# Presentation: 066143

## Silicon Parametric Charge Deposition Model

***Silicon Parametric Charge Deposition Model***

- Sebastian Carron, Susana Cabrera, Mark Kruse (Duke University)
-                    Michael Gold (University of New Mexico)

## The Model (a minimal explanation)

***Silicon****** ******Parametric Charge Deposition Model***

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***The Model ******(a minimal explanation)***

- -Primary charge deposition is calculated from the basic Bethe-Block formula
- -Parameterized Geant distributions are inputed for the Delta Rays
-  contribution. Magnetic Effects are built into distributions
- -Capacitive Sharing is included.
- -Realistic Noise from database is added
- -*Use of Parameterized distributions as Input to the Code, are supposed to save *
*Much time, as opposed to calculating every contribution from first principles*

***Tunable Parameters***
***  ******   ***-Crosstalk  (amount of capacitive sharing)
-      -Gain (2 parameters)
-      -Amount of Noise

## Creation of Study Samples

***Silicon****** ******Parametric Charge Deposition Model***

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***Creation of Study Samples***

- -After code changes create library
-  from SvxSim package
- -Compile new version of cdfSim
-   using new library, created single muons
-  with Fake Event builder
- -From created Sample, Ntupled
-   using SiStrip ntuple separately for each
-   layer excluding the layer from patern
-   recognition
- -Ntuples are filtered using Silicon Quality
-  cuts  provided by Doug Glenziski, at macro
-  level.
- -All samples created are 10K events big
- -Data is processed through the same ntuple
-  and cuts, also removing layer from patern
-  recognition of track.

- Layer 2 Original Sample (blue-Model, black-Data)

## Silicon Parametric Charge Deposition Model

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***Silicon****** ******Parametric Charge Deposition Model***

***Cluster Charge Distributions, Layer 2  ******(******data******, ******old parametric******, fixed parametric, ******physical******)***

**Original Distributions**

**After Delta Ray Bug Fix**

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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- Without Logarithmic scale we can see that
- Both Montecarlos have charge distributions
- That are narrower than data in layers 1
- To 5 (Not including L0 and ISL in this study)
- At this point realistic noise was not being
- added.
- Did code modifications to include realistic
- Noise. Amount of noise added can be tuned
- using the value of a cutoff in the noise
- gaussian.
- Also option can be chosen in tcl so that noise
- is only added to strips that had hits (option
- hits) or randomically to all strips (option all)

**Parametric**
**Physical**
**Data**

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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**cutoff 2.0**
**cutoff 1.0**
**cutoff 0.5**

- Charge Distributions Phi side,
- option All

- Charge Distributions, Z side
- option Hits

## Silicon Parametric Charge Deposition Model

- All charge distributions considered are scaled to
- Compensate for the different pathlenths.
- The charge was corrected according to the expression:
- (used by silicon experts)
- Which if written in terms of tangent gives:
- But the correct expression is below:
-                                                                                     **Therefore the error was more manifest in the tails**

***Silicon****** ******Parametric Charge Deposition Model***

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- The options all adds too many more hits per event (for cutoff of 0.5, 30k), which makes the
- code much slower. Since it seems an ineffective way to broaden the distributions, the
- option Hits was selected with cutoff of 0.5 using noise from database**.****  **

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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- It was noted that the Data and MC behaved
- Slightly differently under the application
- Of the charge scaling
- Problems in Montecarlo then must be
- angle dependent
- The Montecarlo track angle distribution
- looks flat, then problem must not be in
- track angles generated.

***Delta Rays Multiplicity***
- At this point the delta rays in the model did
- not have a different multiplicity according to
- incidence angle to the silicon wafer.
_**We implemented code changes to  include **_
_**Different multiplicities of Delta Rays**_

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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**Data**
**Before Mult. Changes**
**After Mult. Changes**

- Multiplicity distributions by
- Angle bins, as implemented in code from
- Geant reparametrization

- Charge distributions after the changes,
- We can see that the was some improvement,
- But more is needed to reach good agreement

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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***Tuning the Model***
- After fixing bugs and improving code, what remains is to tune Model. The two most
- Important distributions are the Cluster Charge and the Cluster Width distributions
- To fix Cluster Charge distribution the only parameter that remains is the Gain
- (Conversion between charge and ADC counts), We found **necessary to use a linear **
**function for the gain instead of a number, with a multiplicative factor and an **
**offset.**** **The factor makes the distribution wider or thiner, and the offset sifts it
- left or right.**  **
- To tune cluster width distributions, we found that changes in the Crosstalk were
- Quite effective. It was necessary to implement code to allow for different Crosstalks
- For different layers and sides.
- Although both types of distributions were not completely independent to changes
- to tune the other one, they were nearly so.
- It was necessary to create more than 20 10k event samples to reach the current
- Gain and Crosstalk numbers.

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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***Parametric Model and***
***New Data Phi side***
- Layers 1, 2 and 4 are the same
- Brand, and layers 3 and 5 are
- the same brand.
- The same value for gain both
- Slope and offset was maintained
- For same brand layers.
- As close values of Crosstalk as possible
- Were kept for same brand layers
**We see that agreement is **
**pretty good!!!, vastly improved**
**from original default values**

**Data**
**Parametric Model**

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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**Data**
**Parametric Model**

***Parametric Model and***
***New Data Z side***
- The cluster charge distribution
- For Layer 2 does not agree as
- Well. However the requirement
- For same gain values for the same
- Brand can be lifted for layer 2
- Because this layer has a different
- Pitch.
- If this is done, agreement can be reached
- easily

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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**Data**
**Parametric Model**

***Parametric Model and***
***Old Data Phi side***
- The older data is considered less
- reliable and can be thought as
- an independent check for the
- Tunning.
- The tuning was performed on the
- New data

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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**Data**
**Parametric Model**

***Parametric Model and***
***Old Data Z side***
- The disagrement for Layer 2
- In cluster charge is a bit worse
- Than with New Data.
- But this can be solved by changing
- the gain parameters for Layer 2

## Silicon Parametric Charge Deposition Model

***Silicon****** ******Parametric Charge Deposition Model***

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***Conclusions and to do list***
- Agreement reached is pretty good between Montecarlo and Data.
- Agreement of Parametric model with data now is better than Physical model
- (Physical Model was not tuned for gain values)
- Currently Parametric Model close to a factor of 2 faster
**Big improvement can be made in speed, and work for optimizing speed has**
**begun**
**CDF note is being written with all details of study**
**Validation of Model remains to be done, M. Paulini has agreed to generate**
**t tbar using the model. We have already the macros to compare residuals,**
**etc for validation**