Adil Khan Kyungpook National university Korea-Japan Joint ScECAL Group Meeting kobe University Japan 3rd September 2010 FNAL Beam Test Analysis
Work Layout • Introduction • Prototype Beam Test Layout • Beam Test • Preliminary Results of BT 2008 • Preliminary Results of BT 2009 • Plan
Beam Test • The 2nd ScECAL ProtoType • The 2nd prototype is4 times larger than the DESY BT module. • (18 x 18 cm, 30 layers) • Fully adopt with extruded scintillator. • Precise positioning of MPPC and Fiber • Monitoring system • MPPC : 2160readout channel. Scintillator_ Based Ecal ScECAL • Extensive test beam campaign • FNAL: 2008, 2009 • Wide variety of beam energies and • particle species • 1 GeV to 60 GeV • muons, e±, π± • ScECAL, AHCAL, TCMT Technologies
Pedestal data check 2008 • Using Gaussian Function. • Fitting Function : • gauss->µped± 3σped Collect the Pedestal mean and Sigma Values of all the Run numbers • use the pedestal data for the MIP Calibration constant
Sigma and mean values vs run number Total 120 Run Number were checked. Pedestal sigma and mean Values from the fitting shows The stability of pedestal Distribution.
MIP Selection Event selection Example: For X-Layer i, Strip j →Check a hit of the strip j on other X-layers excepting i .(total 14 layers) MIP event Hit Definition: ADC >ADCped + 3σped Fitting MIP Distribution • Gaussian convoluted landau distribution function Strip =j Layerx !=i Muon Event Recorded in Online Monitor
Mip Signal 32GeV for 2008 data Fitting all the channels • Using Gaussian Convoluted-Landau Function The fitting for the entire channel work well Even the bad channels. Chi2/NDF Result from Fitting
MIP Calibration Constant 2008 MIP Response Mapping • The average of ADC Counts/MIP ~160 and RMS is ~31 • The fluctuation is about 20%, which is coming from variation of the Light yield.
1 Temperature Correction ScECAL Temp Vs HcalM3temp ScECALTemp(C) hCALM3Temp(C) Splitted into 4 parts , in order to make the Temp distribution for linear Fit 2 3 4
Temperature Variation of MIP Constant Total 16 MIP runs were used to get the temperature correction factor . The variation of temperature difference between MIP runs is about ~ 1.4 0C This shows temperature Effect seems to be very small or almost negligible Correlated Temperature=P0* hCALM3 + P1 MipConst and Temperature Obtained Run by Run.
Temperature Coefficient • Used Linear fitting in Order to get the Temperature Correction Factor. • MipConstand corr-Temperature Obtained Run by Run for every strip. • Temperature correlation depends on channel by channel Mip Const Temp(C)
Energy Distribution of each point Without Temp Correction With Temp Correction With 2009 Temp data Correction 3GeV 6GeV After using Temperature Correction Factor, the result is almost same, No significant difference. But 2009 data temperature correction factor shows some change. The wide shift in temperature is due to the damage in air conditioning system during 2009 data taking. 12GeV 16GeV 25GeV 32GeV
Resolution and Linearity The lines are the fitting results with the function of : Without Temp Correction With Temp Correction With 2009 Temp data Correction 3 GeV 6GeV # of counts 16GeV 12GeV 25GeV 32GeV Energy Deposit in ScECAL (MIPS) Sig/E 1/sqrt(E) In terms of using Temperature Correction factor seems not remove the large the large constant term for 2008 data
Linearity Deviation As, the temperature correction doesn’t show any big difference The Deviation from Linear behavior of the energy spectrum is less than 5%
First look into 2009 data Mip constant Correlation Checked in similar way the 2009 data Mip constant correlation between 2009 data Runs at low temperature and high Temperature Runs with 2008 data.
Plan & Schedule • Short Term Analysis (1~2 weeks) • Proceed with the 2009 data for theResolution, Linearity.. • Detail Analysis (~2 months) • Optimize all types of selection cut (Mip, electron) • Temperature Correction for 2009 data • Saturation Correction • Geant4 Simulation for beam test • Evaluation of Systematic Uncertainty (1~2Months)
Chi2/NDF Result from Fitting Pedestal Check 2009 data
MuonRun 32GeV, Layer1 2009 data Mip Distribution of Low Temp Runs Mip Distribution of High Temp Runs Fitting all the channels • Using Gaussian Convoluted-Landau Function
Chi2/NDF Result from Fitting Chi2/ndf of High Temp Runs Chi2/ndf of Low Temp Runs
Euquation Used for Temp Effect : Esum += (slope*Nominal Temp+offset) /(Slope * HM3Temp + offset)*En Tnominal = 25 0C