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20 August 2001 D0-Germany meeting
DD Goals
• Basic goal: efficient b-tagging in both high-pT (Higgs, top, SUSY) and low-pT (B) physics
• Benchmarks set in Run 2 Workshops– Higgs / Supersymmetry (’98) for high pT
• Using secondary vertex tag and assuming “nominal” Run 2 detector performance, estimated close to 60% efficiency for mistag rate below 1%
– B physics (’00) for low pT
• More difficult to give a single number (trigger, analysis details)
• Charge of the DØ b-id group:– Provide the physics groups with the algorithms and the tools to
study their results, both off-line and (where relevant) at trigger level
– Cooperate with physics groups in optimisation
20 August 2001 D0-Germany meeting
DD Tags
• Conceptually, all possibilities for tags exhausted (we think!):– Soft lepton (±, e±) tags
: Paul Balm (L3), Onne Peters• e: Abid Patwa, André Turcot (L3), Georg Steinbrück, Florian Beaudette,
Jean-François Grivaz– Secondary vertex tag
• Axel Naumann (L2), Arnaud Duperrin, Mossadek Talby, F. Villeneuve-Séguier (L3), Ariel Schwartzman, Marcel Vreeswijk
– Impact parameter tag• Jon Hays, Ian Blackler (L3), Bram Wijngaarden, Frank Filthaut, Sasha
Khanov, Flera Rizatdinova– Multivariate combinations of the above
• Pavel Demine, Strasbourg (likelihood), Andy Haas (NN), Sherry Towers (guru)
• Requires discriminating information from individual tags (rather than yes/no)
– flavour tag• No manpower yet (may come from within B physics group)• Thought this was a pure B physics issue, but it turns out other groups
also need this (e.g. t tbar distinction)
• In contrast, in Run I DØ used only its muon tags (J/ for B physics, inclusive semileptonic decays in general)!
20 August 2001 D0-Germany meeting
DD Muon tag
• L3: starting from previous L3 jet and muon “tools”– Associate muon with jet within some cone
– Calculate pTrel of muon w.r.t. jet axis to distinguish between muons
from b quarks and from ,K decays (and c quarks)• Using pT from muon chambers or central tracker? Resolution vs
probability of wrong track – muon association
– Effort not yet started (work on input L3 muons)
• Offline: – Same variable, plus: P / Ejet , DCA (significance), z (significance) +jet reco efficiency only ~ 50% for B physics
(ttbar)
20 August 2001 D0-Germany meeting
DD Electron tag
• L3: effort mainly geared towards recognising J/ – B physics as well as low-energy calibration tool– Elements in common with generic L3 electron tag: electron
recognition tools (track-CAL, track-PS, CAL-PS match)
• Studies so far (April Vert Review):
• MC-track match (R < 0.07)
• Track-CAL match: : 63 mrad (20 mrad
core) : 0.03 core but
large tails (PV position!) match in z! (changed)
• CPS-CAL match: : 29 mrad : same PV tails
• Track-CPS: : 6.1 4.5 mrad z: 10 mm
z
(2) vs z
20 August 2001 D0-Germany meeting
DD Electron tag
• L3 cont’d:– Total e± tagging efficiency ~
26%– Good for (part of) B physics
studies– What about:
• High pT?
• Semileptonic decays?• FPS?
• Offline:– Improved soft electron (E > 2
GeV/c) recognition using track extrapolation in CAL, reducing #cells taken into account
– Still need PS match to reduce fake rate!
– Variables: pTrel, pe/Ejet , Ejet,
soft electron EEM/ptrack
20 August 2001 D0-Germany meeting
DD• Example for high pT: ttbar sample pT
rel
• Example for low pT: J/ KS sample pTrel
Electron tag
20 August 2001 D0-Germany meeting
DD• Performance for high-pT Z bb sample:
– Efficiency includes b e branching ratio– Background taken from same sample
• Efficiency as fct of pT
Electron tag
No PS match PS match req
Efficiency (%) 5.2 ± 0.8 4.8 ± 0.8
Fake rate (%) 1.1 ± 0.1 0.47 ± 0.07
20 August 2001 D0-Germany meeting
DD Secondary vertex tag
• L3: fast algorithm based on Hough transform– tracks in 2D space (r, plane) hits in 2D parametric space (d, 0)
• In current implementation, start from tracks that have been found previously using a similar algorithm
• but should be possible to use “official” L3 track reconstruction
– Look for clustering in 0 coordinate, then “optimise” distance d– Problem: many PV tracks included in SV thus reconstructed (try to
distinguish using 2 fit to either PV or SV, and cut on dt)• Intrinsic to method: binning not very fine
– SV: require |d| > 1 mm, at least 3 tracks– All highly optimised for high-pT samples; 35% SV prob vs 10% PV
prob
20 August 2001 D0-Germany meeting
DD Secondary vertex tag
• Offline: can do vertex finding in 3D: Kalman filter– Start by clustering tracks (simple cone, R = 0.5)– Build up SV starting from track pairs, reject tracks associated to PV
and MB interactions; track pT and opening angle cuts
– When SV found: associate with jet within R < 0.3
– Tag: Lxy/xy > 3
– Constrained fits also track parameters improved
– Works rather well for high-pT events (also optimised for ttbar!)
20 August 2001 D0-Germany meeting
DD Secondary vertex tag
• How well do things work for B physics?– Tracking efficiency in jets as fct of
pT down to 40% from tracking alone
– Boost much smaller (<c> ~ 6 mm) PV track rejection: 24%
– After all cuts: efficiency ~ 15%
Separate B physics selection required!
Quality OK: resolution ~ 50 m (r,), 80 m (z)
20 August 2001 D0-Germany meeting
DD Impact parameter tag
• Offline: – Take collection of tracks– Select best PV based on z
coordinates– Calculate each track’s impact
parameter w.r.t. PV• Can be 2D (r- plane) or 3D • So far, studies have
concentrated on 2D
– Either cut on #tracks above given (physics-)signed i.p. significance, or multiply tracks’ PV probabilities to yield a discriminant (both possibilities implemented)
– Need to reject tracks from , K (preferably explicitly)
Z bb
Z light
ttbar(b)
ttbar(l)
2D impact parameter significance
20 August 2001 D0-Germany meeting
DD Impact parameter tag
• Copying CDF cuts:– 3 tracks with d/d > 2, or
– 2 tracks with d/d > 3
• Starting effort on 3D tags– “Real” 3D: distance
between track and PV, physics signed
– Pseudo 3D: combining separate (r,) and (s, z) information (when useful)
• Performance potentially more sensitive to luminosity
L3 effort has just started•Trying to re-use existing off- line code
20 August 2001 D0-Germany meeting
DD Multivariate tags
• Likelihood tag– Basic use: combination of independent 1D distributions
– Higher dimensionality of the problem taken into account by doing this as a function of jet , pT
– Also looking into 2D distributions
– Variables used so far: pTrel,, Lxy/xy, mSV, charged energy fraction
xx xcuds
x
jetbxpjetcxpnjetudsxpn
jetbxpL
)|( )|( )|(
)|(
P
PHxfHxp
H
H
1
)|()|(
If a value is found
otherwise
f(x|H) is distribution of variable x for hypothesis H
PH is probability to find a value for hypothesis H
NB issue of how to deal with“missing” data
20 August 2001 D0-Germany meeting
DD Multivariate tags
• Results (for Z bb vs Z light quarks)
• NN tag: using the same input, but (in principle) allows to consider full dimensionality of the problem. Started recently– Perhaps harder to understand keep also likelihood method– NB: also individual tags can use neural nets (some do already)
NB:• 0.1 < efficiency < 0.4• rejection > 0.992
20 August 2001 D0-Germany meeting
DD Common issues
• Tracking efficiency in jets– Low even for MC
• Luminosity dependence– Tracking efficiency– Vertex finding and selection
– Jet direction (for pTrel) and energy (some criteria relative to Ejet)
• Jet algorithm dependence– Cone vs. kT, algorithm parameters (so far we’ve used R=0.7
cones??)– Also: use of tracks during jet reco (instead of association
afterwards)
Cone jets kT jets
20 August 2001 D0-Germany meeting
DD• Jet algorithm dependence
– E resolution
• MC parentage– At moderate pT jet ( ~ 50 GeV/c), large fraction of b jets originates
from gluon splitting rather than lowest order production of b quarks
– Makes definition of efficiency ambiguous
• Lack of large (recent) MC samples of wide range of processes
Common issues
20 August 2001 D0-Germany meeting
DD Schedule
• Presently, largest effort into understanding / improving performance on MC– Our inputs are also continuously changing
• Takes time to find out and recover from
• About to study effect of trigger– Was difficult so far, as there was no common n-tuple with both
trigger and offline information• Should start trying to understand the quality of the data
– Muon, dimuon, and muon+jet trigger exists now– Difficult, as b-ID is at the end of the food chain
• Calorimetry, tracking, muons all need to work
• Software: n-tuple, thumbnail support• Try to study / implement as much as possible of the triggers
– Mainly muons• After shutdown (December), phase in other triggers
• As soon as possible (allowing time for commissioning)
• For our physics coordinator: first physics results by Moriond?– Is really pushing it
20 August 2001 D0-Germany meeting
DD Conclusions
• A fairly solid start has been made with b tagging• But much remains to be done
• Our group is clearly manpower-limited– Algorithm development in the DØ environment is not very efficient
• Especially if you’re “overseas”
– DØ tends to “institutionalise” responsibilities– But one person’s effort cannot be spread too thin
• Most of the people in the group are also working on other – and often more urgent – projects.
– More than enough room to accommodate new collaborators