uscms may 2002jim branson 1 e/gamma and b/tau prs (small us effort) (what you should work on when...

USCMS May 2002 Jim Branson 1

E/Gamma and b/Tau PRSE/Gamma and b/Tau PRS(small US effort)(small US effort)

(what you should work on when you finish…)(what you should work on when you finish…)

US CMS Annual Collaboration Meeting May 2002

FSU

Jin Branson


ElectronPhoton main packages*ElectronPhoton main packages*EgammaAnalysis

Modular analyzer and analysis helpersAbstract “writer” supportIteration wrapper and UserCollection support

EgammaNotificationNotification and flow control

EgammaH4SupportHbook CWN “writer”

EgammaClustersBasic clustering algorithmsPosition and energy correctionsIsolation and 0 rejection tools


ElectronPhoton main packages**ElectronPhoton main packages**ClusterTools

Endcap-specific reconstructionPreshower clusteringBrem recovery algorithms

EgammaL1ToolsLevel1 trigger candidate matching

ElectronFromPixelsPixel matching and track seeding algorithmElectron track reconstruction based on pixel seeds

EgammaMCToolsGenerator- and GEANT-level analysis

EgammaTracksTracking setup and helper classes


e/gamma Developmente/gamma Development

Working with MCWorking with MC


Basic Calorimeter Software Activities Basic Calorimeter Software Activities • Calorimeter software has been “stable” for a few years.• US is involved in upgrade program.• There are three areas of activity

– improvements of current architecture of Calorimetry• FORTRAN elimination

• using new ROU naming schema

• navigation and speedup optimization

– online/testbeam specific preparations• splitup the Readout on two parts to read the online/testbeam format

– preparations for the migration to OSCAR• isolation of what is required for hit-formatting

• first prototype of DDD usage


Island ClusteringIsland Clustering

Fast, reliable bump finding

Standalone reconstruction

Accurate position reconstruction

Log-weighed Position Correction


Depth modelingDepth modeling

•Dependence of shower max on energy ~log(E) with energy in GeV

Tmax = A[T0+log(E)]

•Parameterization for ECAL with A = 0.89 (PbO4 rad length)

•Optimize T0 by finding the zero offset for the two half barrels (optionally one could minimize position resolution)•Specific for electrons OR photons


Log weightingLog weighting

• Linear-weighted cog produces characteristic s-shape

• Rather than applying ad-hoc correction, use a log weight:

i i

ii E

EWW log0

W0 ~ smallest fractional energy to contribute to position calculation

Linear weight

Log weight W0=4.2


Position resolutionPosition resolution


Brem recoveryBrem recovery•Average brem loss (~44%) corresponds to an average thickness of 0.57 X0

•Need a brem recovery strategy in ECAL •Cluster composite ECAL objects according to some criterion– E.g. energy deposition from brem

well aligned in • Use narrow window• Collect clusters along

• Produces a SuperCluster – collection of ECAL clusters

• Removes large tails


Hybrid algorithmHybrid algorithm

• Use geometry of barrel crystals– Start from a seed crystal (as

for island)– Take a fixed domino of 3 or 5

crsytals in

– Search dynamically in

• In more detail:

– Start if Etseed>Et

hyb

– Make 1x3 domino

– If center of domino>Ewing

• Extend to 1x5

– Proceed Nstep in 5

– Remove dominoes below Ethresh

– Disconnected domino preclusters with E>Eseedare then reclustered in (producing a SuperCluster)


Optimize Hybrid PerformanceOptimize Hybrid Performance


Energy ScaleEnergy Scale•Energy is estimated by the sum of energy deposits•Emeas/Etrue gaussian+tail, peaking at <1– Incomplete containment– Unrecovered brem•Set the energy scale such that the gaussian peak falls at 1– Parameterize corrections as a

function of the number of crystals included in the cluster

– E.g. for hybrid (barrel) clusters

Electrons 10-50 GeV


Energy scale performance IEnergy scale performance I• In the barrel, with hybrid clusters:

– No Pt dependence

– Small residual dependence


Energy resolutionEnergy resolution• Effective width is defined as the half-width containing 68.3% of the

distribution• Performance on unconverted photons (using fixed window):

eff/E ~ 0.9 %


Preshower matchingPreshower matching

• Endcap SuperCluster • extrapolate components to

Preshower • search PS cluster in narrow road

around extrapolated point• correct component energy• Recalc SuperCluster energy


Pixel Matching (level “2.5”)Pixel Matching (level “2.5”)


e/e/ Level 2.5 Level 2.5


e/e/ Triggers Triggers


Pixel “tracklet”

Cluster

Electron TracksElectron Tracks

• Use “standard” tracking with pixel seeds from matching “Level 2” clusters– Fast (few tracks to

reconstruct)– In the spirit of “regional”

reconstruction

• Special e track fitter may help.


Electron Position Matching in Electron Position Matching in


Electron Rates and EfficiencyElectron Rates and Efficiency


HLT Algorithm TimingHLT Algorithm Timing• Time on (dual) 700 MHz P III

• Data access time (objectivity) excluded

• Optimization possible.


June MilestonesJune Milestones


Tracking Photon ConversionsTracking Photon Conversions

Efficiency still low due to seedsEfficiency still low due to seeds


Callibration with WCallibration with Wee


Background to Background to after standard cuts plus after standard cuts plus tracker and ecal isolationtracker and ecal isolation


Egamma/Jet AvailableEgamma/Jet Available


b/b/ (Tracker Group) (Tracker Group)• Many developers and much progress.

• US not involved (?).

• Software depends on CommonDet.


ORCA for the Tracker

•4 subsystems:

•Tracker: geometry, hit formatting, hit loading, digitization and persistency. Let’s say: everything up to the persistent digiseverything up to the persistent digis. This is the package which has to be ready for the Monte Carlo productions.

•TrackerReco: anything which has to do with reconstructed objects: RecHits and Tracks. In principle those are not persistent, even if now tracks can be written to DB.

•Vertex: same as above, but dealing with primary and secondary vertices.

•bTauAnalysis: high level objects, like b and tau taggers. They use all the above packages.

Tracker

TrackerReco

Vertex

bTauAnalysis


Tracker

•Geometry: put some detectors in the space and call it a Tracker

•Hit Formatting: cmsim flat file to Persistent DB structure

•Hit Loading: read back the last

•Digitizing: simulate the electronics attached to the sensors, and apply filters to reduce the data volume.


Geometry

The number of hits a charged track can leave is always > 10, considered enough to allow an efficient tracking and a reasonable combinatorial overhead.

Number of Si hits excluding pixelsNumber of Si hits excluding pixels


Digitization

•New and more reliable (from real tests in Karlsruhe) treatment of the Lorentz angle in silicon, as a function of bias, irradiation etc.

•Not yet implemented for pixels, where the modeling is more difficult (after irradiation, the depletion will not be complete…); wait for the optimization workshop

Code in ORCA can be adapted via configurables to any•Irradiation conditions•Temperature•V bias•Etc…

Lorentz angle very important for hit resolution:

•Silicon: tan(L) = 0.12 (~6° at 4T)

•Pixel: tan (L) = 0.53 (~28° at 4T)

Silico

n


RecHit Resolution

Versus rVersus r Versus zVersus z

Mean errorMean error

RMSRMS


Seed Generation

In this step a first approximation of a track is constructed using some supposed clean information.

You can think about different types of seeds:

•Take any two silicon/pixel layers and fit a helix with each pair of hits fulfilling some conditions

•Use the 2/3 pixel layers

•Have a seed from outside (for example muons + beam spot or calorimeters)

•Seed generation affects efficiency and timing greatly.


Available Seed Generators

•Currently available:

•CombinatorialSeedGeneratorFromPixel: the standard one

•SeedFromConsecutiveHits: takes 2 consecutive layers and uses the hits to build a seed

•SeedFromSeparatedHits: even more difficult!

•SeedGeneratorFromSimTrack: a MC based seed generator with 100% efficiency. Useful for tests.


Pixel Inefficiencies

Different staging/Lumi scenarios

L = 21033 L = 1034

Expected Inefficiencies at

1/2/10 1034


Seeding with Pixel + Silicon

Hence, work has started to produce seeds from pixels + the first layer of microstrips.

Remember that it is 20 cm away from the IP, so you expect a huge number of compatible RecHits and thus a combinatorial explosion.


Seeds from Pixel + Silicon


New Propagator

•AnalyticalPropagator: a new implementation in ORCA 6. Better protected against numerical problems, more precise and as fast as the Gtf. TO BECOME THE STANDARD SOON!!!!


Trajectory Cleaning

Since the generation of trajectories from the seeds is not one-to-one, we can in the end have two or more different trajectories sharing a great fraction of the hits and thus are not compatible.

Such ambiguities are resolved by the trajectory cleaner, which identifies mutually exclusive subsets and chooses one trajectory per subset.

It works by iterating over the input trajectories, finding for each Trajectory all the others which share more than a given number of hits with it, and then choosing the best trajectory in the set, where best is based on the chi2 of the fit.


Trajectory Smoothing

Since the trajectory building starts with a seed, typically close to the beam spot, and propagates to the outer barrel. In this way, the last fit is done when reaching the end and there all the information is available. Close to the start, where (by the way!) we are usually more interested in the track parameters, we have initial information.

A smoothing algorithm guarantees an uniform and optimal set of parameters everywhere. In this stage, no new hits are allowed, but some hits might be dropped if found not compatible wrt to the full information.


Performances

No 2-pixels!


Track Parameter ResolutionTrack Parameter Resolution


OFFLINE

HLT

B tagging in HLT

We can trigger on b-jets on the online farm with performances similar to those we obtain offline!


TimingTiming• • Pixel Readout: PixelReconstruction::doIt• • Seed Generator: PixelSelectiveSeeds::seeds [<

5%]• • Trajectory Builder:• CombinatorialTrajectoryBuilder::trajectories [>80%]• • Trajectory Smoother:• KalmanTrajectorySmoother::trajectories [<10%]• • Trajectory Cleaner:• TrajectoryCleanerBySharedHits::clean [~ 1%]• • Trajectory Builder: CombinatorialTrajectoryBuilder• [ModularKFReconstructor::reco]• • Tagging: BTaggingAlgorithmByTrackCounting::isB


TimingTiming


Tracker MaterialTracker Material


Detailed Description Detailed Description


Pixel GeometryPixel Geometry


Total Tracker MaterialTotal Tracker Material


Total Tracker Absorption LengthsTotal Tracker Absorption Lengths


Alignment Studies Alignment Studies • Alignment Tools: they work

– one can still add functionality

• Mis-Alignment studies:– reconstruction is uncritical up to even 1mm/1mrad

misalignment (10 times more than survey/laser-alignment accuracy)

• Trigger ?

• update documentation (done), Note (preparation)


SummarySummary• CMS is making good progress on software and

HLT studies in both e/gamma and b/tau.

• Current production to meet June milestones: still ambitious,

• US role in these groups is small so far.

uscms may 2002jim branson 1 e/gamma and b/tau prs (small us effort) (what you should work on when...

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