Production and Evolution of High Energy Jets - PowerPoint PPT Presentation

1 / 112
About This Presentation

Production and Evolution of High Energy Jets


Production and Evolution of High Energy Jets Outline (both lectures) A look at the data Theoretical framework Inclusive Jet Cross sections Multijet Events – PowerPoint PPT presentation

Number of Views:37
Avg rating:3.0/5.0
Slides: 113
Provided by: psu94
Learn more at:


Transcript and Presenter's Notes

Title: Production and Evolution of High Energy Jets

  • Production and Evolution of High Energy Jets
  • Outline (both lectures)
  • A look at the data
  • Theoretical framework
  • Inclusive Jet Cross sections
  • Multijet Events
  • Double Parton Scattering
  • Underlying Event
  • Clustering algorithms
  • Structure inside jets
  • Overall Theme Interplay of Theory and

Day 1
Day 2
Simple view of a proton - antiproton collision
  • Pseudo-rapidity
  • - ln tan ?/2
  • Simple translation
  • (additive) under
  • longitudinal boosts

  • 2?2 scattering
  • Two partons are produced from the collision of a
  • parton in each of the incoming hadrons
  • Initial partons have a fraction, x, of proton
  • longitudinal momentum and small 0 transverse
  • Each outgoing parton forms one jet
  • Events are characterized by x and Q2, where Q is
    the total momentum transfer ETjet

Jets at Fermilab Hadron Collider
  • Fermilab Tevatron collides protons and
    antiprotons at
  • vs 1.96 GeV
  • (was 1.8 TeV in Run 1)
  • These collisions produce the highest energy jets
    (ET500 GeV)
  • Probes proton structure to smallest distance
  • ? hc/Mc2
  • 197MeVfm/500 GeV
  • 4x10-17cm

Jet ET Sum of towers 415 GeV
Regions Covered by Different Measurements
  • Tevatron data overlaps and extends reach of DIS
    (talks by Jose Repond)
  • This talk concentrates on jet production at the

What is a Jet?
  • Jets are the clusters of particles produced by
    the scattered partons
  • Particles (mostly hadrons) are produced nearly
    collinear to parent parton
  • Underlying Event Remnants of incoming hadrons
    leave some low energy particles too. These are
    randomly distributed, not in clusters
  • Fundamental concept Sum up all the daughter
    particles and you approximate the properties of
    the scattered parton

End view of the two-jet event in CDF
Azimuthal angle
Tracks in magnetic field
Can measure momentum of charged particles in
tracking chambers. Neutral particles e.g (p0)
are measured only by the calorimeters
More complicated events three-jet event
  • ET 328 GeV
  • ? 0.21
  • f 2.5o

ET 123 GeV ? 0.23 f 170.4o
ET 173 GeV ? -0.57 f 192.4o
A five-jet event
6 - jet events
From Partons to Jets
Leading Log Approximation (LLA) sum leading
contributions to all orders (from collinear
radiation of quarks and gluons around original
Leading Order Theory Uses 2?2 matrix elements
Parton Shower
Only two jets in final state Only one parton/jet
From Partons to Jets Cont.
  • Hadronization Each parton in the shower is
    converted into colorless hadrons
  • The hadrons are measured in the tracking chambers
    and calorimeters
  • Sum of the momentum and energy of all the
    particles in a cluster
  • ? particle level jet
  • scattered parton

Clustering (or Jet) algorithms Rules for
combining measured energy into Jets
Comparisons between Data and Theory
  • Overall rate of jet production ( cross sections)
  • Valid over full ET range (Jet ET 20 GeV 500
  • Match data for different vs ?
  • Look for something new and unexpected which
    increases the rate of jet production over the
    predicted rates
  • rate of multi( 3, 4, 5...) jet events, can QCD
    predict these higher order processes?
  • Details of event structure
  • Jet shapes
  • Structure inside jets
  • Multiple parton interactions
  • Use Monte Carlo programs (e.g. ISAJET) to
    generate hadrons from LO predictions, and a
    detector simulation to derive corrections to data
  • Compare corrected data to pQCD parton level
  • Theory no dependence on empirical parton shower
    or hadronization models
  • Data can minimize and quantify dependence of
    corrections on modeling

Theoretical predictions at the parton level
fa/A(xa ,?F) Parton Momentum Distributions
(PDF) probability to find parton of type a in
hadron A with momentum fraction xa ?F
4-momentum transfer or factorization scale of
  • partonic level
  • cross section

Rapidity and Pseudo-rapidity
scattered parton
Rapidity (y)
bcosq tanh y where b p/E
Pseudorapidity (?) high energy limit (mpT, ß ?
Rapidity and Pseudo-rapidity are simply additive
under longitudinal boosts
Parton momentum fractions
  • x1 (e?1 e?2) ET/vs
  • x2 (e-?1 e-?2) ET/vs

x1 and x2 can not exceed unity ? -ln tan ?/2
xT 2ET/?s and xT2 ltx1x2lt1 As xT ? 1, x1
and x2 are tightly constrained
??boost ½ (??1 ?2) ?? ½ (??1 - ?2) ??Lab
?? ?boost
Kinematic Variables
  • Transverse Energy ET
  • ET m2 px2 py2 Esin?
  • E2- pz2
  • Energy E
  • E2 m2 p2
  • ET cosh ?
  • Momentum p
  • p2 px2 py2 pz2
  • Longitudinal momentum
  • pz E tanh ?
  • ET sinh ?
  • Transverse Momentum pT
  • pT px2 py2 psin?
  • Invariant Mass for di-jet event
  • M122 (p1 p2)2
  • m12 m22 2(E1E2-p1p2)
  • For m1, m2 ? 0
  • M122 ? 2ET1ET2(cosh?? cos?f)

Phase Space Boundaries for 2 ?2 Scattering
?s 2 TeV and Jet ET 100, 200 and 400 GeV
  • phase space shrinks
  • as ET increases
  • for??1 -?2 , ??boost ? 0
  • for??1 ?2 , M122 4ET2

Leading Order Two-Jet Cross Section
At leading order ET1 ET2 ET
  • where,
  • fi(x,?F) (i g, q, q) is the PDF
  • Mij is lowest order matrix element for ij?2
  • summed and averaged over initial and
    final states
  • ?s(?R) is the strong coupling constant
  • ?F is the factorization scale
  • ?R is the renormalization scale

Usually assume ?F ?R ? ET/2
Many processes contribute
Lowest order matrix elements
  • Matrix elements for

Averaged (summed) over initial (final) state
colors and spins
where s (p1 p2)2, t (p1 - p3)2 and u (
p2-p3)2 are the Mandelstam variables
Quark and Gluon contributions to cross section
Solid ?s 2 TeV Dashed ?s 14 TeV
  • Lowest ET jets from
  • Tevatron are 20 GeV
  • or xT 0.02
  • gluon initial states
  • dominate
  • Highest ET jets are
  • 500 GeV or xT 0.5
  • ??qq dominates,
  • but qg still 20 of total

Fraction of total
  • xT 2ET/?s

The single effective subprocess approximation
  • All the matrix elements have similar shape
  • Can approximate the parton momentum distributions
    fi(x,?F) (i g, q, q) as a single effective

And the lowest order cross section can be written
Parton Luminosity
  • In the single effective subprocess approximation
    the parton-parton luminosity (x1F(x1,µ)x2F(x2,µ)
    ) can be written as a function of ??boost and
  • For ET 100 GeV and vs 2TeV
  • largest luminosity is when x1 and
  • x2 are equally small ?boost ?? 0
  • As ?boost or ?? increases
  • luminosity decreases rapidly

Digression on the scales ?F and ?R
  • ?F and ?R are artifacts of working at fixed order
    in perturbation theory.
  • The predictions should not depend on the choice
    of scales (Data doesnt!)
  • The renormalization scale ?R shows up in the
    strong coupling constant because it is introduced
    when the bare fields are redefined in terms of
    the physical fields
  • The factorization scale ?F is introduced when
    absorbing the divergence from collinear radiation
    into the PDFs
  • Can choose any value for ?F and ?R
  • Typical choice ?F ?R ET/2 of the jets
  • Dependence of predictions on scale indicates
    potential size of higher order contributions
  • Dependence on scale should get smaller as higher
    order terms are included
  • Usually study predictions with range ? ET/4 to

Digression on the scales ?F and ?R cont.
as2 for different ?R compared to ?R ET
for different ?F compared to ?F ET at ?1 ?2
Dependence of LO on choice of scales flat at
10 level for ?ET/2 but normalization uncertain
at 50 level
Inclusive Jet Cross Section Measurements
  • Fundamental and simple test of QCD predictions
  • Include all jets in the event within a given ?
  • Can search for signs of composite quarks

Inclusive Jet Cross Section and Compositeness
  • Compositeness Scale ?c
  • ?c ?? pointlike quarks
  • ?c ?finite ? substructure
  • at mass scale of ?c
  • Hypothesis Quarks are bound states of preons
    which interact via new strong interaction

The composite interactions are represented by a
contact term
  • Compositeness
  • enhances the jet
  • cross section
  • has different ang.
  • dist. from QCD

Measurements of Inclusive Jet Cross Section
  • In the 80s, only Leading Order 2?2 predictions
    were available
  • High energy Jet data was just becoming available
  • AFS vs 63 GeV initial hints of 2-jet
  • UA1 and UA2 vs 546 and 630 GeV , (ET
    20-150 GeV)
  • CDF 1987 vs 1800 (ET 30-250 GeV)
  • Obviously in the data there were events with more
    than 2 jets!
  • Try to make data and theory look more alike
  • Parton shower Monte Carlo program ISAJET FF
    fragmentation, LLA
  • Tune parameters of parton shower and
    hadronization to give agreement with data
    minimizes dependence of corrections on details of
    the model.
  • Defined clustering algorithms which could make
    data look like 2?2 process
  • Summed energy in a large cones R 1 1.2 (cone
  • Summed neighboring towers (nearest-neighbor

  • LO Theory
  • PDFs derived from global fits to data (See talk
    by Walter Giele)
  • Choice of scale for evaluation of as and PDFs
  • higher order corrections
  • Total uncertainty ranged from a factor of 2 to a
    factor of 10 depending on ET
  • Experimental Measurement uncertainties
  • energy scale (could be a whole talk by itself)
  • luminosity
  • corrections to go from measured jets to partons
    (e.g. energy that escaped the cone or jet
  • underlying event (extra energy that leaked into

Inclusive Jet Cross Sections from the 80s
UA1 Unc. 70 50 jet corr. 40 jet calib
10 aging 15 lum ?c gt400 GeV
UA2 Unc. 32 25 Frag. model 15 jet id
11 calib 5 lum ?c gt825 GeV
Theory uncertainties mainly on normalization
compositeness limits set based on shape at high ET
CDF 1987 data Exp. Unc. 70 _at_ 30 GeV 34 _at_ 250
GeV ?c gt700 GeV
While data and theory agreed qualitativly, large
uncertainties existed in both theoretical
predictions and in experimental measurements
NLO 2?2 Theory predictions
  • Late 80s NLO parton level predictions became
  • Aversa et al PLB 210,225 (1988), S.Ellis, Kuntz,
    Soper, PRL 62,2188(1989) ( EKS)

1 loop, 2 parton final state same kinematics as
LO 1 parton jet
tree level, 3 parton final state or 21 parton
final state
Now have possibility of combining partons to
form a jet. Predictions sensitive to size of jet
and way in which partons are combined
NLO 2?2 Theory predictions
  • Dependence on the choice of scale reduced from
    factor of 2 to 30, more precise comparison to
    data possible
  • Ushered in a new era of Jet identification
  • Could use the same algorithm to cluster partons
    into jets as is used to cluster towers of energy
    in the detector
  • Should minimize difference between data and
    theory predictions due to technical differences
  • Led to SNOWMASS accord
  • cone algorithm to be used by CDF, D0 and Theory
  • detailed rules for combining towers (partons)
    into jets
  • No out-of-cone energy correction! (part of NLO
  • still have to estimate and subtract UE energy
  • Other algorithms also exist will be described

SNOWMASS Algorithm
  • Choose a seed tower from a list of high ET towers
  • Define a cone of radius R around the seed tower

Towers (partons) within the cone are associated
with the jet. Calculate new cluster centroid
loop over towers again until stable set of
towers is reached. Finally
Snowmass studies (1992) found that for a cone
size of 0.7 out-of-cone energy underlying event
Inclusive cross section compared to NLO
  • CDF collected data in 1989
  • 4pb-1 vs 1800 GeV
  • 8nb-1 vs 546 GeV
  • Compared to NLO predictions still uncertain due
    to scale and PDFs, but better than LO
  • Statistical uncertainty dominated
  • above about 200 GeV ET
  • Set new limit on ?cgt1.4 TeV
  • CDF also measured jet cross section for different
    cone sizes and looked at Jet shapes for 100 GeV
  • Interplay between data and theory!

Jet cross section dep. on cone size
  • Jet cross section for
  • cone sizes 0.4, 0.7, 1.0.
  • PRL 68 1104 (1992))

µ ET/2 solid µ ET short dash µET/4 long dash
  • Jet ET 100 GeV
  • Best agreement with very small scale ET/4
  • Introduce ad-hoc parameter Rsep which scales
    radius for parton merging
  • ?Rparton Rsep R
  • effectively reduces parton cone size
  • Snowmass Rsep 2

Rsep 1.3
Theory PRL 69, 3615 (1992)
Jet Shape Measurement
DataPRL 70, 713 (1993) Thy PRL 69, 3615 (1992)
Jet ET 100 GeV
  • Measure energy
  • inside subcones around jet axis

Rsep 1.3
µ ET/2 solid µ ET short dash µET/4 long dash
ET/4 give worst agreement Rsep 1.3 gives best
agreement with data
F(r) ET(r)/ET(R)
Snowmass didnt specify how to separate close
jets (not an issue with partons)
  • CDF merged close jets if 75 of smaller jet
    energy overlapped
  • otherwise separated based on distance from
  • At parton level jets are
  • separated if ?Rgt2Rcone

ET 123 GeV ? 0.23 f 170.4o
?R 0.88
ET 173 GeV ? -0.57 f 192.4o
Separation between jets in CDF data
  • In data look at separation between leading 3 jets
  • Plot the minimum separation between the two
    closest clusters
  • 50 separated at 1.3 R
  • 100 separated at 1.6R

Rsep of 1.3 makes sense! Explains better match
between data and theory
(divided by R)
Effect of Rsep on NLO 2?2 Inclusive Jet Cross
Section Predictions
  • Cross section for Rsep 2 is larger than for Rsep
    1.3 by flat 5
  • Lessons
  • Inc. cross section is not very sensitive to Rsep,
    but more detailed comparisons pointed out
    difference between analysis of data and theory
  • Details of clustering algorithms are important
    for precise comparisons between data an theory

More implications of NLO Phase space
  • The Parton momentum fractions at NLO are

ET 50 GeV vs 1.8 TeV
where ET1 gt ET2gtET3 etc.
  • Since ET2 can now be lt ET1,
  • ?2 can increase compared to LO
  • Adding more partons (e.g.NNLO)
  • further increases allowed range
  • Still have sharp cutoff on ?1
  • ?2 can be bigger than ?1

Compare LO and NLO predictions
K factor NLO/LO 10 for ?lt1.5, away from
PS boundaries Large corrections for large
?2 ?stay away from there, theory not
reliable at LO or NLO
Scale dependence
  • where L log(µR/ET) and bi are the beta functions

NNLO coefficient C is unknown. Curves show
guesses C0 (solid) CB2/A (dashed) Dependence
on choice of scale is reduced as higher orders
are included
Usual range
d?/dET at ET 100 GeV
µR /ET
Another digression on the scale
  • Addition of NLO terms reduced dependence of
    prediction on scale when choice ranged from ET/4
    to 2ET
  • But, since ET1 and ET2 are no longer required to
    be equal we now have to think about which ET
    should be used for the scale
  • µ ? ET of each jet in the event
  • Many scales per event
  • Cross section is proportional to as(ET)n, can
    extract as from inc. xsec.
  • µ ? ET1 Maximum Jet ET in the event
  • one scale per event
  • can implement in event generator (JETRAD does
  • Can write the theory both ways Two programs used
    by CDF and D0
  • EKS analytic NLO program uses µ ? ET
  • JETRAD event generator uses µ ? ETMAX

Effect of Scale on NLO 2?2 Inclusive Jet Cross
Section Predictions
CDF Run 1A Inclusive Cross Section (1996)
  • Excess observed above 200GeV
  • In 1996 all PDFs gave roughly same shape
  • Motivated discussions of new physics as well and
    PDF uncertainties

PDF uncertainties 2000
Ratio of inclusive jet cross section for
different PDFs compared to CTEQ4M
  • Turns out PDFs are very flexible, even at high ET
  • 30 changes in shape are OK
  • Pretty much squelched discussions of new physics
  • Ended 15 year history of using Inc. cross
    section for compositeness search.
  • Need more constraints on PDFs!!

Alternate Variables Mass and Angle
  • can write cross section in terms of dijet mass
    M12 and the center of mass scattering angle ?

M122 4ET2cosh2? cos ? tanh ? t - (1-cos
? )s/2
  • Typically measure
  • dijet mass spectrum d?/dMJJ
  • by integrating over a fixed angular range
  • angular distibution d?/dcos?
  • for intervals of dijet mass

Angular Distribution Not sensitive to PDFS
  • Dominant subprocesses have similar shape for
    angular distribution d?/dcos? with different
  • Can use to test for compositeness with smaller
    theoretical uncertainties
  • Measure angular distribution directly
  • Measure dijet mass in different angular regions
  • take ratios to cancel PDF uncertainties

Angular Distribution and quark substructure
QCD is dominated by 1/(1-cos ?)2 Contact
terms by 1/(1cos ?)2 Difference in forward
? region is hard to measure
  • Change to a better angular variable

Much more sensitive to contact term
large difference from QCD in central region
Limits on Quark Substructure
D0 Run IB results
Limits on Quark Substructure
Inclusive Jet Cross Section Run Ib
  • CDF Results
  • 0.1lt?lt0.7

Data and Predictions span 7 orders of magnitude!
Inclusive cross section in detail (linear scale)
CDF Run 1B data
  • Good agreement with data over most of ET range
    for CTEQ4HJ predictions
  • But note CTEQ4HJ was fit to CDF Run 1a data!
  • Still need more constraints!
  • See Talk by Walter Giele next week!

? dependence of inclusive cross section
  • D0 result
  • Solid CTEQ4HJ
  • Open CTEQ4M
  • NLO QCD predictions (JETRAD) provide good
    description of data.
  • Agreement gets a little worse as go to higher ?

CDF and D0 Comparison
  • CDF and D0 see fantastic agreement in 0.1lt?lt0.7
  • Note, this is corrected for the different
    luminosity cross sections used at the time of the

Inclusive cross section and as
d?/dET ?s(µR )2A ?s(µR )3(B
2b0LA) ?s(µR )4(C 3b0LB
(3b02L2 2b1L)A)
  • Use inclusive jet cross section data and NLO
    theory to extract as (only possible if use µR
  • Clearly observe running of as over a wide range
    of Jet ET
  • ? ?s(Mz) 0.1178 .0001(stat.) .0081 -.0095
    (exp. sys), Thy unc. 5 PDFs, 5 scale

END Day 1
  • Basic theoretical and experimental ingredients
    for high ET Jet studies at hadron colliders
  • A little history of high ET jet measurements
  • Interplay of data and theory
  • Sample of the highest ET results from CDF and D0
  • Tomorrow More detailed look at Jets and Jet
  • A few more high ET jet measurements
  • Multi- jet events
  • Double parton scattering
  • Underlying event
  • KT clustering algorithm
  • Structure within jets

Production and Evolution of High ET Jets Day 2
  • Yesterday we looked at events and discussed
    comparing data to LO and NLO predictions for 2? 2
    scattering (even though we saw events with many
  • NLO 2?2 scattering
  • 2 or 3 partons are produced from the collision
    of one parton in each of the incoming hadrons
  • Initial partons have a fraction of proton
    longitudinal momentum and small pT 0
  • Each outgoing parton forms a jet or 2 partons
  • combine into one jet
  • Data and Theory are in pretty good agreement
    over large ET range (20-500 GeV) where cross
    section falls by 7 orders of magnitude!

Production and Evolution of High ET Jets Day 2
  • Today will describe a more complex (realistic?)
    model for the data
  • Cover some of the details that were glossed over
    on Day 1
  • Inclusive cross sections at different CM energies
  • Multi jet measurements
  • Double parton scattering
  • Underlying Event
  • Clustering algorithms
  • Structure within jets

Inclusive Cross sections at different CM
Scaled Cross Section
  • Can rewrite inclusive jet cross section in terms
    of dimensionless quantity xT
  • Scaling means predictions are independent of vs
  • QCD does not scale due to dependence of
    strong coupling
  • constant and parton momentum distributions
    on the factorization
  • and renormalization scales ?R and ?F
  • In ratio of cross sections many
    uncertainties, both theoretical and
  • experimental will cancel

Ratio of scaled cross sections?s 630 GeV / ?s
1800 GeV
xT 2ET/?s
Shape of CDF and D0 Data and Theory agree above
xT 0.15,
Ratio of cross sections vs 630/vs1800
  • Uncertainty from PDFs cancels in ratio!
  • Normalization of NLO predictions do not match
  • Open issue no good explanation

Reality (closer) of proton- antiproton collision
  • Initial state radiation (ISR) incoming parton
    emits a gluon extra jets, PT? 0
  • Final state radiation (FSR) outgoing parton
    emits a gluon - extra jets
  • Remnants of proton and antiproton interact
    producing low ET particles (Underlying Event)
  • Can have collisions between more than one
    proton-antiproton pair ?Multiple interactions,
    can see multiple verticies in the detector
  • Can have collisions between more than one parton
    within each incoming proton or
  • antiproton ? double parton interactions

Event Generators
  • Monte Carlo programs such as HERWIG, ISAJET, and
    PYTHIA are used today to reproduce all aspects of
    the events
  • All based on LO matrix elements Leading Log
  • Include the effects of Initial and Final State
  • Different parton shower models are used by the
    different programs
  • primary goal is to generate the shower of partons
    near the scattered parton direction.
  • also includes some wide angle radiation which
    could produce additional jets.
  • Hadronization model to covert colored partons to
    colorless hadrons
  • Parton shower and hadronization parameters can be
    (are) adjusted to give good agreement with data.
  • Underlying event
  • assumed to be similar to Minimum Bias events in
    number of particles produced and their PT
  • empirical and parameters can be tuned to give
    agreement with the data
  • Output of these programs is a list of particles
    (mostly hadrons) which can be fed into a detector

Fragmentation models
  • Independent Fragmentation (Feynman-Field) Used
    in ISAJET and others
  • each parton fragments independently
  • scattered partons shower independently
  • resulting partons are converted into hadrons
  • can trace every particle back to original
    scattered parton
  • can tune every aspect to give agreement with
  • String Fragmentation Used in PTHYIA and others
  • separate partons are connected by color strings
    with uniform energy/unit length
  • Cluster Fragmentation Used by HERWIG and others
  • Pairs of color color connected neighboring
    partons are combined into color signlets.
  • Cluster and String models have more physics and
    less tunable parameters (see talk by Mrenna)

Correcting the data
  • Generators are essential for correcting the
    measured data
  • energy radiated outside the cluster or cone
  • underlying event energy that sneaks into the
    cluster or cone
  • feed detector simulations to study detector
  • Try minimize dependence of corrections on MC
    model by tuning parameters to data and by using
    data where ever possible.
  • to minimize parton shower/hadronization
    differences we usually correct back to particle
  • cluster algorithm is run on generated particles
  • derive corrections from difference between energy
    measured in the detector and the particle
  • Then we compare corrected data to LO or NLO
    parton level predictions
  • ? Corrections depend on what you are
    comparing to!!
  • for comparisons to LO an out-of-cone correction
    is needed
  • for NLO no need for out-of-cone, NLO predictions
    can throw energy out of the cones.
  • Can also compare raw data to fully simulated
  • disadvantage is that for any new prediction you
    need to resurrect and run the full simulation
    (generator detector simulation)
  • These MC models also used in other measurements
    (e.g. top mass, Higgs search, etc) to derive
    corrections and uncertainties.

Multijet events High ET radiation
  • CDF and D0 have studied event topologies up to 8
  • Many kinematic variables examples
  • ?3 scattering angle of 3rd jet
  • ?3 angle between 3-jet plane and plane
    containing lead jet and the beam
  • Compare to QCD Generator Detector simulation
  • HERWIG - 2?2 matrix elements parton shower
  • NJETs leading order 2 ? N matrix elements, N
    2,...5, N6 uses approximation, ?R partons gt 0.9
  • Phase space match mNj and mj/mNj to HERWIG

6-Jet events
Multijet events (3 jets)
  • Angular distributions for 3-jet events (CDF)
  • Phase space is uniform ? most different from
    data at edges!
  • NJETs and HERWIG both pretty close to Data

?3 scattering angle of 3rd jet
angle between 3-jet plane and plane containing
lead jet and the beam.
Angular Distributions for 6-Jet events
  • Successively combine lowest mass jet pairs to
    form 3-jet-like event
  • plot the same angular variables
  • Phase space is uniform ? divergences at edges
    are even
  • more pronounced than in 3-jet case
  • NJETs and HERWIG both pretty close to Data
  • NJETS is closer to data at edges
  • Amazing that HERWIG can reproduce 6-jet events at

Double Parton Scattering
  • Two partons in each incoming hadron have a hard

m2 (1) if A and B are (in) distinguishable ?eff
process independent contains information
on spatial distribution of partons inside the
proton Uniform large ?eff Lumpy small ?eff
Uniform hard sphere ?eff 11 mb
Double Parton Scattering History
  • Search in 4-jet samples for pairs of uncorrelated
    dijet events (m1)
  • AFS ?eff 5mb Z.Phys. C34, 163 (1987)
  • UA2 ?eff gt 8.3 mb PLB268, 145(1991)
  • CDF ?eff 12.1 10.2 -5.4 mb PRD68, 4857
  • hard sphere prediction protons are spherical
    and have uniform parton density ?eff 11mb
  • CDF measurement with Run 1a photon 3 jet data
    (16 pb-1)
  • PRD 56, 3811 (1997), PRL 79, 584 (1997)
  • Isolated sample of events with 53 with double
    parton scattering events
  • Used low ET jets to maximize cross sections
  • Extracted result without relying on MC

Double Parton Scattering Photon 3 jets
  • Look for events with a photon jet event plus an
    uncorrelated dijet event
  • sensitive variable is angle between
  • photon-jet and jet-jet pair
  • Photon ET gt 16 GeV
  • Jet ETgt5 GeV
  • ET2 , ET3 lt 7 GeV
  • ?R between photon and jets gt 0.8
  • 16853 events with one vertex
  • 5983 events with two pp interactions
    (2 vertex)
  • generated uncorrelated DP models from data
  • used 2-vertex data sample
  • photon 1 jet 2-jet event (MIXDP)

Double Parton Scattering
  • Find pairing that minimizes PT imbalance

Measure angle between the pairs ?S Single
parton (SP) scattering peaks at p Double parton
(DP) scattering is flat (uncorrelated to
photon) Fit Data to mixture of SP and DP
Data is 52.6 2.5 0.9 DP! No evidence for
correlations between the two scatters ?eff 14.5
1.7 1.7 2.3 mb
Look for correlations in x
  • Enrich sample
  • ?S gt 1.2 ? 90 DP
  • Compare data to
  • model (no correlations)
  • Data and model agree ?
  • No observable correlations!

Reality (closer) of proton- antiproton collision
  • Talked about
  • production of extra jets (Initial and Final
    state radiation)
  • Double parton interactions shown that they
    definately exist and rate is consistant with hard
    uniform sphere
  • Multiple proton-antiproton collisions are
    identified in trackign chambers by two or more
  • Now the Underlying Event or remnants of proton
    and antiproton collision

Underlying Event data
  • Typically jet data is corrected for underlying
    event based on estimates from the data
  • Jet Data
  • Measure energy in cones located at ?? 90o from
    leading jet.
  • plot energy of Min. and Max. energy separately.
  • Observe (and expected) energy
  • in higher ET cone is affected by radiation
    from other jets jets are rarely exactly 180 o
  • Pretty good agreement with HERWIG for min. Cone
  • Data is higher from Max cone.

Min. Cone
Underlying Event Minimum Bias data
  • Minimum Bias Data
  • triggered on hits in forward and backward
  • events usually have one vertex and low ET
  • no obviously discernable jet structure
  • Min. Bias Data is result of soft collision
    between proton and antiproton
  • Should be similar to interactions of remnants
    from a hard collision
  • Note no sharp cut offs Jets dont suddenly
    appear at some threshold.
  • We cant see very low ET jets because particles
    spread out.
  • CDF measured energy in cones placed randomly in
    minimum bias data
  • ? found same energy as in minimum cone
    analysis of Jet data
  • (2.2 GeV)
  • Note must be careful to correct for additional
    interactions MB data had an average of 1.05
    int., Jet data had an average of 2.1
  • Take a large uncertainty (30 ) on Underlying
    event energy corrections because it is not well
    defined theoretically

Underlying Event Models
  • The underlying event in a hard scattering process
    has a hard component (particles that arise from
    initial final-state radiation and from the
    outgoing hard scattered partons) and a soft
    component (beam-beam remnants).
  • However the soft component is color connected
    to the hard component so this separation is (at
    best) an approximation.
  • For ISAJET (no color flow) the soft and hard
    components are completely independent and the
    model for the beam-beam remnant component is the
    same as for min-bias but with a larger ltPTgt.
  • HERWIG breaks the color connection with a soft
    q-qbar pair and then models the beam-beam remnant
    component the same as HERWIG min-bias (cluster

Underlying Event Multiple Parton Interactions
  • PYTHIA models the soft component of the
    underlying event with color string fragmentation,
    but in addition includes a contribution arising
    from multiple parton interactions (MPI) in which
    one interaction is hard and the other is
  • The probability that a hard scattering events
    also contains a semi-hard multiple parton
    interaction can be varied but adjusting the
    cut-off for the MPI.
  • One can also adjust whether the probability of a
    MPI depends on the PT of the hard scattering,
    PT(hard) (constant cross section or varying with
    impact parameter).
  • One can adjust the color connections and flavor
    of the MPI (singlet or nearest neighbor, q-qbar
    or glue-glue).
  • Also, one can adjust how the probability of a MPI
    depends on PT(hard) (single or double Gaussian
    matter distribution).

Charged particle distributions in data
Underlying Event plateau
  • Define Df lt 60o as Toward, 60o lt Df lt 120o
    as Transverse,
  • and Df gt 120o as Away.
  • All three regions have the same size in h-f
    space, DhxDf 2x120o 4p/3
  • Plot the average number of charged particles (PT
    gt 0.5 GeV, h lt 1, including jet1) vs Jet1 PT
  • The solid (open) points are the Min-Bias (JET20)
    data. Smooth connection!

Transverse PT distributions
  • Plot the PT distribution of the Transverse
    ltNchggt, dNchg/dPT.
  • for different jet PT
  • The integral of dNchg/dPT is the Transverse
  • The triangle and circle (square) points are the
    Min-Bias (JET20) data.

Transverse ltNchggt vs PTJet1
Isajet 7.32
Pythia 6.115
Herwig 5.9
  • Compare data to the the QCD hard scattering
    predictions of HERWIG 5.9, ISAJET 7.32, and
    PYTHIA 6.115 (default parameters with PT(hard)gt3
  • Tracking eff. has been included in MC predictions

ISAJET Transverse Nchg versus PT(jet1)
ISAJET total
Outgoing jets Initial and Final State Radiation
Beam-Beam Remnants
  • ISAJET 7.32 (default parameters with PT(hard)gt3
    GeV/c) .
  • ISAJET has two categories that contribute to
    transverse region
  • charged particles that arise from the break-up of
    the beam and target (beam-beam remnants)
  • charged particles that arise from the outgoing
    jet plus initial and final-state radiation (hard
    scattering component).

HERWIG Transverse Nchg versus PT1
Beam-Beam Remnants
Outgoing Jets plus Initial Final-State Radiatio
  • HERWIG 5.9 (default parameters with PT(hard)gt3
  • HERWIG has two categories
  • charged particles that arise from the break-up of
    the beam and target (beam-beam remnants)
  • charged particles that arise from the outgoing
    jet plus initial and final-state radiation (hard
    scattering component).

PYTHIA Transverse Nchg versus PT1
Outgoing Jets plus Initial Final-State Radiatio
Beam-Beam Remnants plus Multiple Parton
  • PYTHIA 6.115 (default parameters with PT(hard)gt3
  • PYTHIA particles are divided into two categories
  • charged particles that arise from the break-up of
    the beam target (beam-beam remnants including
    multiple parton interactions)
  • charged particles that arise from the outgoing
    jet plus initial and final-state radiation (hard
    scattering component).

Compare Hard Scattering Components
  • HERWIG and PYTHIA modify the leading-log picture
    to include color coherence effects
  • leads to angle ordering within the parton
  • Angle ordering produces less high PT radiation
    within a parton shower. (See talk by S. Mrenna)

ISAJET TransversePT Distribution
PT(charged jet1) gt 30 GeV/c Transverse ltNchggt
PT(charged jet1) gt 5 GeV/c Transverse ltNchggt
  • Look at PT distribution for jets with ETgt 5 and
    30 GeV

ISAJET Transverse PT Distribution
  • Dashed curve is the beam-beam remnant component
    and the solid curve is the total (beam-beam
    remnants plus hard component).

HERWIG Transverse PT Distribution
PT(charged jet1) gt 30 GeV/c Transverse ltNchggt
PT(charged jet1) gt 5 GeV/c Transverse ltNchggt
HERWIG TransversePT Distribution
  • The dashed curve is the beam-beam remnant
    component and the solid curve is the total
    (beam-beam remnants plus hard component).

PYTHIA Transverse PT Distribution
Includes Multiple Parton Interactions
PT(charged jet1) gt 30 GeV/c Transverse ltNchggt
PT(charged jet1) gt 5 GeV/c Transverse ltNchggt
Can vary the parameters for Multiple interactions
assumes a varying impact parameter and a
hadronic matter overlap consistent with a
single or double Gaussian matter distribution,
with a smooth turn-off PT0PARP(82)
PYTHIA Multiple Parton Interactions
Vary impact parameter Tune to data
Note Multiple parton interactions depend on the
Tuned PYTHIA Transverse PT Distribution
Includes Multiple Parton Interactions
PT(charged jet1) gt 30 GeV/c Transverse ltNchggt
PT(charged jet1) gt 5 GeV/c Transverse ltNchggt
  • Tuned PYTHIA CTEQ4L, MSTP(82)4 (hard core),
    PT0PARP(82)2.4 GeV/c.

Tuned PYTHIA Transverse PT Distribution
Includes Multiple Parton Interactions
  • PYTHIA 6.115 with PT(hard) gt 0, CTEQ4L,
    MSTP(82)4, PT0PARP(82)2.4 GeV/c.
  • The dashed curve is the beam-beam remnant
    component and the solid curve is the total
    (beam-beam remnants plus hard component).

The Underlying Event Summary Conclusions
  • ISAJET (FF) produces too many (soft) particles
    and the wrong dependence on PT1.
  • HERWIG and PYTHIA (modified LLA) do a better job
    describing the underlying event.
  • ISAJET and HERWIG do not have enough beam-beam
    remnants with PT gt 0.5 GeV/c.
  • PYTHIA (with multiple parton interactions) has
    best description of the underlying event.
  • Recently an underlying event that depends on
    multiple parton interactions was included in
  • Multiple parton interactions gives a natural way
    of explaining the underlying event in a hard
    scattering, and have been observed in photon
    jet data
  • Warning to Top-mass type studies
  • Multiple parton interactions are very sensitive
    to the parton structure functions. You must
    first decide on a particular PDF and then tune
    the multiple parton interactions to fit the data

Fragmentation models and Clustering
  • Independent Fragmentation (ISAJET)
  • each parton fragments independently
  • simple to trace parentage of hadrons
  • doesnt describe data very well
  • Cluster Fragmentation (HERWIG)
  • Pairs of color color connected neighboring
    partons are combined into color singlets.
  • Cant trace parentage of hadrons back to original
  • Gives generally good agreement with data
  • Clustering
  • imposing a cone algorithm conceptually implies
    independent fragmentation
  • Cluster fragmentation suggests imposing a cone
    will be artificially cutting color lines
  • Successive recombination algorithms (e.g. KT)
    maybe more natural
  • Difficulty with KT algorithms is derivation of
    corrections for variable size jets ? Recent D0

Jet Algorithms NLO, NNLO considerations
  • Jet algorithm should be insensitive to
  • infrared and collinear divergences
  • hadronization
  • logitudinal boosts

Infrared problem adding an infinately soft
parton should not change the number of jets
Collinear problem replacing any parton with a
collinear pair of partons should not change the
number of jets
Note The calorimeter towers the
preclustering (grouping) of towers in a
detector integrate over these effects in the data
Cone Algorithm is Not IR safe at NNLO KT is safe
at all orders
KT algorithm at Hadron Colliders
  • Successively associate pairs of particles
  • dij min(PTi2,PTj2) ?Rij2/D2
  • where ?Rij2 (?i ?j)2 (fi fj)2
  • and for each particle define di PTi2

Uses one parameter D ? minimum separation
between final jets For D1 and Rijltlt1 dij
relative pT (KT)
Find minimum of di and dij ? dmin If dmin
dij ? merge particles If dmin di ? remove i
from particle list and add to jet list Keep going
until all particles are assigned to a
jet. Result list of jets with separation between
them D

Note all particles in a cone of radius R around
the centroid are not necessarily included in the
KT jet and particles far from the centroid can
be included.
KT Algorithm
  • soft and collinear particles are merged first
  • Final jets separation gt D
  • D is the only parameter (cone algo has Cone
    Radius and Rsep)
  • KT algo is IR safe to all orders
  • At LO KT cone (1parton/jet)
  • At NLO D 1 gives same result as R0.7, Rsep1.3
  • (Ellis-Soper PRD 48, 3160)
  • At higher orders this relationship might not

Inclusive Jet Cross Section with KT Algo.
D0 KT papers hep-ex/0108054 (PRD) and
hep-ex/0109041 (PRL)
KT Algorithm ? Cone in DATA
  • Cross sections are different at low PT
  • Match leading two jets in ?-f (?Rlt0.2)
  • plot PTKT ETcone vs PT

KT jets are more energetic 7 ( 4GeV) at 60
GeV 3 (6 GeV) at 200 GeV
If shift the cone cross section by this measured
difference then the cross sections agree
Compare KT and Cone jets with HERWIG
  • Generate Jet events with HERWIG down to particles
  • Run KT and Cone algos on particles
  • match the two leading clusters in ?-f (?Rlt0.2)
    and plot the difference

HERWIG shows KT algo picks up more energy than
cone Level is smaller than in data 2 (1) at
60(200)GeV HERWIG flat 2 GeV Data 4 - 6 GeV
Overall uncertainty is 2 on energy scale so
these agree at 2?
KT and Cone Jets look inside HERWIG Jets
  • Look at distance to furthest particle from jet
  • KT jets have more particles far from centroid
  • Cone also has particles outside radius due to
    merged jets but at a lower level than KT jets

Number of particles in jet is 30 larger for KT
KT and cone jets are different!
Quantify effect of hadronization
  • Generate HERWIG jets
  • Compare KT and Cone algos at parton level and
    after hadronization particle level for two
    leading jets
  • KT jets pick up more energy than in parton level
    by including partons far from the original
  • cone jets lose energy outside the cone

Add the HERWIG hadronization effect to the NLO
predictions ? Difference between data and theory
at low pT is reduced ? Remaining difference is
large ? More interplay between data and theory is
Quark and Gluon Jets with the KT algorithm
  • Quarks and gluons radiate proportional to their
    color factors
  • Expect gluon jets to be broader than quark jets
  • Gluon jets should have softer fragmentation,
  • (more low energy particles)

Separation of quark and gluon jets
  • LEP extensive studies of quark-gluon separation
    (Bill Garys talk)
  • At Fermilab we can compare the samples from
    different CM energies

For the ET range of 50-60 GeV, HERWIG predicts a
gluon jet fraction of 66 vs 1800 GeV
and 47 vs 630 GeV
Quark Gluon separation (D0 analysis)
  • use the KT algorithm to look for subjet
  • inside the jets
  • dij min(pTi2,pTj2) ?Rij2/D2 gt ycutpTjet2
  • For ycut 1, Nsubjet 1
  • For ycut ? 0 Nsubjet ? 8
  • Count the number of subjets and compare to
  • Chose fixed ycut 0.001
  • This corresponds to minimum of 3 of total jet pT
    in a subjet

Quark Gluon separation and subjets
  • Plot the number of jets of multiplicity M
    normalized by the total number of jets for
    different subjet multiplicities at CM 1800 and
    630 GeV
  • The subjet multiplicity M in a sample is a
    combination of the multiplicities of quark ( Mq)
    and gluon (Mg) jets
  • M fMg (1-f)Mq
  • where f is the fraction of gluon jets and (1-f)
    is the fraction of quark jets

For two samples with different fractions Mq
f1800M630 f630M1800/(f1800-f630) Mg
(1-f630)M1800- (1-f1800)M630 /(f1800-f630)
Quark Gluon separation
Compare Subjet Multiplicity to Predictions
  • HERWIG is in great agreement with data.
  • ? ask Steve Mrenna
  • to explain how HERWIG can do so well!
  • Analytic resummed calculation predicts higher
    multiplicies in gluon jets
  • Smaller effect in quark jets

QCD in Run II
  • Run I
  • 20 events with ETgt 400 GeV
  • Run II
  • 1K events ETgt 400 GeV
  • 100 Events ETgt 490 GeV
  • Great reach in high x and Q2
  • search for new physics
  • test QCD predictions in new regions

Jet ET
  • Covered a wide variety of topics related to
    production and evolution of high energy jets
  • Inclusive jet cross sections
  • Multijet production
  • Double parton scattering
  • Underlying event
  • Cone and KT clustering algorithms
  • Separation of quark and gluon jets
  • Set stage for upcoming talks
  • What is in the theory and the event generators
    and how well they agree with data
  • More details on generators from Steve Mrenna
  • Walter Giele will talk about how to derive new
  • Keep in mind some of these issues when you hear
    talks on searches for new physics, the HIGGS,
    precision top mass etc.
  • Main message Experimental and Theoretical
    understanding progress together
  • Run II has new CM energy (1.96 TeV) and lots of
    new data!
Write a Comment
User Comments (0)