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Low-pT Multijet Cross Sections
John Krane
Iowa State University
MC Workshop Oct. 4 2002, Fermilab
Part I: Data vs MC, interpreted as physics
Part II:Data vs MC, interpretedas a tuning problem
John Krane -- Iowa State University 2
Motivation
High-pT inclusive jet spectra appear to be well described by NLO QCDPossible exceptions include kT algorithm analysis,
possibly also the ratio of cross sections at 630/1800 GeV, large- dijets (BFKL). But only at 1 or 2 ,not actual disagreement
Originally, this was a search for BFKL effects, which could produce extra jets in low-Q2 events
John Krane -- Iowa State University 3
The Analysis
Jets with ET > 20 GeV, usual jet and event cuts,efficiencies applied but no unsmearing
Study inclusive samples of events having at least: 1-jet, 2-jets, 3-jets, 4-jets
Compare to normalized Pythia + GEANT and Herwig + GEANT, tune if necessary
The usual sample
John Krane -- Iowa State University 4
Data and Pythia
Inclusive xsec looks fine
Multijet xsecs exhibit deviations from Pythia
Let’s pretend it’s physics
points=data, histo=Pythia
John Krane -- Iowa State University 5
(D-T)/T
Solid lines: energy scale lum uncertainty
Dash: smearing uncertainty
Dotted: total error in ratio
John Krane -- Iowa State University 6
Data and Herwig
Started generating jets at 0.5 GeV
Multijet xsecs exhibit similar deviations
points=data, histo=Herwig
John Krane -- Iowa State University 7
Vector sum pT
Define The more jets in the event, the more
imbalance in energy
Could this be
ISR, with pT
lost down the
Beampipe?
2TnT2T1
2T )ppp(Q
Events > 250 are the excess in 3+ jet events
(Data and Pythia)
>150 in 4+
John Krane -- Iowa State University 8
Angles in 3-jet events
Find which jet is “the third one” by isolating the two jets with minimal pT
Many back-to-backin the data
Usually, third jet is near one of the first two, but more so in Pythia
(Data and Pythia)
John Krane -- Iowa State University 9
Angles in 3-jet events
Find which jet is “the third one” by isolating the two jets with minimal pT
Min pT not bad… Third jet is often at 90 degrees, often composed of underlying event E
(Data and Herwig)
John Krane -- Iowa State University 10
Signs point to initial state radiation effects in data– DGLAP style?
– BFKL style?
…or a need to tune the MC
Early impressions of these results
John Krane -- Iowa State University 11
“Try tuning Pythia, also compare to Herwig;see what works…”
Herwig defaults also did poorly Many iterations required Only compared to distributions shown today
(and a few other very similar ones…)
Pythia works if
PARP(83) = 0.32 (from 0.5)
Fraction of matterin the proton “core”
Herwig works if
PTMIN = 3.7 GeV
pT generation threshold
A Multiplepartonscatteringparameter
Does this changeunderlying eventin some way?
Both higher and lowervalues do worse!
Didn’t try Jimmy…
John Krane -- Iowa State University 12
Data and Tuned MC
Points = Data
Solid = Pythia
Dash = Herwig
John Krane -- Iowa State University 13
(D-T)/T
No remaining deviations from data
Is this because there were no ISR effects?
Answer lies in the validity of our tuning
John Krane -- Iowa State University 14
Vector sum pT
Tuned MC reproduced the small “shoulder”in addition to the 3+ and 4+
John Krane -- Iowa State University 15
Angles with Pythia (and Jetrad)
Points = Data
Solid = Pythia
(error bands and…)
Dash-dot = Jetrad
John Krane -- Iowa State University 16
Angles with Herwig
Points = Data
Solid = Herwig
Dot = Herwig
with cut on merged jets
Peak (from “underlying event jets”) becomes enormous if ptmin>3.7 GeV
Pythia’s CKIN(3) showsno such sensitivity…
Cross section shapes verystrange if ptmin<3.7 GeV
John Krane -- Iowa State University 17
Conclusions
Results not entirely satisfying– Would like to make definitive statements about ISR– …or provide solid tuning suggestions
Instead, we found sensitivity to several params.– Think the multiple parton scattering is constrained
by other data, we provide a new handle– We don’t understand the Herwig tuning at all
Our decision: publish the data, leave tuning to experts with a more global view
– Tuning isn’t really our forté– If we do it, we probably want a second paper out of it!
John Krane -- Iowa State University 18
Backup Slides
John Krane -- Iowa State University 19
Cone Algorithm Details (Run I)
Draw a cone around a “seed”
Calc sum ET, and ET-weighted position
Draw new cone here and recalculate sum ET, position
Reiterate until stable
John Krane -- Iowa State University 20
Energy Scale
Correction back to “the particle level”
Remove noise, underlying event,extra pp interactions
Correct for detector response
Undo misassignment of particle energies to jets
q
calorimeter jet
Tim
e
q g
parton jet
particle jet
hadrons
CH
FH
EM
p p
K
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