# Presentation: 827687

## Muon Combined PerformanceD. Adams BNL  D. Levin UM    P. Kluit NIKHEF 

- _Topics_
-  CSC notes
-  Status of Muon Combined  Reconstruction
-  Performance tasks and studies

## MCP CSC Notes

- _Main  considerations:_
- document current  performance of
- Muon software reconstruction in terms of standard candle physics processes
- Limitations imposed by detector functioning & gauge detector response when tweaked from the ideal (misalignments, miscalibrations, defects)
- document tools to use to determine efficiency, acceptance, resolution, and misalignments, miscalibrations using real data
- document current trigger performance
- Detail muon reconstruction and signatures combined with calorimetry

## The number and scope of these notes is determined by availability of editors and contributors.

- Four broadly scoped notes were identified with emphasis on
- Track reconstruction
- Performance with data
- Calorimetry
- Trigger
**Meta-goal of the CSC notes effort:**
** *****Provides a very effective arena in which competing groups can cross-pollinate and work collaboratively.***

## We have a very effective arena in which competing groups can cross-pollinate and work collaboratively!

**We have a very effective arena in which competing groups can cross-pollinate and work collaboratively**!

## CSC Notes I 

- 	Muon track reconstruction algs and performance. Editors: Stephane Willocq, Ahmimed Oarou, Alan Poppleton
- A core paper bearing the meat of muon reconstruction.
- Will document performance of muon combined reconstruction using various reconstruction chains and algorithms
- Contents:
- Overview of reconstruction and identification algorithms
- Tools for performance evaluation& Classification of tracks in the Muon Spectrometer
- Muon Spectrometer standalone reconstruction
- Muon reconstruction at the interaction point& Energy loss correction (Note III)
- Combined muon reconstruction
- “Low Pt” Muon identification with Inner Detector tracks and Muon Spectrometer segments

## CSC Notes II 

- 	In situ Determination of the Performance of the Muon Spectrometer
- 	Editors: Oliver Kortner and Matthias Schott
- scope and contents:
- 	Performance of ideal and deteriorated detector
- 	Measurement of acceptance and reconstruction efficiency
- 	Determination of misalignments
- 	Checking of the Magnetic field map
- 	Sensitivity to specific miscalibrations
- 	(degraded RTs, wire sags, B field distortions)
- This paper will have some common ground with SM Notes- i.e, using Z  “tag & probe” technique

## CSC Note III	Muons in calorimetry Editor Frank Taylor 

- _CSC Note III_	Muons in calorimetry Editor Frank Taylor
- Muon isolation and  energy loss algorithms:
- Athens University & UAT Saloniki/Saclay
- Muon Identification algorithms exploiting energy profiles in calo cells/layers
- Performance of the above with selected physics processes.

## CSC Notes IV 

- Muon Trigger Performance Editor: Michela Biglietti
- Contents: **General trigger performance studies**
**	****Trigger rate evaluation for the full slice**
**	****Fake dimuon triggers from single muon double countings **
**	****Muon from in flight K/p decay rejection **
**	****Performance with pileup &  cavern background**
**	****Trigger performance summary from physics CSC papers**

## Muonboy/STACO/MuTag Enhancements (Saclay)

- Use of TrkExtrapolator in:
- STACO:
- Extrapolation of MS Tracks from  the Calorimeter Entry to the perigee
-  MuTag:
- Extrapolation of ID Tracks from the perigee to the muon Segment plane

## Use TrkExtrapolator in STACO

STACO combines ID and MS Tracks extrapolated to the perigee
 ID Tracks at the perigee
 Muonboy Tracks extrapolated to the perigee inside Muonboy
Muonboy Tracks are also given at the Calorimeter Entry

 Use Andi’Extrapolator to extrapolated Muonboy Tracks at the Calorimeter entry to the perigee

The Muon measurement expressed at perigee obtained using Extrapolator is compared with the Muonboy Muon measurement expressed at perigee (single 100 GeV pT sample)

- STACO combines ID and MS Tracks extrapolated to the perigee
-  ID Tracks at the perigee
-  Muonboy Tracks extrapolated to the perigee inside Muonboy
- Muonboy Tracks are also given at the Calorimeter Entry
-  Use Andi’Extrapolator to extrapolated Muonboy Tracks at the Calorimeter entry to the perigee
- The Muon measurement expressed at perigee obtained using Extrapolator is compared with the Muonboy Muon measurement expressed at perigee (single 100 GeV pT sample)

- Muon System

- Calorimeter Entry

- x

- Perigee

- ID

- x

- Extrap

- Mboy

- Muonboy/STACO/MuTag Enhancements (Saclay)

## The difference of the Track parameters at perigee between Extrapolator &  Muonboy

- No effect on d0, z0 and theta
- Some small effect, few % on
- q/P
- Substantial effect on Phi0
- Possibly due to Field used in
- ID reconstruction

- The difference is scaled
- to the sigma of the
- parameter from Muonboy
-  track

## d = extrapolated_ID -segment

- MuTag: Uses only , direction. Now try segment direction
- d = extrapolated_ID -segment
- First look at dijet sample: mc11.005014.j5_pythia_jetjet.pileup.v11004210
- 4 sigma cut reduces cavern background by 60%

## 	Sample:	single   pT= 100 GeV/c simulated  & digitized with 12.0.3 nightlyRDO input file location = /castor/cern.ch/user/m/muonprod/1203/digit/atlas-dc3-07.*Reconstructed with release 12.0.3 nightly (rel_4) + tags as inhttps://twiki.cern.ch/twiki/bin/view/Atlas/RecoSimu1203DetDescrVersion = “ATLAS-DC3-07”GeoModelSvc.MuonVersionOverride =	'MuonSpectrometer-R.01.01.Initial.Light'      (ideal layout R) 	'MuonSpectrometer-R.01.01.Initial.Light_Egg_Rndm'               (egg-shape random misalignments layout R'')

- 	_**Sample**_:	single   pT= 100 GeV/c simulated  & digitized with 12.0.3 nightlyRDO input file location = /castor/cern.ch/user/m/muonprod/1203/digit/atlas-dc3-07.*Reconstructed with release 12.0.3 nightly (rel_4) + tags as inhttps://twiki.cern.ch/twiki/bin/view/Atlas/RecoSimu1203DetDescrVersion = “ATLAS-DC3-07”**GeoModelSvc.MuonVersionOverride =****	****'MuonSpectrometer-R.01.01.Initial.Light'      (ideal layout R)**** ****	****'MuonSpectrometer-R.01.01.Initial.Light_Egg_Rndm'   ****            (egg-shape random misalignments layout R'')**

***Moore Single ************ Performance in 12.0.3***

_**S. Willocq, K. Black, A. Poppleton**_

## Moore Efficiency

**Moore Efficiency**

- No discernable change in efficiency
- Also, no change to number of hits on track

## Moore Resolution

**           ****Layout R                                               Layout R’’**

**Moore Resolution**

- No change to resolution width, but reduced RMS for R’’ layout

## Moore Pulls & Resolution vs 

**         ****Layout R                                          Layout R’’     **

## MuGirl Status  (muons from the inside out) 

_***MuGirl Status  ***_(muons from the inside out)
- (S.Tarem, N. Panishkavili, D. Primor, Z. Tarem)
- Initialize Muon candidate from ID track
- Extrapolate track to Muon Spectrometer
- Find spectrometer hits in road around extrapolated track
- Make segments from hits & improve extrapolation
- hit & segment information identifys muon
- ANN to create one figure of merit & select “muon like” candidates
- _Improvements  _
- Define a *combined segment* improves extrapolation. (= best combination of the trigger TGC or RPC and the MDT segment in each station, with φ from trigger chamber or ID.
- This better pointer to the next station *reduces the road widths*

## MuGirl Barrel  Middle to OuterCombined segment vs MDT, RPC, ID

_**MuGirl Barrel  Middle to Outer**_**Combined segment vs MDT, RPC, ID**

- Distance of segment from extrapolated track.
- RPC contribution is surprisingly small. Possible geometry bug- (since repaired.)

## Method I: “CaloLR” ( Wisconsin)
Identify muons by the distinct pattern of their energy loss in all calorimeter systems

From fully-simulated single muons and single pions, obtained the distributions for potentially relevant ratios of variables.

Some examples:

- eemb2/EEM+Had

- etileb0/EHad

- EtopoMax/Etopo

- etileb1/EEM+Had

- Muons
- Pions

- Method I: “CaloLR” ( Wisconsin)
- Identify muons by the distinct pattern of their energy loss in all calorimeter systems
- From fully-simulated single muons and single pions, obtained the distributions for potentially relevant ratios of variables.
- Some examples:

- _Muons in Calorimetry: Identification Algs_

##  rejection  vs   efficiency

- Colors: **0-10**, **10-50**, **50-100 **[GeV]
- LR and rejection evaluations obtained from disjoint samples
**But, still, in a clean environment**
- Rejections of up to 1000±300 @ 90% efficiency (energy>50GeV).
- Lower values in the crack
- For low energy: in the 10s.
- for H 4 mu
- Efficiency gain (over Staco+MuTag): **16.0%**
- No loss of resolution
- Similar amount of non-Gaussian tails (~85% within 2σ)

-  rejection

- Muon efficiency

- Muon efficiency

- Muon efficiency

- BARREL

- CRACK REGION

- END CAP

## Method II: CaloTrkMuId Algorithm (NIKHEF) 	
Is based on TrackToCaloTool
Uses only Hadron Calorimeter deposits
Focus on 4pi Muon id to complement Muon system
Less emphasis on background rejection
Study low momentum muons for 900 GeV data
Algorithm flow
Loop over tracks
Tries to extrapolate to Calorimeter surfaces
         using ExtrapolToCaloTool::TrackSeenByCalo
Stores DepositInCaloCollection into StoreGate
        Containing:
caloSample, caloEta, caloPhi, caloRadius
             pt_calo_ctb, caloEnergies (cone sizes 0.1,0.2,0.3)
Runs CaloMuonTag() method

- Is based on TrackToCaloTool
- Uses only Hadron Calorimeter deposits
- Focus on 4pi Muon id to complement Muon system
- Less emphasis on background rejection
- Study low momentum muons for 900 GeV data
- Algorithm flow
- Loop over tracks
- Tries to extrapolate to Calorimeter surfaces
-          using ExtrapolToCaloTool::TrackSeenByCalo
- Stores DepositInCaloCollection into StoreGate
-         Containing:
- caloSample, caloEta, caloPhi, caloRadius
-              pt_calo_ctb, caloEnergies (cone sizes 0.1,0.2,0.3)
- Runs CaloMuonTag() method

- Atlas Muon Week Gustavo Ordonez Sanz    RU Nijmegen

## New CaloTrkMuid Efficiency

- Green=total
- Red= last layer
- Blue=last-1
- Black= last-2

- Single  Pt = 100 GeV

- Single     Pt = 5 GeV

- Atlas Muon Week Gustavo Ordonez Sanz    RU Nijmegen

## Muon Software Algs activity

**New, much improved CSC clusterization-  (D. Adams, see talk)**
**Detect Before Estimate CSC method (D. Primor, see test beam review)**
**Muon tracking geometry tools (S. Todorova, M. Wolter, J. Hartman) Can provide where-am-I information along the track.**
**Progress in pattern recognition modules developments- NIKHEF**

## Muon Software Algs activity (cont)

***Truth, Holes and Quality*** information for muon tracks (E. Moyse)
- Truth: Hit level Truth maps for each level of muons
- Currently: Truth for PrepRawData is functional
- Holes: Tool to report on presence of holes in track under development
- Quality: need to deliver quality parameter for muon tracks. Currently available are 2 and number of hits and holes  on track.
- Truth and Holes capability expected for 12.0.x

## Muon AOD/ESD news(K. Assamagan)

- Some modifications by the release 13. Most important:
- The CombinedMuon (ESD) and the Muon (AOD) will be merged into one class, simply Muon
- On the ESD, Muon may contain more information and less in the AOD
- It will be easier to promote/demote data to/from the AOD
- The single class will allow running same analysis code on the AOD or ESD in a transparent way without recompilation or recreation the AOD on the fly
- Similar re-organization have been made for CaloCluster and is in program for egamma (ESD) and Electron/Photon(AOD). Discussion is in progress to do the same for tauObject (ESD) and TauJet (AOD).

## A Muon Performance Assessment Algorithm (D.A.)

- For MC sets, evaluate muon reconstruction using truth information
- Select a collection of reconstructed muons (evaluation sample)
- Select a collection of Monte Carlo muons (reference sample)
- Match the two
- One-to-one with leftover MC (inefficiency) and reconstructed (fakes)
- Generate performance ntuple (new  next slide)
- Evaluate individual muon performance metrics
- Efficiency is (# matched MC)/(# MC)
- Fake rate is the (# unmatched reco)/event
- Compare matched reco and MC parameters to calculate resolutions and fraction of misreconstructed tracks
- Evaluate event performance metrics
- Fractions of events with missed or fake muons
- PT sums and residuals

## A performance ntuple
One entry for each found, lost or fake track
Lost has MC info only
Fake has reco info only
Found has both
All have run and event number; other content:

- One entry for each found, lost or fake track
- Lost has MC info only
- Fake has reco info only
- Found has both
- All have run and event number; other content:

|  | MC | Reco |
| --- | --- | --- |
| Production vertex |   X |  |
| Track type (standalone, inner, combined) |  |   X |
| Track parameters at beam line DCA |   X |   X |
| Track error matrix |  |   X |
| Quality parameters (chi-squares, ...) |  |   X |
| # hits for each detector |   X |   X |
| Calorimeter energy loss |   X |   X |
| Distance to and pT of nearest jet |   X |  |

## ConclusionSome MCP Performance tasks planned or underway 

- Muon performance comparison studies:
**inner Detector tracking  algs with muon Mutag (j/psi and ttbar) **
** ****MuGirl &  MuTag (Athens, BNL)**
**STACO/MUID on muonboy+InDet tracks (?)**
**MDT muon segment pattern recognition**
- Evaluation of alignment scenarios an calibration scenarios:
- extensive program starting with single muons to physics samples
- Most of muon performance CSC studies to be done with pileup & cavern background
- currently under validation in 12.0.3