# Presentation: 016066

## Pixel Efficiency in Overlap Region

- Hemma Mistry
- Kevin Lung, Ana Ovcharova, Boyan Tabakov
- Weiming Yao, Jim Siegrist

**URAP Project: Atlas Pixel Commissioning**
**Goal:**** Study pixel detector performances using pixel endcapA cosmic data and compare with Monte Carlo predictions in terms of pixel clustering, noise, resolution, and hit efficiencies as an undergraduate research project**

-                               6/12/2007

## Current Work

- Check cluster width vs. Incident Angle
- Check total cluster charge vs. Incident angle
- Compare Data and Monte Carlo
- Check hit efficiency in overlap region
- _What's new _since last presentation (4/24/2007)
- Removing noise/disable modules, bug fixes...

##  Cluster width in local x vs. incident angle of track passing through disk

-  Cluster width in local x vs. incident angle of track passing through disk
-  Data agrees well with Monte Carlo

***Cluster Width X vs. Incident Angle***

**X Projection**

**Y Profile**

**noise**

##  Cluster Width X vs Incident Angle after Cleanup 

-  Cluster Width X vs Incident Angle after Cleanup

-  Noise modules are identified: 0/15,0/34,1/39,2/42
-  Removing 17% of tracks after cleanup
-  Data agree well with Monte Carlo

##  Cluster width in local y vs. incident angle of track passing through disk

-  Data agrees well with Monte Carlo after cleanup

***Cluster Width Y vs. Incident Angle***

## Cluster Charge vs. Incident Angle

-  Total cluster charge (ToT) vs. incident angle of track passing though disk
-  Good agreement except peak shifted due to wrong calibration used in MC

##    Cluster Correlation between Overlap Hits 

- Cluster Width X Odd vs Even (Left)          Cluster Width Y Odd vs Even (Right)

## Checking Efficiency

- Check hit efficiency in overlap regions
- Plot local x vs. local y of active overlap region
- Take hit on front of disk and extrapolate to back of disk to find expected hit
- Check if expected hit is within overlap region
- Check minimum distance between expected hit and real hit on module

## Local x

**Local x**

**Local y**

***Local X vs. Local Y***
- Overlap Region - Odd Modules

## Extrapolate Hit on Front of Disk to Back of Disk

***Extrapolate Hit on Front of Disk to Back of Disk***

- Disk 0

- Disk 1

- Disk 2

## Find Expected Hit on Back of Disk

**X****A**

**X****B**

**Y****B**

**Y****A**

**X****A**, **Y****A** is the hit on the front of the disk
**X****B**, **Y****B** is the expected hit on the back 	of the disk

**X****B** = **X****A** + dz * tan(**θ**) * cos(**φ**)
**Y****B** = **Y****A** + dz * tan(**θ**) * sin(**φ**)

- dz

- z

- y

**θ**

**φ**

**(X****A****, Y****A****)**

**(X****B****, Y****B****)**

- y

- x

***Find Expected Hit on Back of Disk***

## Convert XB, YB to Local Coordinates

-  7.5 degrees between each module
-  angle = (3.75+7.5*module) * π/180
-  center of module:
-  X0 = 119.17 * cos(angle)
-  Y0 = 119.17 * sin(angle)

**Local x** = (XB – X0) * cos(angle + π/2) +(YB – Y0) * sin(angle + π/2)
**Local y** = (XB – X0) * sin(angle + π/2) -(YB – Y0) * cos(angle + π/2)

## Local X vs. Local Y

- Overlap Region - Even Modules

## Efficiency in Overlap Regio

***Efficiency in Overlap Regio***

- dr = (Δx2 + Δy2)1⁄2

- eff = N(dr<1)/Ntotal

## Efficiency vs Module 

## Efficiency (0.89+-0.03) seems low for Disk 0 Module 38 

- Check the expected local x, y for failing drmin cut, some of them near the side of fiducial region.

## Conclusion

- Cluster data are in good agreement with MC simulation.
- The pixel efficiencies have been measured to be close to 99% using overlap hits
- The cleanup removes 17% of tracks due to noise modules
- Overlap efficiency seems flat as function of module
- Residual distance (drmin) seems consistent between data and Monte Carlo.
- Check global position of middle disk between other two disks still on going.