Analysis summary

1
Analysis summary
2

• Born approx (LO)
• NLO

MC_at_NLO Generator takes these NLO contributions
into consideration
Forbidden in SM
Real emission sub-process q q ? ZZg
Virtual sub-process q q ? ZZ
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Number of reconstructed electrons
Full IsEM0
IsEM 0x20
Identification is based on the Hadronic leakage
Only
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Number of reconstructed electrons
IsEM 0x7FF 0
IsEM 0xFF 0
Selection based on Calo info only
All IsEM cuts except TRT
5
Reconstructed electron Multiplicity

• PT3e gt 10 GeV and Isolation (etcone/pt) lt 0.2

Tight electron
Loose electron
Medium electron N3e 2 N4e

• Efficiency of 3e channel
• less sensitive than 4e channel to electron
  identification cuts
• yields more events.
• Thus, the 3e channel is promising

6
Pt of Electrons (1)
Zbb Sample Electrons in Pt order 3 electrons Ptgt7
at least one Pt gt20
ZZ Sample Electrons in Pt order 3 electrons Ptgt7
at least one Pt gt20
GeV
GeV
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Pt of Electrons (2)
ttbar Sample Electrons in Pt order 3
electrons Ptgt7 at least one Pt gt20
WZ Sample Electrons in Pt order 3 electrons Ptgt7
at least one Pt gt20
GeV
GeV
8
Isolation Missing ET
ZZ sample
ZZ WZ ttbar
ETmiss
Zbb sample
M3e
Zbb
ttbar sample

• ETmiss lt 20 GeV
• etcone30/Pt lt 0.2

9
Impact Parameter Significance (scaled)after a Pt
cut of 10 GeV on the three leptons
muons
electrons
Zbb Zb tt WZ ZZ
Zbb Zb tt WZ ZZ
arbitrary units
arbitrary units
Impact Parameter significance for muons do/sdo lt 3
Impact Parameter significance for
electrons do/sdo lt 5.5
Zbb, Zb and tt are most likely to originate from
displaced vertices. d0 is the distance of closest
approach on the transverse plan
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ETmiss and Isolation in signal and background
Zbb Zb tt WZ ZZ
tt Zbb Zb WZ ZZ
After a Pt cut of 10 GeV on the 3 leptons
After Pt cut, Impact parameter significance and
isolation lt0.15
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Initial selection
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Use Z mass as a cut in the case of ZZ?3e X
e1

• Find which combination of 2 electrons
  makes a Z for both samples ZZ and Zbb.
• Difference in kinematics gives different
  distribution when the electrons are Pt ordered.
• Require opposite sign.
• Define a variable M_ZBest.
• Check the two combination
• M13 and M23
• The closest of them to the
• M_ZPDG is the M_ZBest.
• Consider a cut
• M_ZPDG M_ZBest lt 10 GeV
• The Zbb and Zb are still too high.
• There is a need for the 4th lepton

e2
Z
e2
Z
e4
e3
Z
b
b
e1
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The 4th Electron might be seen as a jet
Remove jets within dR lt 0.2 From any Medium
electron
In the event of 3 Medium electrons are
reconstructed With Pt gt 10 GeV
ZZ sample
Jet Candidate (i.e. a potential electron
reconstructed with Jet Algorithm C4)
Does the jet candidate match the unfound truth
electron
Most reconstructed jets are actually electrons in
this sample.
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Jets vs Jet candidates in ZZ, Zbb and Zb (not
scaled)
Higher number of jets per events is due to the
electrons seen as jets
Jets
Jet candidate
Most ZZ events have at least 1 jet not matching
a medium electron
ZZ Zb Zbb
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Kinematics of matched jet candidate in ZZ? 3e X
Most of jet candidate match the unfound truth
electron There are 1209 matches in DR lt 0.2 e
1209/1318 92
Minimum DR between a jet candidate and the
unfound truth electron in ZZ
Wide range in eta coverage
Truth unfound Z electron Matched Jet candidate
Similar PT spectra
Eta of jet candidate matched to the unfound Z
electron.
Leading jet usually matches unfound electron
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Pt Resolution if Pttruth gt 20 GeV Pt_resolution
0.24
Pt Resolution if Pttruth lt 20 GeV Pt_resolution
0.41
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The CaloTopoCluster algorithm
Wide range in eta coverage
Minimum DR between a topocluster candidate and
the unfound truth electron in ZZ
Most of jet candidate match the unfound truth
electron There are 1693 matches in DR lt 0.2 e
16939/1723 98
M3e
GeV
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Pt resolution for Topo Cluster
RMS 0.26
Truth unfound electron Matched cluster candidate
PT gt 20GeV
Similar PT spectra
RMS 0.39
PT lt 20GeV
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Particle Identification on the jet candidatesEM
fraction
Barrel
End Cap
Jet candidate with a truth match in ZZ
Jet candidate with a truth match in ZZ
No match In ZZ
No match in ZZ
Zbb
Zbb

• The EM fraction was used.
• EMF_Barrel gt 0.8
• EMF_Barrel gt 0.85

Plots are not Normalized
20
Secondary vertex cut SV2 algorithm
ZZ
Zbb
The are 99 entries that have and an SV2 gt 0
99/192 51
The are 80 entries that have and an SV2SUM gt 0 5
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Secondary vertex cut SV2 algorithm
tt
Zb
The are 86 entries that have and an SV2 gt 0
86/192 44
The are 70 entries that have and an SV2 gt 0
70/87 80
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Combination of IP3D and SV1

• No Zbb events pass my cuts
• Only 2 Zb events pass my cuts ( 2 out of 4
  events)
• Use the 3DSV as a cut
• -2,3.5

23
MZ_Best vs. MZ_second in ZZ and Zbb in
ZZ?3e X
ZZ
MZ_Best GeV
Zbb
MZ_Second GeV

• Apply all cuts and take the first leading jet
  candidate (no truth used here). Using jet
  candidate can improve S/B in two ways.
• Kinematic constraints
• (used for now 2D cut)
• 4th lepton makes the second Z peak
• Basic particle ID cuts
• EM fraction EMF_B gt 0.8 EMF_EC gt 0.85
• The EMF reduces the Zbb by a factor of 4 and Zb
  by a factor of 3.

ZZ Zbb Zb
arbitrary units
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Particle Identification on the calo Topo cluster
candidate

• There are more Cluster moments to consider.
• A possibility to build a likelihood.
• the normalized second longitudinal moment
• , with l 0 for the two
  most energetic cells
• , with l 10 cm for the two
  most energetic cells and for all other cells
• 0 means shower more compact in 3D
• 1 means shower more spread
• For now cut on 0.8

ZZ with truth matching Zbb Zb
Not normalized
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Finding the second Z peak with the
CaloTopoCluster Algorithm
MZ_Best GeV
MZ_Best (2m) GeV
ZZ?3e
ZZ?2m1e
MZ_Second GeV
MZ_Second GeV

• The first leading calo topocluster is taken from
  the ones passed the longitudinal moment cut.
• A 2D cut on MZBest and MZSecond should be within
  the interval 80GeV -100 GeV

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Summary table of performances for ZZ Sample
Similar
N.B. We are looking for a cluster without regard
to a track. i.e. a photon like object.
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Final Selection cuts while using the jet
algorithm and the calo Topocluster

• Pt of the 3 leptons PT3e gt 10 GeV and PT2m1e gt
  10 GeV
• Medium electrons, STACO for muons
• Impact parameter significance
• do/so lt 5.5 for electrons
• do/so lt 5 for electrons
• do/so lt 3 for muons
• Isolation etcone20/et lt 0.14
• Missing ET ETmiss lt 25 GeV ( to deal with WZ)
• SV2 lt 0 and 3DSV1comb (w_cmb gt -2) (w_cmb lt
  3.5)) .
• EMF_B gt 0.8 and EMF_EC gt 0.85
• The second longitudinal moment lt 0.8
• Take the first leading jet candidate
• Take the first leading TopoCluster candidate
• MZ_Best between 75 GeV to 100 GeV
• MZ_second between 85 GeV to 110 GeV
• MZ_Best between 80 GeV to 100 GeV
• MZ_second between 80 GeV to 100 GeV

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Results (1fb-1) for the Jet Algorithm and
TopoCluster
Signal 5 events Background 1 event
Signal 5 events Background 6.6 event
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Particle ID of the topoclusters The normalized
second longitudinal moment

• l is the distance of the cell from the shower
  center along the shower axis
• long2 ltl2gt , with l 0 for the
• two most energetic cells
• longmax ltl2gt , with l 10 cm
• for the two most energetic cells and l 0
  for all other cells
• 0 means shower more compact in 3D
• 1 means shower more spread

ZZ Zb Zbb
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Particle ID of the topoclusters The normalized
second lateral moment

• r is the distance of the cell from the shower
  axis
• lat2 ltr2gt , with r 0 for
• the two most energetic cells
• latmax ltr2gt , with r 4 cm
• for the two most energetic cells and r 0
  for all other cells
• 1 means big showers,
• and 0 means small showers

ZZ Zb Zbb
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Isolation Max
energy fraction
ZZ Zb Zbb

• Energy fraction of the most energetic cell

The layer energy weighted fraction of
non-clustered neighbor cells on the outer
perimeter of the cluster
All these moments are not suitable for a standard
cut. Thus, a multivariate technique is crucial
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Longitudinal vs. Isolation
Background
Signal
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The likelihood method
These distributions can be used to assign a
probability for a given topocluster to be signal
or background
and
Multiplication of these variables gives the
overall probability for the event.
The likelihood discriminant is defined as
following
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Getting the Ps and Pb

• Get the Ps from Z ? ee by requiring one medium
  electron in the event and the second one will be
  a cluster from unreconstructed electron
• Get the Pb from tt sample
• Normalize to 1 to get the pdfs

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The probabilities for signal and
background (pdf)
S B
S B
Normalized second lateral moment
Normalized second longitudinal moment
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The probabilities for signal and
background (pdf)
S B
S B
Energy fraction in the most energetic cell
The layer energy weighted fraction of
non-clustered neighbor cells on the outer
perimeter of the cluster
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Likelihood Signal is ZZ and
Background is Zbb
S B

• e of signal events that passes a given
  likelihood/total of signal event
• Fake rate (f) of background events that
  passes a given likelihood/total of background
  event

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Shapes of the backgrounds likelihoods
For L gt 0.3 e 82 fZbb 19 fZb 25 fWZ
23 fttbar 15 fb 12 Zjets not
available on release 13 nor 14
WZ Zbb Zb b
The shapes are similar
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Likelihood dependence on h

• The pdfs are strongly h dependent
• The barrel is divided into three regions
• Barrel-1 hlt 0.7
• Barrel-2 h gt 0.7 and hlt1
• Barrel-3 hgt1 and hlt1.375
• End Cap
• EC-1 hgt1.375 and hlt1.9
• EC-2 hgt1.9 and hlt2.5
• EC-3 hgt2.5 and hlt3.2
• FCal
• hgt3.2

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Signal efficiency and fake rates for L gt 0.5
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Efficiency vs. PT
Fake vs. PT
ZZ diboson
Zbb sample
Low PT lowers the efficiency
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Topology of an LHC event at particle level

• All hadronization occurs at one space point
  primary vertex.
• Some particles are long lived i.e. can travel
  longer before decaying.
• Example of these particles b/c hadrons, t
  leptons.
• Particles from these decays form secondary
  vertices.
• Good vertexing ability can separate primary and
  secondary vertices and thus identify b jets

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Topology of full LHC event with pile up

• At LHC low luminosity there will be 4.6
  collisions per bunch crossing which are readout
  as a single event.
• At LHC high luminosity it will be 23 collisions
  per bunch crossing.
• This pile up creates a challenge for finding
  primary and secondary vertices.
• Fortunately, most of pile up is minimum bias
  collisions and can be separated from hard
  scattering processes by requiring the presence of
  high Pt particles in the primary vertex.

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B tagging

• Definition
• B tagging means identification of jets which
  contains a b quark.
• Lifetime 1.5 ps i.e. flight distance 4mm for
  50 GeV particle.
• Have non zero Impact parameter
• Possible B tagging methods
• Lifetime tag (impact parameter)
• Secondary vertex

do
do is the track impact parameter in the
transverse plane (r-f). zo is the track impact
parameter in the longitudinal plane (r-z).
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Charged tracks and track selection

• In average a track consist of
• 3 pixel hits
• 4 space points in the silicon micro-strip
  detector
• 36 hits in the TRT
• The track selection for b tagging
• Select well measured tracks
• Reject fake tracks from long lived particles (Ks,
  L,..)
• Reject tracks from material interactions (photon
  conversions or hadronic interactions).
• At least two hits in the pixel detector of which
  one must be in the b layer as well as do lt 1 mm
  and zo - zpvsinq lt 1.5 mm
• This selection is used by algorithms relying on
  Impact parameter

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B tagging Algorithms Impact Parameter algorithm

• Most of them are based on likelihood ratio
  approach.
• Secondary interactions rejection is achieved by
• Building all two-track pairs that form a good
  vertex
• The mass of the vertex is used to reject the
  tracks which are likely to come from Ks, L decays
  or photon conversions.
• Impact parameter tagging algorithm
• IP1D relies on the longitudinal impact parameter.
• IP2D relies on the transverse impact parameter
• IP3D uses 2D histograms of the longitudinal vs.
  transverse IP, taking advantage of their
  correlations.

47
Secondary vertex tagging algorithm

• Vertices compatible with Vo or material
  interaction are rejected.
• In All remaining two-track, iterate until the c2
  of the vertex fit is good.
• Three properties are used
• The invariant mass of all tracks associated to
  the vertex.
• Energy Ratio The ratio of the sum of the
  energies of the tracks participating on the
  vertex to the sum of the energies of all tracks
  in the jet .
• Number of two-track vertices

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Formalism of likelihood ratio

• Comparison of measured value Si to a pre-defined
  smoothed and normalized distributions for both
  the b- and light jet hypothesis, b(Si) and u(Si).
• 2D or 3D pdf are used
• The ratio b(Si)/ u(Si) defines the track or
  vertex weight.
• SV1 2D distribution of the two first variables
  and a 1D distribution of the number of two-tracks
• SV2 3D-histogram of the three properties