Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 1 Tracker SAS Analysis Objective: To expose the tools and an approach to understanding the GLAST Tracker Initially.

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Presentation transcript:

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 1 Tracker SAS Analysis Objective: To expose the tools and an approach to understanding the GLAST Tracker Initially the charge was to delineate what the data requirements were for the Tracker Analysis This was by way of contributing to the "Run Plan" during I&T The "End-to-End" committee and I&T detailed a sets of runs - Let's evaluate this to see if its enough or too much!

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 2 Key to most HEP detector systems is the Tracking - Knits together not only itself - but by projection to other systems affords a "built-in" test beam. Elemental Tracker Data - - Hit SSD channels - Groups of adjacent hits = TkrClusters (Its from these that Pat. Rec. and Track Fits are made) - Trigger Primative - 3-in-a-Row Information - Time-over-Threshold (TOT) (once per layer) Tracker Self Consistency - - Reconstructed Trajectories match expectations. - Geometry - Efficiency (Reminder: expect ~ 100%)

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 3 A Trial Balloon: Image the individual SSD's with a goal of verifying - Location - Integrity (Wire Bonds) - Efficiency Idea was hatch with Eduardo in planning for this meeting Est. Require ~ 1 Hit/mm 2 Implementation: Recover the local trajectory location where there are missing SSD layers (gaps). Problem: No such variables available EITHER in the TDS or the Merit nTuple. Solution: Write a little code in the Analysis Package

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 4 Analysis Package Purpose: Provide subsystem and system wide parameters for Event Analysis leit-motif: Provide a collection of templates and examples on how to use the system (TDS & Services & Tools). A set of classes where each class focuses on calculating variables associated with a subsystem - or several together All have names like McValsTool, CalValsTool, TkrValsTool,... Start by looking at TkrValsTool.cxx as this involves only Tkr Data.

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 5 // Section to dig out the TOT information int gapId = -1; int lastLayer = -1; while(pln_pointer != track_1->end()) { Event::TkrFitPlane plane = *pln_pointer; int thisPlane = plane.getIDPlane(); int thisIview = Event::TkrCluster::viewToInt(plane.getProjection()); int thisLayer = 0; if(thisPlane%2 != 0) thisLayer = 2.*thisPlane+thisIview; else thisLayer = 2.*thisPlane+((thisIview+1)%2); if(lastLayer < 0) { //First Hit lastLayer = thisLayer; } else { Begin Loop Planes Computer Layer# from Plane & View (Probably should be added to TkrFitPlane) (I added the gap stuff to this loop) Continued on the next page....

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 6 if(gapId < 0 && lastLayer+1 != thisLayer){ gapId = lastLayer+1; Event::TkrFitPlane lastPlane = *(--pln_pointer); pln_pointer++; Point lastPoint = lastPlane.getPoint(Event::TkrFitHit::FIT); Event::TkrFitHit lastHit = lastPlane.getHit(Event::TkrFitHit::FIT); double xSlope = lastHit.getPar().getXSlope(); double ySlope = lastHit.getPar().getYSlope(); Vector localDir = Vector(-xSlope,-ySlope,-1.).unit(); Ray localSeg(lastPoint, localDir); int view; int layer; pTkrGeoSvc->planeToLayer (gapId, layer, view); double gapZ = pTkrGeoSvc->getReconLayerZ(layer,view); double arcLen = (gapZ-lastPoint.z())/localDir.z(); Point gapPoint = localSeg.position(arcLen); Tkr_1_GapX = gapPoint.x(); Tkr_1_GapY = gapPoint.y(); } lastLayer = thisLayer; // The Loop Goes On... First Gap Trigger Setup a local Track Segment (Probably should be added to KalmanFilterUtil) Compute ArcLength Project & Store Results

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 7 Next Step: Setup a run and execute: Use Flux Source "Surface Muons" Run 50K Events Set min. Energy for Finding/Fitting = 300 MeV TkrInitSvc.TkrMinEnergy = 300; Cuts: TkrNumTracks > 0 CalCsIRLn > 2 Leaves 6.8 K Events Results: 10.3 K Events in Tuple

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 8 Require: Tkr1Gaps > 0 This is was the original idea Image the Tracker Layout Leaves 4.7 K Events

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 9 Collapse down onto one Tower Cut off the edges ( 8 mm) Collapse down onto one SSD Cut off the edges... ( 4 mm) These are the events that shouldn't be... Lets Explore!

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 10 Require 1 Track Require Small   Require a MIP InEff. Events Good Events

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 11 This suggests we require: 1) Tkr1Chisq <.2 2).8 < CalMIPRatio < 1.2 3) TkrNumTracks == 1 Leaves: 4.1 K Events ( ~ 40% Efficiency) This leaves 1 Ineff. Event

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 12 What's Been Learned ? 1) The cosmic source of particles can be "Cleaned Up" thus affording highly efficient tests. Suspect the real world will be worse however! 2) The efficiency of this is ~ 40% (See above) 3) Broken wire bonds, etc. will be readily visible at 1 Hit/mm 2. In this example that would translate into x 16 x 2.5 (Eff.) x 2 (Layer Factor) = 11.3 M Triggers (Full Lat) x 2 x 2.5 (Eff.) x 4 (Layer Factor) = 2.8 M Triggers ( 2 Towers) (or about 1/2 day - 60 Hz Rate Trig. Rate assumed)

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 13 Where to go from here? 1) Repeat analysis with 2 Tower Data and Updated Surface Cosmic Rays Source 2) Find out what that remaining event was!

Bill Atwood, SCIPP/UCSC, June, 2004 GLAST 14 Mystery Event TkrThinHits = 24 TkrThickHits = 8 TkrBlknHits = 4 Why didn't all the hits wind up on the track????