MAMMA data analysis Marco Villa – CERN 3 rd May 2011

Outline Space resolution and clustering algorithm Ntuple cleaning and gain study 2

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µM space resolution (reminder) R12, Ar:CO 2 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 4

Residual distributions (zoom) 570 V mesh, 870 V drift600 V mesh, 900 V drift 5

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 6

All BAT tracks V mesh, 870 V drift600 V mesh, 900 V drift

Main gaussian (low residual) events V mesh, 870 V drift600 V mesh, 900 V drift Cut on residuals:  180 µm

Side bumps (high residual) events V mesh, 870 V drift600 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 10

Strip 36: this is what is happening 11

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 12

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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 14

Gain scaling factor V mesh, 870 V drift600 V mesh, 900 V drift   0.002

Scaling factor channel by channel 16

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 17