# Presentation: 466367

## Zero Suppression Studywith a fast MC

**John Krane**
**At large member of DØ...**

- Calorimeter Task Force
- December, 2002

## Goals

- Run 1k events in a few seconds(actual is currently 15k jets/min)
- Simulate jet energy profiles
- Longitudinal
- Ncells in each layer
- Simulate noise
- Simulate arbitrary ZSP scheme

## Method of Fast MC

- Sample (random number “thrown against” histo) Layer_E
- While total jet layer E < Layer_E
- Sample fractional cell E distribution
- Add noise by sampling actual calibration histograms (R. Zitoun)
- Result fluctuates around the generated Layer_E...this is OK
- Add noise to any remaining cells in jet cone
- Suppress cells with 1.5, 2.5, or different  for different layers...whatever you like...towers

## Method for Inputs

- Study jets in Monte Carlo for initial profiles
- Free of noise pathology and zero-suppression
- Low, med, high-pT = 15-20, 100, 300 GeV
- Get histo of E, layer by layer
- Get histo of Cell E fraction per layer
- Currently using p10.14 with noise and zsp, want Jet MC with no noise and no zsp

- Forced positive!

## Input Histograms: Total Energy by Layer

**Input Histograms: Total Energy by Layer**

- Central lyr 1

- Central lyr 2

- Central lyr 15

- Central lyr 15 for jets >20 GeV

- Low pt: lyr 15 is noise
- High pt: lyr 15 populated

## Input Histograms: fractional Energy per cell

**Input Histograms: fractional Energy per cell**

- Central lyr 1

- Central lyr 15

## Current Results (pending better inputs!)

- Have result histos for 9 different ZSP schemes
- Central, ICR, Forward
- Low, med, high jet pT
- Also, 0 GeV Jets, i.e. how noise can fake jetsI allowed double-wide jets...
- Looking at positive-E towers vs. +/- towers

## Definition of a “tower” in Fast MC

**Definition of a “tower” in Fast MC**

- Store cell energies per layer in an array
- Random number of cells rqd to reach the generated Layer_E
- A “tower” is each “vertical sum” through these arrays
- Ignoring merged jets  noise jets

- Lyr 1

- Lyr 2

- Lyr 3

- Lyr 4

- Lyr 5

- Lyr 6

- Lyr 7

- Lyr 11

- Lyr 12

- etc...

- Cell array [154]

## Aside on Noise jets

- Many noise jets are merged and split DOZENS of times (as many as 99 times!)
- Multiply that by number of jet algo
- Reco CPU needs increase
- Event has many many cells so disk needs increase
- My numbers on noise jets provide info on one ZSP scheme relative to another...absolute numbers not so valid because I’m not simulating merge/split behavior

## ZSP schemes

**ZSP schemes**

- 1.5  zsp
- 2.5  zsp
- 1.5 in low-noise layers (2,3,4,5,6,7)and 2.5 elsewhere
- 2.5 in EM and 3.5 elsewhere

| 1 | EM1 |
| --- | --- |
| 2 | EM2 |
| 3,4,5,6 | EM3 |
| 7 | EM4 |
| 8 |  |
| 9 |  |
| 10 |  |
| 11 | FH1 |
| 12 | FH2 |
| 13 | FH3 |
| 14 |  |
| 15 | CH |
| 16 |  |
| 17 |  |

## Key

**Key**

## Noise, central region

## Noise, ICR

## Noise, forward region

## Jet Energy

- Central

- Central

- Forward

- Forward

## Jet Energy Loss, Resolution (central)

- Still Gaussian

## Jet Energy Loss, Resolution (ICR)

## Jet Energy Loss, Resolution (forward)

## Resolution Calculation

- Previous plots were “raw resolution”
- Want to assume an Energy Scale Correction that performs as well as it can
- Perfect noise correction ***on average ***will not affect width of resolution gaussian
- Perfect response correction ***on average ***resolution gaussian width scalles with correction

## Corrected Resolution (Central)

**Corrected Resolution (Central)**

- Circ: +/- tow
- Star: pos-only tow
- Line is Run I reso
- Note odd slope forextreme zsp

## Corrected Resolution (ICR)

**Corrected Resolution (ICR)**

- Circ: +/- tow
- Star: pos-only tow

## Corrected Resolution (Forward)

**Corrected Resolution (Forward)**

- Circ: +/- tow
- Star: pos-only tow
- I don’t trust this one!

## Summary

- Fast ZSP Monte Carlo is working
- Post-analysis of “JES-corrected” resolution
- Need better MC for input histograms