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RPC_sim Optimization w ith Positrons (+ Pions)

RPC_sim Optimization w ith Positrons (+ Pions). Burak Bilki Argonne National Laboratory University of Iowa. (S)DHCAL Meeting January 15, 2014 Lyon, France. DHCAL Simulation Strategy. GEANT4 → points in the gas gap with energy loss

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RPC_sim Optimization w ith Positrons (+ Pions)

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  1. RPC_sim Optimization with Positrons (+ Pions) Burak Bilki Argonne National Laboratory University of Iowa (S)DHCAL Meeting January 15, 2014 Lyon, France

  2. DHCAL Simulation Strategy GEANT4 →points in the gas gap with energy loss RPC_sim→ generates and distributes the charge over pads applies a threshold to determine pad hits Simulated data→pad hits RPC_sim tuning Tune major parameters to reproduce the muon response (José) Match number of hits per layer in the clean regions Tune charge at edges of chambers to reproduce tapering off of efficiency Tune the remaining parameters to reproduce the positron response (Kurt →Burak) Match mean and sigma of Nhits distributions, longitudinal profiles, density plots No tuning based on pion response

  3. The 4 RPC_sim Versions

  4. 3 Versions of the dcut weight weight A B 1 1 dcut suppresses avalanches close to others Can not be tuned with μ‘s ecut dcut dcut r r weight C (tanh(A*(r-B))+1)/2 1 r

  5. Tuning of dcut Values Use Positron distributions at 8 GeV Mean of hit distribution Sigma of hit distribution Density distribution (0÷8) Longitudinal profile Measure difference to measured distributions Define a χ2 Tuning Identify smallest χ2

  6. RPC_sim_3_A 2 exponential lateral charge distribution 1 dcut parameter χ2 Mean Sigma Density Longitudinalprofile Simulation index Best result fordcut = 0.1

  7. RPC_sim_3_A with dcut= 0.1 Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  8. RPC_sim_4_A 1 exponential lateral charge distribution 1 dcutparameter χ2 Mean Sigma Density Longitudinalprofile Simulation index No best solution

  9. RPC_sim_4_A with dcut= 0.05 Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  10. RPC_sim_5_A 1 Gaussian lateral charge distribution 1 dcutparameter χ2 Mean Sigma Density Longitudinalprofile Simulation index Best result for dcut = 0.18

  11. RPC_sim_5_A with dcut= 0.18 Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  12. RPC_sim_6_A Lateral charge distribution with 1(a+r2)3/2 1 dcutparameter χ2 Mean Sigma Density Longitudinalprofile No best solution Simulation index

  13. RPC_sim_3_B weight B 2 exponential lateral charge distribution 2dcutparameters 1 χ2 Mean Sigma Density Longitudinalprofile ecut dcut r Check 0.01/0.35 Simulation index Best solution with 0.01/0.35

  14. RPC_sim_3_B with dcut/ecut= 0.01/0.35 Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  15. RPC_sim_5_B 2 exponential lateral charge distribution 2dcutparameters χ2 Mean Sigma Density Longitudinalprofile Best result with 0.15/0.40 Simulation index

  16. RPC_sim_5_B with dcut/ecut= 0.15/0.40 Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  17. RPC_sim_3_C 2 exponential lateral charge distribution Smooth transition with 2 parameters χ2 Mean Sigma Density Longitudinalprofile weight C 1 Simulation index Best result with 20.0/0.225 r

  18. RPC_sim_3_C with A/B= 20.0/0.225 Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  19. RPC_sim_5_C 2 exponential lateral charge distribution Smooth transition with 2 parameters χ2 Mean Sigma Density Longitudinalprofile Best result with 40.0/0.40 Simulation index

  20. RPC_sim_5_C with A/B= 40.0/0.40 Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  21. RPC_sim Charge Generation Default Sample distribution measured with cosmic rays dE/dx based sampling Model the gas with heed++ pC μ # of primary ionizations βγ

  22. Charge Generation using βγ Sample βγ from cosmic muon spectrum Sample ionization location d inside gas gap from heed++ Generatecharge spectrum using empirical function βγ→ d →Q Q=5.46(1-tanh(60.8(d-0.1012)))

  23. RPC_sim_3_A with βγ 1 exponential lateral charge distribution 1 dcutparameter χ2 Mean Sigma Density Longitudinalprofile Best result with dcut = 0.01 Simulation index

  24. RPC_sim_3_A with dcut= 0.01 and βγ Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  25. RPC_sim_5_A with βγ 2 exponential lateral charge distribution 1 dcutparameter χ2 Mean Sigma Density Longitudinalprofile Best result with dcut = 0.01 Simulation index

  26. RPC_sim_5_A with dcut= 0.01 and βγ Data RPC_sim π+ e+ Not used for tuning Number of hits Number of hits e+ μ+ e+ Layer number Number of hits Density bin

  27. Conclusions Even though muons are well simulated, the simulation of positrons is not trivial The simulation of positrons depends strongly on the RPC_simversion, even though all reproduce the muons quite well The simulation of positrons depends strongly on the dcut parameter/implementation Treating the energy loss in the gap properly (using βγ) might be necessary Current implementation of ionization losses not yet successful Other approaches are being explored None of the digitizers satisfactory yet RPC_sim_5 with 2 Gaussians performs best (I have been told that OPAL never succeeded in simulating their high granularity gaseous HCAL response)

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