 1.5/fb (electron channel)
AN-2011-229 - internal document corresponding to TOP-11-021 (many more details, including technical ones) - warning: a few details in the latest version are outdated! When in doubt, refer to the approval talk
"The Angular Correlations in Top Quark Decays in Standard Model Extensions", S. Batebi, S. M. Etesami, M. Mohammadi Najafabadi
...add some beyond-SM papers here...

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:

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

Useful links

Reference selection for the t-channel analysis with 2011 data
Systematics in t-channel analysis
Central wiki of the Single Top group
Central wiki of the Top PAG
Single-top hypernews (hn-cms-singletop@cernNOSPAMPLEASE.ch)
Agenda of the Top PAG group and subgroup meetings; search for "Single Top"
Single-top cross sections
Recommended MC samples in the Top group
theta - tool for profile-likehood fits (very popular in the single top group)
- A general, physics-focused introduction
- Some recommendations
Utilities for integrated luminosity calculation
Running on the GRID
What shapes the cosθ distribution (from an old MC study): 1 - 2

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

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

label	subpath	parent	int. lumi (/pb)
old	./Jul15/WD_SingleMu2	/SingleMu/joosep-Jul8_51f69b-7cb0fdcb434651e6fe30ffadc793c329/USER	4918
new	WD_SingleMu2	/SingleMu/joosep-Jul8_51f69b-7cb0fdcb434651e6fe30ffadc793c329/USER	6398

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.

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:

/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:

SVD Approach to Data Unfolding

RooUnfold:

Unfolding algorithms and tests using RooUnfold

Statistics Committee interim note on unfolding:

Interim Recommendations on Unfolding, Cousins

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, it’s 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

Update talk on 23.01.2014 (Andres)
Single Top Workshop in Naples, 20.12.2013 (Joosep)
Approval talk on 10.09.2013 (Joosep)
Pre-approval talk on 06.08.2013 (Matthias)
Update talk on 25.07.2013 (Joosep)
Update talk on 18.07.2013 (Andres)
Update talk on 06.06.2013 (Matthias)
Update talk on 02.05.2013 (Liis)
Update talk on 21.03.2013 (Steffen)
FastSim/FullSim comparisons and W+jets statistics (Andrea)
Update talk on 11.01.2013 (Andres)
Update talk on 09.11.2012 (Joosep)
Plans Louvain+Estonia, 05.10.2012 (Andrea)
Round table on single top anomalous couplings, 04.05.2012 (Andrea)

-- AndreaGiammanco - 16-Mar-2012

Attachments

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

Topic revision: r108 - 2015-01-19 - MatthiasKomm

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