Calibration of the ATLAS Lar Barrel Calorimeter with Electron Beams

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Calibration of the ATLAS Lar Barrel Calorimeter with Electron Beams [email protected] 19/09/2007 •The ATLAS e.m. barrel calorimeter and status • Calibration strategy • Test-beam results

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Calibration of the ATLAS Lar Barrel Calorimeter with Electron Beams. [email protected]. 19/09/2007. The ATLAS e.m. barrel calorimeter and status Calibration strategy Test-beam results. The ATLAS Calorimeter. LAr Calorimeters: em Barrel : (| |

Transcript of Calibration of the ATLAS Lar Barrel Calorimeter with Electron Beams

Page 1: Calibration of the ATLAS Lar Barrel Calorimeter with Electron Beams

Calibration of the ATLAS Lar Barrel Calorimeter with Electron Beams

[email protected]

19/09/2007

•The ATLAS e.m. barrel calorimeter and status

• Calibration strategy

• Test-beam results

Page 2: Calibration of the ATLAS Lar Barrel Calorimeter with Electron Beams

endcap A endcap Cbarrelendcap A endcap Cbarrel• LAr Calorimeters:– em Barrel : (||<1.475) [Pb-LAr]– em End-caps : 1.4<||<3.2 [Pb-LAr]– Hadronic End-cap: 1.5<||<3.2 [Cu-LAr]– Forward Calorimeter: 3.2<||<4.9 [Cu,W-LAr]

• ~190K readout channels• Hadronic Barrel: Scintillating Tile/Fe calorimeter

The ATLAS Calorimeter

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Discovery potential of Higgs (into γγ or 4e± ) determines most requirements for em calorimetry:• Largest possible acceptance ( accordion, no phi cracks)

• Large dynamic range : 20 MeV…2TeV ( 3 gains, 16bits)

• Energy resolution (e±γ): E/E ~ 10%/√E 0.7% precise mechanics & electronics calibration (<0.25%)…

• Linearity : 0.1 % (W-mass precision measurement) presampler (correct for dead material), layer weighting, electronics calibration

• Particle id: e±-jets , γ/π0 (>3 for 50 GeV pt) fine granularity

• Position and angular measurements: 50 mrad/√E Fine strips, lateral/longitudinal segmentation

• Hadronic – Et miss (for SUSY)– Almost full 4π acceptance (η<4.9)

• Jet resolution: E/E ~ 50%/√E 3% η<3, and E/E ~ 100%/√E 10% 3<η<5 • Non-compensating calorimeter granularity and longitudinal segmentation very important to

apply software weighting techniques

• Speed of response (signal peaking time ~40ns) to suppress pile-up

Physics Requirements

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>22 X

0Lead/Liquid Argon sampling calorimeter with accordion shape :

Presampler infront of caloup to = 1.8

The E.M. Barrel ATLAS Calorimeter

middle

back

strips

Main advantages:LAr as act. material inherently linearHermetic coverage (no cracks)Longitudinal segmentationHigh granularity (Cu etching)Inherently radiation hardFast readout possible

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EM Barrel: Wheels Insertion P3

M-wheel inside the cryostat, March 2003

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EM Barrel: Wheels Insertion P3

ATLAS barrel calorimeter being moved to the IP, Nov. 2005

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EM Barrel: Wheels Insertion P3

ATLAS endcap calorimeters installation, winter-spring 2006

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Commissioning – The Road to Physics

2005 2006 2007 2008

1: Testbeams 2: Subdetector Installation, Cosmic Ray Commissioning

3: First LHC collisions

4: First Physics

Sommer ’07: Global cosmic runwith DAQ of ATLAS detector

Final cooldown

~30 k events in barrel

>03/07weekly cosmic data takingtogether with Endcap A~100 k events

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Test-beam 2002: Uniformity: 3 production modules scanLinearity: E-scan 10 -245 GeV at eta=0.69 phi=0.28

thanks to special set-up to measure beam energy:linearity of beam energy known to 3 10-4 and a constant of 11 MeV (remnant magnet field)

Test-beam 2004 : (not covered here)Combined test beam full slice of of ATLAS detector

final electronics+ DAQ

Test beam Setups

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LAr electronic calibration

F = ADC2DAC DAC2A A2MeV fsamp

Scan input current (DAC)Fit DAC vs ADC curve with a second order polynomial, outside of saturation region

ADC MeV conversion

Every 8 hours

All cells are pulsed with a known current signal:

A delay between calibration pulses and DAQ is introducedThe full calibration curve is reconstructed (Δt=1ns)

response to current pulse

Every change of cabling

pedestals and noise

Cells are read with no input signal to obtain:

PedestalNoiseNoise autocorrelation (OFC computation)

Every 8 hours

PADCa F Ej2

1

5

1iiij

j

Energy Raw Samples

Optimal Filtering Coefficients

PedestalsADC to GeV

Ampl

itude

( E

nerg

y)

Pedestal subtracted

The ionization signal is sampled every 25 ns by a 12 bits ADC in 3 gains. Energy is reconstructed offline (online in ROD at ATLAS).

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Samp.frac. depends on shower composition.Many short-ranged, low-energy particles are

created and absorbed in the Pb (much higher cross-section for photo-electric effect in Pb than LAr)Sampl. fract. decreases with depth and radius as such particles become more and moretowards the tails of the shower

On the Calibration of longitudinally Segmented Sampling Calorimeter

act

pasactsampaccrec E

EE1/fd ,E d E

Shower

Use one sampling fraction forall compartments apply energydependent correction

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Sampling Fraction Correction

Correction to sampling fractionin accordion:- intrinsic E-dependence of s.f.- I/E conversion- out-of-cluster (fiducial volume) correction

acc100Esamp

rec E f d(E)1 E

1%

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AccordionCalorimeter

Cryostat Walls

Presampler

e-

• Accordion Sampling Calorimeter– Segmentation in three longitudinal

compartments• Presampler • (Significant) amount of dead material upstream

(~2-3 X0)– Cryostat wall, solenoid, …

• Calibration Strategy:– Use MC to understand effect of upstream

material– Validate MC with test-beam data– Derive calibration constants from MC– Cross-check by applying calibration to test-

beam.

Material in front of the Accordion in ATLAS

Correction for Dead Material Losses

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Opt. LinearityOpt. Resolution

A simple weight is not sufficient!

DM Correction using the Presampler I

Assume for a moment perfectly calibrated Lar calorimeter:

? E a E PSrec DM

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Sampling fraction for PS can not be calculated as for sampling calorimeter

Slope is smaller: Secondary electrons:• only traverse part of dead material• are created in PS• are backscattered from calorimeter

Offset not zero:In the limit of hard Bremsstrahlung, no electrontraverses the pre-sampler

DM Correction using the Presampler II

Showere-

e+

e-

Presampler Accordion

Dead Material

Dead Material

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PSrec E b a E Upstream

DM Correction using the Presampler II

Offset accounts for energy loss by particlesstopping before PS - Ionisation energy loss - low-E Bremsstrahlung photons - photo-photonuclear interactions

Weight accounts for energy loss (partly)traversing the DM and the PS

energy dependent

e-

e+

e-

Presampler

Dead Material

Dead Material

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• Significant amount of inactive material (~0.5 X0)– Electronics boards and cables immersed in LAr– Dependence on impact point

• Shower already developed (about 2-3 X0 before Accordion)

• Best correlation between measured quantities and energy deposit in the gap:

• Empirically found

e-

e+

e-

Presampler

Dead Material

Dead Material

DM Correction between PS and Strips

E E c E StripPSPS/striprec

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Showere-

e+

e-

Presampler Accordion

Dead Material

Dead Material

• Good linearity and resolution achieved• Constants depend on impact point (upstream material) and on the energy.

– Can be parameterized.• Constants are derived from a MC simulation of the detector setup.

Final Calibration Formula

Offset: energy lost by beam electron passing dead material in front of calorimeter

Slope: energy lost byparticles produced in DM (seeing effectively a smaller amount of dead material) in front ofcalorimeter

acc100Esamp

stripsPSPSrec E f d(E)1E E c(E) E b(E) a(E) E

Correction to sampling fractionin accordion:- intrinsic E-dependence of s.f.- I/E conversion- out-of-cluster correction

+Eleak

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Data MC Comparison – Layer Energy Sharing

Most difficult: correct description of DM materialBand due to uncertainties in material estimation

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PS

Strips

Middle

Back

Data

MC

Deposited energies = f() in the PS and in the 3 calorimeter compartments before applying the correction factors a,b,c,d

Excellent Data / MC agreement

in all samplings

Data MC Comparison – Layer Energy SharingMean visible energy for 245 GeV e-

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Data/MC Comparisons – Radial Extension

•Good descriptionalso for asymmetry

First layer:

MC uncertainty shownbut not visible

We do not know why thisIs, can be - detector geometry ?- beam spread ? - cross-talk - G4 physics problem ?

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Data/MC Comparisons – Total Energy Distribution

Need to fold inacceptance correctionfor electrons havinglost large energyin „far“ material (from beam-linesimulation)

MC uncertainty contains variation of „far“ material: air in beam-line and beam-pipe windows

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Linearity Result

within 0.1% for 15-180 GeV, E=10 GeV 4 per mil too low, reason unclear…

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Systematics

..within 0.1%

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Resolution Result

Good resolution while preserving good linearity

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Resolution is much better described innew G4 version !

PreliminaryPhi-impact correctionnot applied

Data MC comparison - Resolution

G4.8 hascompletely revisedmultiple-scattering

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nA/MeV 14.4f:G4.8nA/MeV 16.0f:G4.7

I/E

I/E

nA/MeV 15fI/E

Current to Energy Factor in ATLAS Barrel EM Calorimeter

From calculation using field-Maps:

G. Unal: ATLAS-SIM 09/05

From comparison of data and MC:

Much better understanding of absolute energy scale from first principles !(Some effects missing in simulation and calculation,e.g. recombination effect in Lar)

nA/MeV 14.2fI/E

Assuming calo is simple condensatorand knowing Lar drift time:

electrodePb absorber

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Calibration Parameter vs Eta

,, E=245 GeV e-, scan in

acc100Esamp

stripsPSPSrec E ),(f1E E h)c(E, E )b(E, a(E) E

E

Internal ATLASmodul numberrelated to

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Uniformity barrel resultsModule P13 Module P15

0,44% 0,44%

0,7-0,9% 0,7-0,9%

245.6 GeV 245.7 GeV

ResolutionU

niformity

TDR requirement:0.7%

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ConclusionPrecise calibration of em calorimeter need to take em physics effects - variation of sampling fraction with depth energy - dead material correction

This is only possible using a MC and requires excellent description by MC

As an alternative calibration parameters can be extracted using a fit(based on correct functional form of calibration formula)

In ATLAS presently both strategies are followed

In the test-beam it has been demonstrated:

1) MC describes data well2) Calibrations parameters extracted from MC, lead to linearity of 0.1% and optimal resolution (~10% 1/sqrt(E)) - 0.44 % global uniformity over one module (shown for 2 modules)

MC-based calibration presently extended to hadron calibration Challenging since MC much less reliable

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Accordion:24.5 X0 thick

Upstream fraction vs E,eta

Impact point: =0.4, =0

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Calibration Constants - 2004 RunDependence on upstream material

• All parameters rise when material is added– More energy lost upstream, later part of the shower is measured.

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Beam energy accuracy

• Procedure works also for larger amounts of upstream matter– Linear within the beam

energy accuracy

Sensitivity to DM Material

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CTB simulation

• Resulting error within 1% for E >50 GeV• 2% for E >50 GeV

Apply calibration constants derived for slightly different setup– Upstream material overestimated by 0.3 X0

- Upstream material underestimated by 0.3 X0

Sensitivity to DM Material

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Longitudinal leakage

Linearity: small leakage contribution, use of the average value only.

LeakCaloLeakage EEE

Uniformity: correlation of leakage/energy in the back E3

If no leakage parameterization, becomes a dominant effect for uniformity (0.6% contribution)

33Leak

Leak EβαEη,EE

Leak

Leak

EE

3E

= 1

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Understanding of the uniformity

Uniformity over 300 cells < 0.5 %

Over < 0.8 region (181 cells)• Correlated non-uniformity P13/P15: 0.29 % • Uncorrelated non-uniformity : 0.17 % (P15) and 0.17 % (P13)

Source Contribution to uniformityMechanics: Pb + Ar gap < 0.25 %Calibration: amplitude + stability < 0.25 %

Signal Reconstruction + inductance < 0.3 %

modulation + longitudinal leakage < 0.25 %

0.5 %

P13 0.34% rmsP15 0.34 % P13/P15 0.24%

From ATLAS physics TDR

Energy scaleP13/P15 ~ 5 10-4 !

x = 0.8 x 0.15 181 cells

Nor

mal

ized

en

ergy

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Data/MC Comparisons – Layer FractionsE=50 GeVE=10 GeV

• Fraction of under electron peak can be estimated by looking at late showers: E1/(E2+ E3)• Pions depositing most of energy in Lar deposit large fraction electromagnetically, but shower later than electrons• f MC-pion + (1-f) MC-electron gives good description of MC• Effect of pion contamination on reconstructed energy can be estimated from simulated energy distributions -> effect is negliable• shift of energy distribution with/without E1/(E2+ E3) is negliable

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Correlation of passive material with Eps

This differencecauses thelinearity problem for

mipPSPSPS w 6.0)(Ew

Indeed 1 MIP !