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

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Pass 6: GR V13R9

Muons, All Gammas, & Backgrounds

Bill Atwood

SCIPP/UCSC

Data Sets:

Muons: allMuon-GR-v13r9 (14- Jan-2008)

AG: allGamma-GR-v13r9 (14-Jan-2008)

BKG: backgnd-GR-v13r9 (15-Jan-2008)

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

Live time = 2 sec/Run * No. Runs * .925 (Dead Time Corr.)

DT Corr = 55,270,161 evts * 26 msec/event /(2* (10000-447)) sec total run time

= .925

Irreducible Event Filter Cuts

((McZDir < -.2 & McId < 20) | Acceptance FoV for e+ , e- & g

(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%

have 4%! ??

CPF Analysis

Background Events

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

CPF Acceptance & Quality Bkg. Cut: 50048 Bkg.events left

McZDir < -.2 & McAcdZEnter > 100 & McCharge != 0 & CTBCORE > .1 & CalCsIRLn > 4

Remove Irreducible Events: 47827Bkg. events left

Events use Pass 5 definition

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

Quality Cuts: 165322 events Left

CTBCORE > .1 & CalCsIRLn > 4

Schematic

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

Pass 6 CPF Analysis

- What's new since Pass 5
- Using Ribbons as intended
- Usage of scaled ACD energies
- Improved understanding of where self veto comes from

Ribbon Cut

AcdRibbonActDist > -(2 +350/sqrt(max(20,CTBBestEnergy))) &

AcdRibbonEnergy > .05 & (was .1)

Tkr1SSDVeto < 3

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

Percentages

The >650 ZEROs maybe a problem

Low Cut Used!

Inefficiency circled in RED

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

Percentages

ACD Corner Cut

Most distances used in this analysis are scaled by

This makes the cut Energy dependent.

Selection: Tkr1LATEdge < 150 & Tkr1SSDVeto < 3

Vetoed Events shown in PURPLE

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

ACD Corner Cut

(Tkr1LATEdge ^ 2 + (AcdCornerDocaENorm - 10)^ 2 < 3600 |

(Tkr1LATEdge < 80 & abs(AcdCornerDocaENorm-2) < 4)) &

Tkr1SSDVeto < 3

ACD Basic Tile Energy Cut

Example 1 Cut:

Tkr1SSDVeto == 0 &

AcdTkr1ActiveDist > 0 &

AcdTkr1ActDistTileEnergy > 1.

Example 2 Cut:

Tkr1SSDVeto < 5 &

AcdTkr1ActiveDist > 0 &

AcdTkr1ActDistTileEnergy > .2

Example 1

Low & High Energy

Bands

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.

Self Veto Study

Plot 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

Tkr1SSDVeto == 0

Tkr1SSDVeto <= 1

Tkr1SSDVeto <= 2

Tkr1SSDVeto <= 4

Story

Two Choices for the Basic Veto Cut

#1

#2

Tkr1SSDVeto == 0 &

AcdTkr1ActiveDist > 0 &

AcdTkr1ActDistTileEnergy > 1.

Tkr1SSDVeto == 0 &

AcdTkr1ActiveDist > -16 &

AcdTkr1ActDistTileEnergy > .4

This cut more reflects

our usage in practice

This was the cut used

in the Skimmer

Correlation between Basic and Total Energy Cuts

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

USING #2

This really helps reduce the high energy residual Bkg. events

ACD Total Tile Energy Cut

- Scaled ACD Tile Energies
- Scaling 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…

First Cut

AcdTotalTileEventEnergyRatio > .8

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

The simple cut can be improved

on by using Tracking (AcdTkr1ActiveDistENorm)

Vetoed Events shown in BLUE

Total Tile Energy Cut

AcdTotalTileEventEnergyRatio > .8 |

(AcdTkr1ActiveDistENorm > -300 &

AcdTotalTileEventEnergyRatio >

max(.005, .1 - .0001*AcdTkr1ActiveDistENorm))

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

ZOOM IN

Tile Edge Energy Cut

abs(AcdTkr1ActiveDistENorm) < 15 &

AcdTotalTileEventEnergyRatio > .005

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 division

1 CT

Case 2: 0 and > 0 SSD Vetoes

2 CTs

CPF CT

Choose no division as nothing gained.

Greatly amplified the statistics here by

including all the available data

(nominally 20k sec worth)

Muon Hermiticity Test

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)

10 Events

50 Events

Pass 6 - Pass5 CPF Performance Comparison

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

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