Status of the muon simulations

1. Status of the muon simulations Anna Kiseleva

2. Outline • Simulation environment • Muon software • geometry of the muon system (MuCh) • segmentation of the muon detector layers • clustering • Muon tracking • Results of the reconstruction • Simulation activities in India • FLUKA calculations • Next steps

3. Simulation environment • trunk (release Jun 09) of the cbmroot • background – central UrQMD at 25 AGeV • signal: ω • detector setup • muon magnet and muon field • pipe shielding • STS (standard) • MuCh (simple and modular design)

4. Detector system 20 20 20 30 35 100 cm STS 30 cm Total size: 405 cm total size of MuCh in release Apr 08 ~ 327 cm

5. Muon software: geometries and hit producer • Evgeny Kryshen (PNPI) • Mikhail Ryzhinskiy (PNPI & SPbSPU) • Alexander Zinchenko (JINR) • Test of software – Anna Kiseleva (U. Frankfurt)

6. Geometries of the MuCh simple design modular design modular design with straw tubes

7. Modular design of MuCh • Dead zones → missing hits • Overlaps → double hits

8. Automatic segmentation // Number of stations seg->SetNStations(6); // Set minimum allowed resolution for each station Double_t sigmaXmin[] = {0.08, 0.08, 0.08, 0.08, 0.08, 0.08}; Double_t sigmaYmin[] = {0.08, 0.08, 0.08, 0.08, 0.08, 0.08}; seg->SetSigmaMin(sigmaXmin, sigmaYmin); // Set maximum allowed resolution for each station Double_t sigmaXmax[] = {0.6, 0.6, 0.6, 0.6, 0.8, 1.}; Double_t sigmaYmax[] = {0.6, 0.6, 0.6, 0.6, 0.8, 1.}; seg->SetSigmaMax(sigmaXmax, sigmaYmax); // Set maximum occupancy for each station Double_t occupancyMax[] = {0.05, 0.05, 0.05, 0.05, 0.05, 0.05}; seg->SetOccupancyMax(occupancyMax);

9. Manual segmentation # General informationNumber of stations : 6# Station specificationNumber of channels : 128 128 128 128 128 128Number of regions : 4 4 3 3 3 3# Station 1Region radii [cm] : 19.6 30.8 47.6 70Pad width [cm] : 0.28 0.56 1.12 2.24Pad length [cm] : 0.28 0.56 1.12 2.24# Station 2Region radii [cm] : 26.6 41.8 64.6 96Pad width [cm] : 0.56 1.12 2.24 4.48Pad length [cm] : 0.56 1.12 2.24 4.48# Station 3Region radii [cm] : 33.6 52.8 120Pad width [cm] : 1.12 2.24 4.48 Pad length [cm] : 1.12 2.24 4.48 # Station 4Region radii [cm] : 42 66 150Pad width [cm] : 1.12 2.24 4.48Pad length [cm] : 1.12 2.24 4.48# Station 5Region radii [cm] : 51.1 80.3 182.5Pad width [cm] : 1.12 2.24 4.48Pad length [cm] : 1.12 2.24 4.48# Station 6Region radii [cm] : 69.3 108.9 247.5Pad width [cm] : 1.12 2.24 4.48Pad length [cm] : 1.12 2.24 4.48

10. Segmentationfor simple design of MuCh ~ 390 000 channels

11. Segmentationfor modular design of MuCh ~ 560 000 channels

12. Muon Tracking • Andrey Lebedev (GSI, LIT JINR) • Test of the tracking – Anna Kiseleva (U. Frankfurt)

13. μJ/ψ μω Muon tracking J/ψ→μ+μ– ρ0→μ+μ– J/ψ→μ+μ– ω→μ+μ– φ→μ+μ– ω→μ+μ–

14. Algorithm of the muon tracking • Tracking is based on • Track following • Kalman Filter (KF) • Different hit-to-track association techniques (nearest neighbor, branching, weighting) • Two main steps: • track finding • track selection

15. Global tracking TOF TRD MUCH STS Hit-to-track merging Global tracking L1 STS tracking STS tracking Global Tracking + TOF hit to track merging

16. Tracking performance Andrey Lebedev Events 1000 UrQMD at 25 AGeV + 10 mu in each event all muons Branching tracking Efficiency in %

17. Results of the full reconstruction ω→μ+μ- + central Au+Au collisions at 25 AGeV • Cuts: • χ2prim.vertex < 2.5 • ≤ 4 STS hits • χ2MuCh < 40 • ≥ 15 MuCh hits • Cuts: • χ2prim.vertex < 2 • ≤ 4 STS hits • χ2MuCh < 42.5 • ≥ 14 MuCh hits

18. Invariant mass spectrum ω→μ+μ- + central Au+Au collisions at 25 AGeV modular design simple design

19. Clustering CbmMuchDigitizeAdvancedGem* digitize = new CbmMuchDigitizeAdvancedGem("MuchDigitizeAdvancedGem", digiFile, iVerbose); digitize->SetSpotRadius(0.15); digitize->SetQThreshold(3); digitize->SetQMaximum(500000);digitize->SetNADCChannels(256);

20. Clustering CbmMuchFindHitsAdvancedGem* findHits = new CbmMuchFindHitsAdvancedGem("MuchFindHitsAdvancedGem", digiFile, iVerbose); Produces hits in GEM-like modules using different clustering algorithms. Clustering algorithms can be chosen by the switch SetAlgorithm(Int_t iAlgorithm) Several clustering algorithms are supported 0 – Simple with threshold=0 1 – Simple 2 – Ward (fuzzy clustering) 3 – Simple + Ward 4 – Divisive clustering 5 – Simple + divisive clustering The Default value is 1: Simple Clustering Algorithm // --- Set Algorithm for clustering findHits->SetAlgorithm(1); Divisive Clustering Method

21. Event display

22. Results of the full reconstruction with clustering ω→μ+μ- + central Au+Au collisions at 25 AGeV • Cuts: • χ2prim.vertex < 2 • ≤ 4 STS hits • χ2MuCh < 42.5 • ≥ 14 MuCh hits modular design of MuCh

23. Invariant mass spectrum ω→μ+μ- + central Au+Au collisions at 25 AGeV without clusters with clusters

24. Activities in India Students working on various topics.. • Partha(VECC), Hemen (GU) : Trigger, SIS100, physics simulation • Bipasha (CU): dynamic range simulation, J/Psi physics at FAIR • Arun: Geometry study • Manish, Irshad (Jammu U) EVO meet every Thursday: co-ordinator: Z. Ahammed

25. Trigger simulations • Partha Pratim Bhaduri (VECC, India)

26. Take 3 hits from the trigger station with one from each of the 3 layers & fit with st. line both in X-Z & Y-Z plane passing through the origin (0. 0) i.e. X = m0*Z ; Y=m1*Z Make all possible combinations Find χ2 & apply cut on both χ2X & χ2y Hit combination satisfying the cuts is called a triplet. Hits once used for formation of a triplet is not used further. Find m0 & m1 of the fitted st. lines Define a parameter α=√(m02+m12) Apply cut on α Trigger station (0,0,0) Magnetic field Trigger algorithm

27. Results • Input: • background – 80 000 minimum bias events at 25 AGeV Au+Au collisions • signal – J/ψ→μ+μ- in 1000 minimum bias events

28. Future plans • Prepare a look-up table for different values of cut parameters & corresponding values of background suppression factor & signal reconstruction efficiency. • Implementation of TRD in the present scheme. • Study pad resolution effect. • Formation of CbmMuchTrigger class to be run in chain.

29. Study of Manual Segmentation of MuCh • Arun Prakash (High Energy Physics Lab Department of Physics Banaras Hindu University Varanasi-221005)

30. Different segmentation schemes

31. Efficiency of the reconstructed muons from J/ψ

32. Future plans • To look into other parameters like invariant mass, acceptance plot, momentum distribution etc. • Add clustering • Study auto-segmentation

33. SIS-100 simulation • Charm simulations for SIS100 energies using HSD generator • Optimization of the muon geometry (N of stations/pad-sizes) • Arun (and Dr. Viyogi) will be at GSI working on this

34. FLUKA calculations • Anna Kiseleva (U. Frankfurt)

35. Radiation dose simulations (Denis Bertini) 13. CBM Collaboration MeetingMarch 9-13, 2009, GSI Darmstadt

36. Compact MuCh scoring planes target 20 20 20 30 40 cm • Absorber • material: • Fe • C • W

37. UrQMD events central mBias

38. mBias UrQMD original UrQMD UrQMD with rotated reaction plane

39. Next steps • Muon system optimization: number of detector layers and thickness of the absorbers • Optimization of the segmentation scheme • Implementation of the realistic detector parameters from the beam test • Radiation dose calculation with FLUKA for all detector systems