1 ATLAS reconstruction software David Rousseau- LAL/Orsay

1

ATLAS reconstruction software

David Rousseau- LAL/Orsay

David Rousseau, ATLAS reconstruction, HEP2003, Aachen, July 20032

ATLAS detector

Straw tracker

Si tracker

Lar em calo

Lar had calo

Tile calo

Muon spectrometer


Hno

pile-up


Hhigh luminosity (L=10^34)

23 interactions per bunch crossing

1000 charged tracks in tracker acceptance


Tracking

3-layers pixel Si detector (middle one missing at startup)

4 layers of stereo strip Si detectors Straw tracker (typically 30 straws on

track)More details in Alessia Tricomi’s talk


Impact parameter resolution 1/pT resolution


B-jet tagging

Impact-parameter of tracks combined in likelihood-ratio

Both transverse and z impact parameter used

Severe requirements on track quality (e.g innermost pixel cluster inambiguous)


WH event

H bbWl lM(H)=120

GeV/c2


u jet rejection @ b=60%

More material:IP resolution degradationMore fake high IP tracks


Impact parameter resolution of b-tracks degraded by multiple scattering

-More non-b tracksMore fake high IP tracksB-track narrow jet


ttH event

H bb tt W(l l )bW(qq)b

M(H)=120 GeV/c2

Same b tagging performance (for given pseudo-rapidity and Pt) factorization hypothesis holds


b tagging in Heavy Ion collision

Heavy Ion physics was not even considered when Atlas was designed

~10.000 tracks in tracker acceptance (10 times more than high luminosity pile-up)

But track density comparable to density in high Pt jets…soo with little extra work on tracking

algorithm, tracks can be foundo b tagging even doable:

Ru=35 @ b=50% , 11 @ b=60%


Electron bremsstrahlung:need special tracking

E/ identification

High pT (>7GeV): o Find e.m cluster (sliding window)o E.m shower shape cutso Track findingo 0 track: photon (typical jet rejection 2000)o 1 track: E/p matching + Transition Radiation hits

counting: electron (typical jet rejection 100000)

Low pT electron (b tagging, J/): o Start from the track and

search energy deposition in e.m. calorimeter


Soft electron ID

Tagging variables

epi

# of TR hits

diff betweenshower and impact position

shower isolation

fraction of E in 1st sampling

energy weighted width

Et(calo)/pt

transverseimpact parameter

fraction of E in 3rd sampling


Soft electron ID

Electron in b jets Hbb (mH=120 GeV)

without noise

with noise

Efficiency

Pio

n re

ject

ion


E/ reconstruction

E.m. clusters reconstructed with sliding window algorithm

Rectangle clusters usedo Robust against

Electronic noise Pile-up Underlying event Material effects

o Calibration/linearity

Typically 3 eta cells x 5 phi cells o Cell granularity 0.025 pseudo rapidity/radiano Larger in phi to accomodate B field


Em cluster reconstruction

E measured vs conversion radius

*

Conversionscan be reconstructed


pointing

PV

strips

middle

O z

1

2

direction

presampler

LHC: luminous region z~5cm


Mass resolution H

Primary vertex from tracks

=1.31 GeV=1.18 GeV

No pile-up, no el. noise

1 conv

mH (GeV)

mH (GeV)

Primary vertex from calo pointing

Primary vertex finding: not always possible with low Pt(H) and high lumi


Intermezzo… ATLAS reconstruction has evolved from feedback

on detector design to evaluation of detector performance and physics reach and recently:o foresee treatment of real Atlas datao migration fortran to C++ completedo keep on improving or new algorithms

Use Athena/Gaudi (with LHCb) flexible framework:o Separation between Data and Algorithmso Run-time configuration and dynamic library loading

Athena also used for MC generation, Geant4 simulation (coming), high level trigger, fast simulation, user analysis

Spring 2003 : Data Challenge 1, several millions event simulated (G3) and reconstructed world-wide (tens Terabytes of data)


Flow example

Fast DigiSimulation

MCHits

Detailed Digitization

RawByteStream

LArCellBS decoding Calo Clustering

Read Out Driveremulation

RawChannels First data reduction

TileCell

Missing ET


Work modelCirca 1500 C++ classes in 300 packages

maintained/developed by 100 people (only a few CERN based)

Structured CVS repository with one directory per detector specific software (Muon, Larg calorimeter…), and one per activity (Reconstruction, DetectorDescription…). Each directory managed by responsible person.

One major release every ~6 monthsDeveloper release every three weeks (1-2

iterations allowed, some failure allowed)Automatic nightly builds with latest tagged

version of all software in view of the following release.


Jet reconstruction

Several algorithms exploredo Cone jet (seeded/unseeded + split/merge)o kT jet

Weighting technique:o w= a + b/E + c ln(E)

o Minimize resolution under constraint E=Etrue

o Bins in pseudo-rapidity because effective length of calorimeters is non uniform (mainly 1/sin() but also passive material distribution)

o « 2 » weights: one for e.m calo one for had caloo « 7 » weights : exploit calorimeters longitudinal

segmentations


Jet r

elat

ive

ener

gy r

esol

utio

n

E/E=100%/E 2%

E/E

true

E/E=80%/E 2%

E/E=65%/E 2%


Missing ET

Missing transverse energy essential tool for a wide range of physics

Computed from sum of cell transverse energy with optimised weights

Calorimeter acceptance very important: -5<pseudo-rapidity<5


Missing ET resolution


bbA m(A)=450 GeV Z

No noise

With noiseAsymetric cutE>2E

Z/A/H 1 2 X1 1 X2 2

Assume the two neutrinos are colinear to visible tau decays

System solvable using Missing ET measurement

Mass reco with missing ET

Mass resolution (GeV) Mass resolution (GeV)


Tau identification Especially important for A+- and

numerous supersymmetry channels Hadronic tau decay characterised as

a very narrow jet in particular:o use very fine granularity of first layer of

Lar em calorimeter : =0.003o reconstructed track counting

Strong pT dependence: at higher pT, tau jet is narrower, background jet fatter

Correlated tagging variables combined in bins of jet pT

(measured with weights optimised for tau’s ) Depending of analysis, different working points in

Rejection vs Efficiency plane


Tau Tagging variables

jet

Radius of em cluster Energy within 0.1<R<0.2 Number of charged tracks

Cluster eta width in em calo first layer

Number of em calo strip with energy abovethreshold

Charged tracks total charge


Tau ID efficiency

A+-l+h-A+-h+ h-

t H+b (h)b

0.5

susy searches


1. Identification of Region of Activity

2. Reconstruction of local straight track segments

3. Combination of three tracks segments

4. Global fit taking into account multiple scattering and energy loss

Muon reconstruction


S.Hassani Athens 05/03

A.Farilla Gallipoli 06/03

Muon backtracking

Backtracking from Muon System down to beam region through calorimeters taking into account E loss, multiple scattering and E loss fluctuations

E loss from parametrization (from calo measurement possible but risk of pollution from nearby particle)

Combination with inner detector track


pT(GeV)

•Pattern recognition perturbed by possible em shower accompagning high pT muon•Under study: Mu System pattern recognition redone using Inner Detector measurement

High pT efficiency


As pT decreases, the energy lost by the in calorimeters becomes comparable to its

energy, especially in the barrel

pT(GeV)

Inner Station Segments Tracks

•Under study :use of the Inner Station Segments could improve the identification efficiency up to 90%

Low pT efficiency


m(GeV)

J/→+-

m(GeV)

Z→ + -

H → Z Z→ +- + -

reconstruction Mass plots


OutlookA complete spectrum of algorithms are

availableOngoing developments:

o Cleaner modularization (toolbox)o Robustness (noisy/dead channels, misalignments)o Extend algorithms reach (e.g low pt, very high pt)o New algorithms

Next challenge: summer 2004, an ATLAS barrel wedge with all detectors in testbeam. Reconstruction and analysis using (almost) only atlas offline reconstruction.

Many thanks to my ATLAS colleagues, in particular for this talk: Nektarios Benekos, Frédéric Derue, Ambreesh Gupta, Michael Heldmann, Anna Kaczmarska, Jean-Francois Laporte, Jessica Leveque, Pavel Nevski, Frank Paige, Gilbert Poulard, Jean-Baptiste de Vivie, Silvia Resconi, Francesco Tartarelli, Monika Wielers

Documents

1 ATLAS reconstruction software David Rousseau- LAL/Orsay