Timing for pileup mitigation in forward jets (&...
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Timing for pileup mitigation in forward jets (& more) F. Rubbo, A. Schwartzman, 9/4/2015 1
Transcript of Timing for pileup mitigation in forward jets (&...
Timing for pileup mitigation in forward jets (& more)
F. Rubbo, A. Schwartzman, 9/4/2015
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Status
• Recap: • Developed and characterized timing algorithms for pileup
mitigation exploiting features of LHC pileup-leveling with crab-cavities.
• INT Note (work in progress) and last talk at Upgrade Physics meeting.
• Today’s result: • Investigating timing algorithms independent of collision
configuration. • Applications:
• pileup/hard-scatter jet tagging • selection of VBF topologies.
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Geometry and event simulation
η=0 η=2.5
η1zHS
z0=3.5 m
t1 = tHS+d1/v1
d1 = (z0-zHS)/tanh(η1)
Simulated as disk at z=3.5 m with |η| coverage [2.5,4.3].
absolute time
zPU
t2 = tPU+d2/v2
• Timing detector: disk at z=3.5 m with |η| coverage [2.5,4.3].
• Pythia simulation of signal overlapping with 200 pileup vertices, keeping the full particle record.
• Run jet finding (fastjet) on the HS event only (HS “truth” jets) and on the full (signal+pileup) event record (“reco” jets).
• Apply jet area subtraction.
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Space-time degeneracy of collisions
z0
Run 1-2 bunch configuration:
Space-time PU interaction probability density is degenerate for head-on collisions.
z vertex [m]
ct v
erte
x [m
]
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Timing as discriminant
The inclusive particle time distribution for head-on collisions provides little discrimination power between HS and PU.
Two approaches:
• Remove time-space degeneracy of the interaction region with LHC crab cavities.
• Exploit jet and topology features to extract discriminating information (this talk).
• The crab-kissing configuration (ψ=5) squeezes the time component of the interaction region while keeping the same spatial spread. Pseudo-rectangular bunches flatten the spatial distributions, reducing the pileup density.
head-on collisions
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Crab cavities for pileup leveling
crab-kissing
ct v
erte
x [m
]
ct v
erte
x [m
]
z vertex [m]z vertex [m]
0.0 0.2 0.4 0.6 0.8 1.0
Efficiency
0.0
0.2
0.4
0.6
0.8
1.0
Fake
Rat
e
No DiscriminationPseudo-RectangularGaussian
Timing as discriminant (w/ CK)
• The CK configuration allows using directly timing for jet pileup mitigation (HS jets: |time|<threshold).
• Relies on LHC upgrade and bunch crossing configuration.
head-on collision - ψ=0 crab-kissing - ψ=5 7
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Jet timing substructure
Time density
• The hard-scatter timing (corrected for zPV and η) is the same for all hard-scatter particles, within resolution.
• Look for timing “clusters”!
R=0.1
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Time density
• HS jets have a large number of HS time measurements while PU time measurements are evenly distributed.
• PU time measurements in (stochastic) PU jets are evenly distributed.
HS jet PU jet
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Density difference
Build a HS vs PU discriminant: • Find timing clusters with gaussian kernel density estimation. • Order cluster by decreasing density. • Δd = density[0] - density[1]
Δd
Δd 11
0.0 0.2 0.4 0.6 0.8 1.0
Efficiency for hard-scatter jets
0.0
0.2
0.4
0.6
0.8
1.0
Effi
cien
cyfo
rpile
-up
jets
ps = 14 TeV, µ = 200
Pythia8 dijetspT > 20 GeV
�t=0 ps�t=10 ps�t=20 ps�t=30 ps
Density difference - performance
• rejection ~5 @80% efficiency for σt=0 ps • performance quickly degrades with resolution. • encouraging first results indicating timing-based PU.
suppression w/o crab-kissing is possible.
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Δd > threshold
Possible improvements
• Use pT measurement (from multiple layers?) to enhance density of HS time measurement.
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• Improve discriminant definition: • e.g. use median
density instead of second peak to define baseline.
• Combine with CK.
• New ideas..?
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VBF tagging
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VBF-like selection
For VBF-like topologies, want to select forward and backward HS jets.
Double tag Require both forward and
backward HS jets
Event tag Identify forward-
backward jet events compatible with VBF topology
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VBF-like selection
HS-HS
HS-PU (stochastic)
PU-PU
PU-PU (same vertex)
Tagging individual jet:
• HS-HS efficiency drops as εHS2
• High HS-PU rate as εHS*εPU
• PU-PU rate strongly suppressed as εPU*εPU
• QCD pileup jets have higher εPU because more similar to HS jets. Subdominant at high µ and low pT.
z
VBF signal
VBF background
zPV
Double tag
• The efficiencies of identifying each jets are uncorrelated • VBF signal efficiency is quadratic —> Requires very high
single tag efficiency —> High PU rate. • N.B. same applies for a track-based tagger.
0.0 0.2 0.4 0.6 0.8 1.0
Efficiency for hard-scatter jets
0.0
0.2
0.4
0.6
0.8
1.0
Effi
cien
cyfo
rpile
-up
jets
ps = 14 TeV, µ = 200
Pythia8 dijetspT > 20 GeV
�t=0 ps�t=10 ps�t=20 ps�t=30 ps
0.0 0.2 0.4 0.6 0.8 1.0
Signal efficiency
0.0
0.2
0.4
0.6
0.8
1.0
Bac
kgro
und
effic
ienc
y
ps = 14 TeV, µ = 200
Pythia8 VBF inv. Hjet pT > 20 GeV
�t=0 ps�t=10 ps�t=20 ps�t=30 ps
2X
single jet tagging
double jet tagging
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Event tag
η=0 η=2.5η=-2.5
η1η2
zPV
z0
t1 = tPV+d1/v1
t2 = tPV+d2/v2
d2 = (z0+zPV)/tanh(η2)d1 = (z0-zPV)/tanh(η1)
tPV = t1-(z0-zPV)*cotanh(η1)/v2 = t2-(z0+zPV)*cotanh(η2)/v2
Use forward-backward timing measurements to identify jets from the same interaction.
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Forward-backward time difference
• Select events with the two leading jets at opposite η (|η|>2.5). • Use kernel density estimation to extract absolute timing of
each jet. • Given zPV, compute Δt = tPV1-tPV2.
• Tails in HS-HS due to
• relativistic approximation: not all time measurements correspond to particles with v=c. pT info could help.
• Using jet η as particle η. Room for improvement by tweaking density-based time algorithm.
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Performance
0.0 0.2 0.4 0.6 0.8 1.0
Signal efficiency
0.0
0.2
0.4
0.6
0.8
1.0
Bac
kgro
und
effic
ienc
y
ps = 14 TeV, µ = 200
Pythia8 VBF inv. Hjet pT > 20 GeV
�t=0 ps�t=10 ps�t=20 ps�t=30 ps
Excellent performance at low efficiency with mild degradation from time resolution. Kink at εs~0.6 due to double gaussian shape of signal Δt distribution (room for improvement).
Event tagging
VBF Signal efficiency
potential improvement
from removing Δt tails for HS-HS.
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Performance
0.0 0.2 0.4 0.6 0.8 1.0
Signal efficiency
0.0
0.2
0.4
0.6
0.8
1.0
Bac
kgro
und
effic
ienc
y
ps = 14 TeV, µ = 200
Pythia8 VBF inv. Hjet pT > 20 GeV
�t=0 ps�t=10 psEvent tagDouble tag
Significant improvement wrt double-tag algorithm.
VBF Signal efficiency
improvement
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Conclusions…
• Use of timing for pileup mitigation is challenging. Studied two approaches:
• LHC crab-kissing to minimize time spread of collisions. • Advanced timing algorithms exploiting jet and event time
structure.
• Crab-kissing enables ~10% PU rate @ 80% HS efficiency.
• New time-density-based algorithms give ~20% PU @ 80% HS efficiency.
• Independent of bunch crossing configuration! • Many handles for further optimization.
• New technique for VBF tagging based on timing of forward-backward jet pairs.
• To be implemented and tested in full VBF analysis.
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…and next steps
• Continue algorithm R&D: new (or old) ideas to be (re-)implemented to improve further performance.
• e.g. vertex identification in VBF events: same algorithm as VBF-tagging in reverse (HS-HS jets—>vertex z-position).
• Dedicated GEANT simulation for more accurate estimation of performance and R&D of detector geometry (see Ariel’s slides).
The tools are ~ready! Many interesting studies are on the way and help is welcome!
