mamma data analysis marco villa – cern 3 rd may 2011

MAMMA data analysisMarco Villa – CERN3rd May 2011

Outline

• Space resolution and clustering algorithm

• Ntuple cleaning and gain study

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µM space resolution (reminder)

• R12, Ar:CO2 85:15, ALTRO readout, 0 angle

• BAT tracks extrapolated to µM plane and matched to closest µM cluster (cog)

• Space resolution from gaussian fit over residual distributions

Observations:• Resolution larger than expected (~ 60 µm

with 250 µm strip pitch)• Side bumps at a distance ~ strip pitch

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Residual distributions (zoom)570 V mesh, 870 V drift 600 V mesh, 900 V drift

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Where do the bumps come from?• Are the bumps related to inefficiencies?• Are the bumps due to the pillar structure?

Procedure:• Build a graph containing all BAT tracks

extrapolated to the µM plane• Produce the same graph with BAT tracks

which residual is in the main gaussian peak• Repeat the exercise with the side bumps

events• All info from BAT; µM used for event selection

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All BAT tracks

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570 V mesh, 870 V drift 600 V mesh, 900 V drift

Main gaussian (low residual) events

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570 V mesh, 870 V drift 600 V mesh, 900 V drift

Cut on residuals:

180 µm

Side bumps (high residual) events

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570 V mesh, 870 V drift 600 V mesh, 900 V drift

Cut on residuals:

180 µm

Remarks…

• Uniform background of high residual events main gaussian tails and scattering

• Pillar structure does show in all plots inefficiencies and scattering

• High residual events concentrate around strip 36. This concentration is more evident at low voltages ???

Look at those events one by one

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Strip 36: this is what is happening

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More remarks…

• Channel 36 appears to be dead…• …however in many cases it works as

expected

Most probably bad connection problem

• In such cases one should merge neighbouring clusters into one supercluster

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high_gain/low_gain cleaning

• ALTRO ntuples contain information (Q, T) from both high gain and low gain channels

• Clean up the ntuple by picking up the most appropriate value, so that clustering and analysis codes will deal with univocal data

• high_gain/low_gain known a priori, but it is interesting to extract it from data

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Gain scaling factor

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570 V mesh, 870 V drift 600 V mesh, 900 V drift

16.100 0.004 16.113 0.002

Scaling factor channel by channel

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Conclusions & outlooks

• Need for new clustering algorithm• Gain scaling factor study completed• Values compatible with expectations• Scaling factor map will be used in the

ntuple clean up process

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