MICE Collaboration Meeting, October 30 2003 A.Tonazzo, L.Tortora EMCAL optimization studies 1 Electromagnetic Calorimeter: optimization studies on simulation.

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Presentation transcript:

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 1 Electromagnetic Calorimeter: optimization studies on simulation A.Tonazzo and L.Tortora Roma3 Physics Department and INFN

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 2 Spaghetti calorimeter A reminder of the calorimeter design: from L.T.’s presentation at CERN on 29/03/03 Readout: square (or rectangular) cells connected to PMT photocatode by light guides shaped as Winston cones

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 3 Muon vs electron identification We have carried out simulation studies in G4MICE to optimize the mu/electron separation capabilities by varying:  sampling fraction, i.e. lead layer thickness: mm  readout segmentation, i.e. cell size: 3.75x3.75 cm 2, 3.25x3.25 cm 2, 2.5x2.5 cm 2, 2.5x4.0 cm 2 We only consider a “pattern- based” identification algorithm, i.e. detection efficiency in layers >1

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 4 Calorimeter signal, efficiency definition Detection efficiency is defined by a cut on signal above noise threshold: 3-4 p.e. PMT signalEnergy deposit “ digitization”: Light attenuation along fibers Winston cone collection efficiency Photocatode quantum efficiency

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 5 One caveat We don’t know the “final” beam profile at calorimeter entrance yet (cfr phone meeting of Oct.15 and mail by V.Palladino)  We cannot define the detector transverse size (and cost). Maximum affordable height is about 60 cm.  The optimization cannot be concluded: we will show the results as a function of muon energy and angle, which will have to be convoluted with the actual beam shape Simulated samples of 1000 particles just in front of the detector, with fixed energy (muons Ek=70,110,150,190 MeV, electrons Ek=190MeV) and angle (90 o,45 o )

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 6 Lead layer thickness = 0.5 mm Small cells give too small collected light (essential for timing information!) Efficiency for detecting low energy muons in layers >2 is low Rectangular cells increase efficiency for particles impinging at an angle

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 7 Lead layer thickness = 0.2 mm Efficiency for detecting low energy muons in layers >2 increases reducing lead thickness, but so does efficiency for electrons

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 8 Beam as in H.Wilson’s report on 30/07/03 numEvts 5000 RunMode Normal #SolDataFiles useFiles rfCellType none AbsorberType none ZOffsetStart SigmaX 50. SigmaXPrime 0.15 BunchLength 30. DeltaEoverE 0.1 AverageKineticEnergy NominalKineticEnergy TrackerOffsetZ 0. #muDoDecay 1 BeamProtonFraction 0. BeamPionFraction 0. BeamElectronFraction 0. (or 1.) SciFiMode Off TPGMode On TOF1Mode Off TOF2Mode Off TOF3Mode On Ckov1Mode Off Ckov2Mode On EMCalMode On VirtualMode On EMCalUseSpaghetti 1 EMCalFiberDiameter 1.0 EMCalLeadThickness 0.5 (0.3, 0.2) EMCalMotherLength 150 EMCalMotherRadius 300 EMCalSliceRadius 300 Beam upstream of calorimeter (H.W.) Iron shield in front of Cherenkov is not included in the simulation Preliminary!

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 9 Beam as in H.Wilson’s report on 30/07/03 Pb=0.5mmPb=0.3mmPb=0.2mm muons electrons  3.75x3.75  3.25x3.25 o 2.50x2.50 ● 2.50x4.00 Preliminary!

MICE Collaboration Meeting, October A.Tonazzo, L.Tortora EMCAL optimization studies 10 Summary and outlook We have carried out a simulation of the EMCAL in G4MICE to study the optimization of the design for best muon/electron separation: –Sampling fraction (lead layer thickness) –Readout segmentation (cell size) Only pattern has been considered: better identification algorithm should be studied (baricenter depth, etc.) Conclusions can be drawn when the beam description is available Also the definition of detector transverse size (and cost) depends on the beam profile