Double parton interactions in + 3 jets events in p...
Transcript of Double parton interactions in + 3 jets events in p...
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Double parton interactions in γ + 3 jets events
in pp̄ collisions at√s = 1.96 TeV in CDF
Giorgia Rauco
Fermilab, CDF
Summer Internship 2013
Supervisor:
Raymond L CulbertsonTutor:
Alessandra Lucà
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 1 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Outline
1 Introduction and DPI theory
2 Kinematics of γ + 3 jets events
3 Discriminating variables
4 Data results
5 Montecarlo simulations
6 Summary
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 2 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Outline
1 Introduction and DPI theory
2 Kinematics of γ + 3 jets events
3 Discriminating variables
4 Data results
5 Montecarlo simulations
6 Summary
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 2 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Outline
1 Introduction and DPI theory
2 Kinematics of γ + 3 jets events
3 Discriminating variables
4 Data results
5 Montecarlo simulations
6 Summary
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 2 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Outline
1 Introduction and DPI theory
2 Kinematics of γ + 3 jets events
3 Discriminating variables
4 Data results
5 Montecarlo simulations
6 Summary
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 2 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Outline
1 Introduction and DPI theory
2 Kinematics of γ + 3 jets events
3 Discriminating variables
4 Data results
5 Montecarlo simulations
6 Summary
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 2 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Outline
1 Introduction and DPI theory
2 Kinematics of γ + 3 jets events
3 Discriminating variables
4 Data results
5 Montecarlo simulations
6 Summary
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 2 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Introduction
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 3 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Introduction
Single Parton Collision
One partonic scattering in oneproton-antiproton collision
Double Parton Collision
Two indipendent partonicscatterings in oneproton-antiproton collision
Final state of DPI: γ+jet and dijet
The �rst analysed was performed by UA2 in 1991
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 4 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Introduction
How?
γ + 3 jets events∫L dt = 9.5 fb−1
pp̄ collisions at√s = 1.96
TeV
Why?
to determine the fraction of the DPI in a single pp̄ collision
to make accurate estimation of background for many rare
new physics processes
QCD studies
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 5 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Introduction
How?
γ + 3 jets events∫L dt = 9.5 fb−1
pp̄ collisions at√s = 1.96
TeV
Why?
to determine the fraction of the DPI in a single pp̄ collision
to make accurate estimation of background for many rare
new physics processes
QCD studies
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 5 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Kinematics
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 6 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Kinematics of γ + jets events:
Multiplicities
Figure: Multiplicities of photons and jets depending on their energy, in
linear and log scale
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 7 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Kinematics of γ + jets events:
angular distributions
Figure: Azimuthal angle and pseudorapidity distributions for the γ and for
the leading jet, as a function of their energy
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 8 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Kinematics of γ + jets events:
energy distributions
Figure: Energy distributions for the γ and for the leading jet
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 9 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Discrimination beetweenDPI and SPI
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 10 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Discriminating variables
D0 Collaboration, arXiv:0912.5104v2 [hep-ex]
Discriminating DPI from SPI
Try to exploit the back-to-back nature of the objects coming fromSPI events
∆S = ∆φ( ~pT (γ, i), ~pT (j , k)) (1)
In the γ + 3 jet analysis,
the i , j and k objects are
chosen such as to minimize
the pT imbalance
In this way, it is possible to
split the γ + 3 jet into
γ+ jet and dijet pairs
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 11 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Discriminating variables
The two object pairs are found by minimizing three other
variables with respect to the jet index:
SpT =1√2
√(| ~pT (γ, i)|δpT (γ, i)
)2
+
(| ~pT (j , k)|δpT (j , k)
)2
(2)
Sp′T
=1√2
√√√√√( | ~pT (γ, i)|| ~pγT | + | ~pi
T |
)2
+
| ~pT (j , k)|
| ~pjT | + | ~pk
T |
2
(3)
Sφ =1√2
√(∆φ(γ, i)
δφ(γ, i)
)2
+
(∆φ(j , k)
δφ(j , k)
)2
(4)
where ∆φ(γ, i) = |π − φ(γ, i)|
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 12 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Discriminating variables
The two object pairs are found by minimizing three other
variables with respect to the jet index:
SpT =1√2
√(| ~pT (γ, i)|δpT (γ, i)
)2
+
(| ~pT (j , k)|δpT (j , k)
)2
(2)
Sp′T
=1√2
√√√√√( | ~pT (γ, i)|| ~pγT | + | ~pi
T |
)2
+
| ~pT (j , k)|
| ~pjT | + | ~pk
T |
2
(3)
Sφ =1√2
√(∆φ(γ, i)
δφ(γ, i)
)2
+
(∆φ(j , k)
δφ(j , k)
)2
(4)
where ∆φ(γ, i) = |π − φ(γ, i)|
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 12 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Discriminating variables
The two object pairs are found by minimizing three other
variables with respect to the jet index:
SpT =1√2
√(| ~pT (γ, i)|δpT (γ, i)
)2
+
(| ~pT (j , k)|δpT (j , k)
)2
(2)
Sp′T
=1√2
√√√√√( | ~pT (γ, i)|| ~pγT | + | ~pi
T |
)2
+
| ~pT (j , k)|
| ~pjT | + | ~pk
T |
2
(3)
Sφ =1√2
√(∆φ(γ, i)
δφ(γ, i)
)2
+
(∆φ(j , k)
δφ(j , k)
)2
(4)
where ∆φ(γ, i) = |π − φ(γ, i)|
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 12 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Discriminating variables
We plotted the three variables and the three jets combinations.
SpT distribution Sp′T
distribution Spφ distribution
Observation
Good separation between the plots of the pair (γ, jet 0) and theremaining two.
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 13 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Discriminating variables
We plotted the three variables and the three jets combinations.
SpT distribution Sp′T
distribution Spφ distribution
Observation
Good separation between the plots of the pair (γ, jet 0) and theremaining two.
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 13 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Data results
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 14 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Data results
We plotted the index of the jet associated to the γ which
minimizes the three variables.
Result
The best pairs combination is (γ, jet 0) and (jet 1, jet 2).
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 15 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Data results
We plotted the index of the jet associated to the γ which
minimizes the three variables.
Result
The best pairs combination is (γ, jet 0) and (jet 1, jet 2).
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 15 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Data results
∆S = ∆φ( ~pT (γ, 0), ~pT (1, 2)) (5)
with the pairs obtained based on the best pairwise balance
Result
The tail between 0 and 1.5 is relatively �at → Evidence for DPI
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 16 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Data results
This is constistent with the theoretical hyphotesis:
SPI
distribution ∆S should peak at π and should show a tail due to
the radiation
DPI
distribution ∆S alone should be relatively �at
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 17 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Montecarlo
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 18 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Montecarlo results
∆SpT distribution ∆Sp′T
distribution ∆Spφ distribution
evidence of the tail
- relatively �at for DPS- with a light slope due to the radiation for SPS
DPI samples bigger than SPI sample (SPS has no MPI)
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 19 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Montecarlo results
∆SpT distribution ∆Sp′T
distribution ∆Spφ distribution
evidence of the tail
- relatively �at for DPS- with a light slope due to the radiation for SPS
DPI samples bigger than SPI sample (SPS has no MPI)
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 19 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Conclusions
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 20 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Conclusions
the best pair combination for the �nal state is (γ, jet 0)and (jet 1, jet 2)
evidence for DPI thanks to the low sided tail in the ∆S plot
What is next?
found the fraction of DPI using both Montecarlo and data
obtain the DPI cross section
To be continued...
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 21 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Conclusions
the best pair combination for the �nal state is (γ, jet 0)and (jet 1, jet 2)
evidence for DPI thanks to the low sided tail in the ∆S plot
What is next?
found the fraction of DPI using both Montecarlo and data
obtain the DPI cross section
To be continued...
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 21 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Conclusions
the best pair combination for the �nal state is (γ, jet 0)and (jet 1, jet 2)
evidence for DPI thanks to the low sided tail in the ∆S plot
What is next?
found the fraction of DPI using both Montecarlo and data
obtain the DPI cross section
To be continued...
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 21 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Conclusions
the best pair combination for the �nal state is (γ, jet 0)and (jet 1, jet 2)
evidence for DPI thanks to the low sided tail in the ∆S plot
What is next?
found the fraction of DPI using both Montecarlo and data
obtain the DPI cross section
To be continued...
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 21 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Conclusions
the best pair combination for the �nal state is (γ, jet 0)and (jet 1, jet 2)
evidence for DPI thanks to the low sided tail in the ∆S plot
What is next?
found the fraction of DPI using both Montecarlo and data
obtain the DPI cross section
To be continued...
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 21 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Conclusions
the best pair combination for the �nal state is (γ, jet 0)and (jet 1, jet 2)
evidence for DPI thanks to the low sided tail in the ∆S plot
What is next?
found the fraction of DPI using both Montecarlo and data
obtain the DPI cross section
To be continued...
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 21 / 22
DoubleParton
Interactions
GiorgiaRauco
Outline
Introduction
Kinematicsof γ + jetsevents
Discriminatingvariables
Data results
Montecarlo
Conclusions
Acknowledgement
Raymond L Culbertson &
Costas Vellidis
Alessandra Lucà
Simone Donati &
Giorgio Bellettini
Italian Summer Students
Giorgia Rauco (CDF) Double Parton Interactions Summer Internship 2013 22 / 22