20150701 PAT-tutorial MINIAOD Tholen - Collaboration … slide pool... · · 2015-07-01Analysis1 tuple Analysis2 tuple Analysis3 tuple Analysis5 tuple ... – with some loose preselection

Heiner TholenUniversity of Hamburg

MINIAODPAT Tutorial

June/July 2015

1

•what is miniaod?• eventformat / datatier

• small event size

• ... use other slides from rizzi

•hands on• miniaod objects and collections

• example

2

what is miniaod?

slides taken fromhttps://indico.cern.ch/event/326181/contribution/4

by Giovanni Petrucciani

https://indico.cern.ch/event/326181/contribution/4

MiniAOD: overall idea!•  Compact high-level data tier (30-50 kb/event)

designed to cover the mainstream analyses replacing the need of big group-level pattuples or ntuples

25.06.14 A. Rizzi (Pisa), G. Petrucciani (CERN) 3

Analysis2 tuple

Analysis3 tuple

Analysis1 tuple

Analysis2 tuple

Analysis3 tuple

Analysis5 tuple

AOD CERN CMGTuple

B2G PATuple

MIT NTuple

…

ETH EDMNTuple

MiniAOD

Analysis1 tuple

AOD

RECO

RECO

very analysis-specific usually flat trees, ~1TB

~1 month

general purpose ntuples 30-100 kb/ev, tot. O(100) TB

1-2 days

promptly

when new high level calibrations or recipes become available

if needed?

Analysis5 tuple

1-2 days

TYPIC

AL R

UN1!

WO

RK

FLO

W!

MIN

IAO

D!

WO

RK

FLO

W!

4

MiniAOD event content!•  High level physics objects (e.g. leptons, jets, …)

–  with detailed information, e.g. to allow retuning of IDs –  with some loose preselection if needed to fit the budget

•  All PF Candidates, in a smartly packed format –  allow re-computing isolations, re-clustering of jets,

jet substructure analysis, event interpretation, … –  including track parameters, to also re-run b-tagging

•  Trigger information: bits, and 4-vectors of objects •  MC truth: “interesting” genParticles, plus all status==1

genParticles (packed), plus GEN/LHE/PDF/PU info •  Other small footprint stuff (e.g. vertices, MET filter flags)

28.05.14 A. Rizzi (Pisa), G. Petrucciani (CERN) 5 5

MC information!•  The full list of genParticles is too large to keep, so we

follow a two-prong approach: •  prunedGenParticles: the interesting particles

–  select leptons, photons, EWK bosons, top quarks, high pT partons, heavy flavour quarks & hadrons, …

–  saved with full information, mother-daughter links, …(reconnecting them if intermediate particles are dropped)

•  packedGenParticles: all status == 1 particles –  useful e.g. to remake GenJets with different clustering –  use a lossy compressed format like for PF candidates. –  include a link to the mother, or closest ancestor available

in the prunedGenParticles collection (e.g. for flavour history)


Cross-referencing!

•  High level physics objects in miniAOD contain references to the packed PF candidates corresponding to the original PFCandidates they came from: –  useful e.g. for footprint removal in isolation, event

interpretation (aka “top projection”), …


E/G Muon Tau Jet

PF PF PF PF PF PF PF PF PF PF PF PF PF PF PF PF

one or more

note: if a muon fails the PF id, it will point to a PF hadron!

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Physics Objects!Electrons: –  keep all gedGsfElectrons –  detailed info for pT > 5 GeV

Muons: –  keep all with pT > 5, or that

pass some loose id (details) –  all information saved

Taus: –  keep those with pT > 20 &

‘decayModeFinding’ ID –  save IDs & links to PFCands.

Photons: –  keep those with pT > 14 &

hadTowOverEm <0.15 –  detailed info if r9 > 0.8 OR

chargedHadronIso < 20 OR chargedHadronIso < 0.3 · pT

Jets (ak4PFchs, ak8PFchs): –  keep those with pT > 10 GeV

(pT > 100 for AK8 ones) –  note: JEC are applied –  keep daughters, id info, b-tag

discriminators


Size decomposition !


Mu

PFCands

Jet

Gen Gen

Jet

Mu Trig

E/G

E/G

Single Muon Data

TTbar MC PFCands

E/G

E/G

9

•miniaod is not yet backward compatible. I.e. a file made in 7_4_1 can only be read within 7_4_X versions

•if you're interested in how the compression works:https://github.com/cms-sw/cmssw/blob/CMSSW_7_4_X/DataFormats/PatCandidates/interface/PackedCandidate.h

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notesminiaod format

https://github.com/cms-sw/cmssw/blob/CMSSW_7_4_X/DataFormats/PatCandidates/interface/PackedCandidate.h

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https://twiki.cern.ch/twiki/bin/view/CMSPublic/WorkBookMiniAOD2015

documentation<>

https://twiki.cern.ch/twiki/bin/view/CMSPublic/WorkBookMiniAOD2015

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https://twiki.cern.ch/twiki/bin/view/CMSPublic/WorkBookMiniAOD2015#Analyzing_MiniAOD

analyzing miniaod <>

https://twiki.cern.ch/twiki/bin/view/CMSPublic/WorkBookMiniAOD2015#Analyzing_MiniAOD

•MINIAOD is designed to save diskspace

•amounts of objects are reduced to the important ones

•less important objects are packed with lossy compression

•if you don't need specialized objects, you could work with MINIAOD samples directly (=> exercises)

•the names of the collections are changed, as compared to RECO, AOD, PAT

•questions?

13

summaryminiaod format

object disambiguationwith (top) projections

•yesterday: cross-object-cleaning• if you do nothing...

=> ambiguities

15

object disambiguation

leptonjet axis

=>

•yesterday: cross-object-cleaning• jets overlapping with leptons are completely removed

16


leptonjet axis

=>


•other possibilities to disambiguate?

17


leptonjet axis

=>


•other possibilities to disambiguate?• reclustering of jets without selected muons

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leptonjet axis

=>



• substract lepton p4 from jet p4 (in general: different result)

19


leptonjet axis

=>



• substract lepton p4 from jet p4 (in general: different result)

20


leptonjet axis

=>

The exercise will deal with reclustering of jets.The tool to accomplish this type of disambiguation is called "top projections". Its idea is explained in the next slides.Slides taken from:https://indico.cern.ch/event/314115/session/7/contribution/25by Sadia Khalil

https://indico.cern.ch/event/314115/session/7/contribution/25

















Ranking of Event Reconstruction and Interpretation

8 21

22

Top projection

13

• In generic terms, a top projection has two inputs:

- The objects we want to disambiguate ➡Top Collection

- The objects we have ➡Bottom Collection

• Inputs of any type

23

Top projection

14

• In generic terms, a top projection has two inputs:

- The objects we want to disambiguate ➡Top Collection

- The objects we have ➡Bottom Collection

• Inputs of any type

24

Top projection

15

25

Top projection

16

26

Top projection

17

27

Top projection

18

28

Top projection

19

particleFlow

(1)

(2)

(3)

(1)

( (

(4)

(5)

(6)

pfJet

pfPileUp

pfNoPileUp

pfMuon

pfNoMuon

pfElectron

pfNoElectron

pfTau

pfNoTau

Top projection in PF2PAT

- input source for PAT (2) (3) (4) (5)

PFBRECO = cms.Sequence( pfNoPileUpSequence + pfParticleSelectionSequence + pfPhotonSequence + pfMuonSequence + pfNoMuon + pfElectronSequence + pfNoElectron + pfJetSequence + pfNoJet + pfTauSequence + pfNoTau + pfMET )

29

object disambiguation exercise

DeltaR(mu, leading jet)

pt(m

u) /

pt(je

t)

30



pt(m

u) /

pt(je

t)

jet seems to consistof the muon alone

31



pt(m

u) /

pt(je

t)

jet seems to consistof the muon alone

exercise:- reproduce this plot- make your own miniaod tuple with

reclustered jets- make this plot with your new jets- check that the ambiguity is gone

exercise: simple W-tagging

•jet-tagging is getting more important• heavy BSM particles => boosted W, Z, H, t

• decay products merged into single fat jets

•jet-substructure info• N-subjettiness

(measure of number of subjets)

• grooming algorithms(remove contribution from unwanted particles)

33

W-taggingintro






34

W-taggingintro

From the miniaod-twiki:double tau1 = jet.userFloat("NjettinessAK8:tau1"); //double tau2 = jet.userFloat("NjettinessAK8:tau2"); // Access the n-subjettiness variablesdouble tau3 = jet.userFloat("NjettinessAK8:tau3"); //

double softdrop_mass = jet.userFloat("ak8PFJetsCHSSoftDropMass"); // access to filtered massdouble trimmed_mass = jet.userFloat("ak8PFJetsCHSTrimmedMass"); // access to trimmed massdouble pruned_mass = jet.userFloat("ak8PFJetsCHSPrunedMass"); // access to pruned massdouble filtered_mass = jet.userFloat("ak8PFJetsCHSFilteredMass"); // access to filtered mass

bool mySimpleWTagger = (tau2/tau1) < 0.6 && softdrop_mass > 50.0;






35

W-taggingintro

From the miniaod-twiki:double tau1 = jet.userFloat("NjettinessAK8:tau1"); //double tau2 = jet.userFloat("NjettinessAK8:tau2"); // Access the n-subjettiness variablesdouble tau3 = jet.userFloat("NjettinessAK8:tau3"); //

double softdrop_mass = jet.userFloat("ak8PFJetsCHSSoftDropMass"); // access to filtered massdouble trimmed_mass = jet.userFloat("ak8PFJetsCHSTrimmedMass"); // access to trimmed massdouble pruned_mass = jet.userFloat("ak8PFJetsCHSPrunedMass"); // access to pruned massdouble filtered_mass = jet.userFloat("ak8PFJetsCHSFilteredMass"); // access to filtered mass

bool mySimpleWTagger = (tau2/tau1) < 0.6 && softdrop_mass > 50.0;

exercise:- find W's in genParticle collection and match

them to ak8 jets => signal / background- plot N-subjettiness for signal and background- write your own W-tagger- what's the performance of your tagger?- improve your tagger! =)

summary

•MINIAOD is a new standard event format in CMS

•designed to suite most analyses' needs=> might need to check if it fits your needs

•"top projections" help to disambiguate objects

•jet-tagging with substructure information

•questions?

37

summaryminiaod

Documents

20150701 PAT-tutorial MINIAOD Tholen - Collaboration … slide pool... · · 2015-07-01Analysis1 tuple Analysis2 tuple Analysis3 tuple Analysis5 tuple ... – with some loose preselection