Pass 6: GR V13R9Pass 6: GR V13R9 Muons, All Gammas, & BackgroundsMuons, All Gammas, & Backgrounds

Data Sets:Data Sets:

Muons: allMuon-GR-v13r9 (14- Jan-2008) AG: allGamma-GR-v13r9 (14-Jan-2008) BKG: backgnd-GR-v13r9 (15-Jan-2008)

Bill AtwoodSCIPP/UCSC

Initial Pruning Cuts:Initial Pruning Cuts: ObfGamStatus >= 0 Passed Onboard Filter (Only Bkg. Data set) TkrNumTracks > 0 At least 1 track CalCsIRLn > 4 Track intercepts CAL CTBCORE > .1 Not unreasonable recon

Normalizations & Irreducibles Normalizations & Irreducibles Live time = 2 sec/Run * No. Runs * .925 (Dead Time Corr.) DT Corr = 55,270,161 evts * 26 sec/event /(2* (10000-447)) sec total run time = .925

Irreducible Event Filter Cuts((McZDir < -.2 & McId < 20) | Acceptance FoV for e+ , e- & (McZDir < .1 & McId > 20)) & Acceptance FoV for protons

McAcdZEnter > 100 & Enters Tracker McCharge !=0 & Isn't a Photon McTHPosHitOthers < 6 & Not enough hits to track anything but e+ & e- McAcdActDistTileEnergy < .2 Entering Tile has little energy

Cuts to blind Irred. Filter to Ribbons

!(((abs(McAcdXEnter)< 519 & abs(McAcdXEnter) > 485 ) | (abs(McAcdXEnter)< 181 & abs(McAcdXEnter) > 155 ))| ((abs(McAcdYEnter)< 519 & abs(McAcdYEnter) > 485 ) | (abs(McAcdYEnter)< 181 & abs(McAcdYEnter) > 155 ))| (abs(McAcdXEnter)> 820 & abs(McAcdYEnter) > 820 ))

As noted in Pass 5: The ratio of proton events to QED is different - predict ~ 30% As noted in Pass 5: The ratio of proton events to QED is different - predict ~ 30% have 4%! ??have 4%! ??

CPF Analysis CPF Analysis

Remove Irreducible Events: 47827 Bkg. events left Events use Pass 5 definition

CPF Acceptance & Quality Bkg. Cut: 50048 Bkg. events leftMcZDir < -.2 & McAcdZEnter > 100 & McCharge != 0 & CTBCORE > .1 & CalCsIRLn > 4

All Gammas:All Gammas: First 200k Events (corresponding to 2.65 x 106 generated)

Quality Cuts: 165322 events Left CTBCORE > .1 & CalCsIRLn > 4

Background EventsBackground Events

Live time = 7370 sec ( Used first 3984 runs) (499957 events)

Pass 6 CPF AnalysisPass 6 CPF Analysis

Use Ribbons to close gaps between ACD Tiles

Kill Tracks pointed at the ACD Corner Gaps

Veto Events with 1st Track pointed at hit Tile

Remove events with excess Total ACD Energy

Cut to remove events with low pulse height near Tile edges

Compute Energy compensated variables for CT usage

Compute CPFGamProb using CT Ensemble and Clean-up

SchematicSchematic

What's new since Pass 5What's new since Pass 5 Using Ribbons as intended Usage of scaled ACD energies Improved understanding of

where self veto comes from

Ribbon CutRibbon CutAcdRibbonActDist > -(2 +350/sqrt(max(20,CTBBestEnergy))) &AcdRibbonEnergy > .05 & (was .1)

Tkr1SSDVeto < 3AcdTkr1RibbonDist > -2 & Tkr1SSDVeto < 2 Try eliminating blanking out RibbonsTry eliminating blanking out Ribbons

The >650 ZEROs maybe a problem

Low Cut Used!

Inefficiency circled in RED

Percentages

Very low pulse height cuts, makes analysis vulnerable to mismatch to as-built equipment

AcdCornerDocaENorm = AcdCornerDoca*(min(1000, max(30, CTBBestEnergy)))^.5/10.

ACD Corner CutACD Corner Cut(Tkr1LATEdge ^ 2 + (AcdCornerDocaENorm - 10)^ 2 < 3600 | (Tkr1LATEdge < 80 & abs(AcdCornerDocaENorm-2) < 4)) & Tkr1SSDVeto < 3

ACD Corner CutACD Corner Cut

Percentages

Most distances used in this analysis are scaled byThis makes the cut Energy dependent.

rgyCTBBestEne

Selection: Tkr1LATEdge < 150 & Tkr1SSDVeto < 3

Vetoed Events shown in PURPLE

ACD Basic Tile Energy CutACD Basic Tile Energy CutExample 1 Cut: Example 1 Cut: Tkr1SSDVeto == 0 & AcdTkr1ActiveDist > 0 & AcdTkr1ActDistTileEnergy > 1.

Self Veto StudySelf Veto StudyPlot the ratio of events in Low & High energy bands as a function of the Tile Energy Cut.

Having jumped ahead to the end of the analysis, there is an appreciable leakage of high energy events that can be missed by this cut. This sets limits on how liberal one can be with the Active Distance and associated Tile Energy. The scaled ACD energies become less capable as the reconstructed event energy increase (ie. > 10 GeV). These suggest that the Active Dist. Min is -16mm and Tile energy is .4 MeV. Fortunately the SSD req. is == 0

Example 2 Cut: Example 2 Cut: Tkr1SSDVeto < 5 & AcdTkr1ActiveDist > 0 & AcdTkr1ActDistTileEnergy > .2

Note: This portion of the CPF Analysis was done with v13r7 since my v13r9 datasets all had the min. basics Active Dist. - Tile Energy cut applied in the Skimmer.

Example 1

Low & High Energy Bands

Story

Story

Tkr1SSDVeto == 0Tkr1SSDVeto <= 1Tkr1SSDVeto <= 2Tkr1SSDVeto <= 4

Tkr1SSDVeto == 0 & AcdTkr1ActiveDist > 0 & AcdTkr1ActDistTileEnergy > 1.

Tkr1SSDVeto == 0 & AcdTkr1ActiveDist > -16 & AcdTkr1ActDistTileEnergy > .4

Correlation between Basic and Total Energy Cuts

Cost of #2 over #1: 936 Events (.7%)Cost of #2 over #1: 936 Events (.7%)

Two Choices for the Basic Veto CutTwo Choices for the Basic Veto Cut

This was the cut used in the Skimmer

This cut more reflects our usage in practice

#1#1 #2#2

This really helps reduce the high energy residual Bkg. eventsUSING #2USING #2

First CutAcdTotalTileEventEnergyRatio > .8

ACD Total Tile Energy CutACD Total Tile Energy CutScaled ACD Tile EnergiesScaling the ACD energies to the total reconstructed energy lessens the self veto effect

dramatically. Two scale energy variables are considered:

AcdTileEventEnergyRatio = AcdTkr1ActDistTileEnergy/CTBBestEnergy * 100

AcdTotalTileEventEnergyRatio = AcdTotalEnergy/CTBBestEnergy * 100

Advantages & Disadvantages Scaled responses automatically increase amount in ACD require to Veto an event as E

increases The dependence on Tracking (along with its ~ 2% mis-tracking) is greatly reduced However as CTBBestEnergy increase, eventually even a MIP is passed…

Note: something akin to this could be done onboard the LAT!

Total Tile Energy CutTotal Tile Energy CutAcdTotalTileEventEnergyRatio > .8 |(AcdTkr1ActiveDistENorm > -300 & AcdTotalTileEventEnergyRatio > max(.005, .1 - .0001*AcdTkr1ActiveDistENorm))

Tile Edge Energy CutTile Edge Energy Cutabs(AcdTkr1ActiveDistENorm) < 15 & AcdTotalTileEventEnergyRatio > .005

Vetoed Events shown in BLUEThe simple cut can be improved on by using Tracking (AcdTkr1ActiveDistENorm)

ZOOM INZOOM IN

More can be gained by using the single tile energy associated with the 1st Track. This is helpful near the tile edges where the pulse height is low

1 CT

2 CTs

CT Analysis: To divide the data or not to divide the data?CT Analysis: To divide the data or not to divide the data?A key factor in using the ACD are the SSD Vetoes. It is natural to break the data into subsets according the number of SSD Vetos

Case 1: No divisionCase 1: No division

Case 2: 0 and > 0 SSD VetoesCase 2: 0 and > 0 SSD Vetoes

CPF CTCPF CTChoose no division as nothing gained.Greatly amplified the statistics here byincluding all the available data (nominally 20k sec worth)

CPFGamProb > 0 50 Events 2.8 x 10-4

178384 Events

For McTkr1DirErr < .01: No. Events = 174752 and 10 with CPFGamProb > 0 (98.0 %) (0.6 x 10-4)

Muon Hermiticity TestMuon Hermiticity Test

50 Events10 Events

Pass 6 - Pass5 CPF Performance ComparisonPass 6 - Pass5 CPF Performance Comparison

Note: These plots use the v13r7 data - skimmed v13r9 data have Basic Cut applied

Conclusion:Conclusion: Pass 6 is an order of magnitude better the Pass 5 while retaining the same Gamma efficiency!

V13r9: Shapes different due to Skimmer cut