Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Detector description for fast simulation as used by the Vienna Fast Simulation.

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Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Detector description for fast simulation as used by the Vienna Fast Simulation Tool for Charged Tracks (“LiC Detector Toy”)

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Why fast simulation? Achieve quick response to local detector modifications, but not intended to replace full simulation –Doesn’t make sense to try detector modifications using the full simulation and reconstruction chain MOKKA/MARLIN (distributed among different institutes, would take months) –Use full simulation to make an ‘ultimate check’ on a promising detector modification Simple to use, even by non experts Doesn’t demand much preparation time Quick results, can be installed on a laptop Effect of various detector modifications can quickly be resolved Human readable, simplified detector description should be standardized to make results comparable

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan The Vienna Fast Simulation Tool Simple, but flexible and powerful tool, written in MatLab Detector design studies –Geometry: cylinders (barrel) or planes (forward/rear) –Material budget, resolutions, inefficiencies Simulation –Solenoid magnetic field, helix track model –Multiple scattering, measurement errors and inefficiencies –No further corruption, therefore no pattern recognition –Strips and pads, uniform and gaussian errors (in TPC with diffusion corr.) Reconstruction –Kalman filter –Optimal linear estimator according to Gauss-Markov (no corruption) –Fitted parameters and corresponding covariances at the beamtube Output –Resolution of the reconstructed track parameters inside the beam tube –Impact parameters (projected and in space) –Test quantities (pulls, χ 2, etc.)

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Subsequent Vertex Fit Fitted tracks as input to the VERTIGO/RAVE toolkit; Interface is the Harvester‘s standard CSV format; Successfully tested with 10- and 1000-prong events. Tracks from barrel region Tracks from forward region

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Basic detector description (VTX, SIT) Description Beam pipeVertex detector (VTX)Silicon Inner tracker (SIT) Name XBTVTX1VTX2 VTX4VTX5SIT1SIT2 R [mm] 14 [1] 16 [1] 26 [1] 37 [1] 48 [1] 60 [1] 160 [3] 270 [3] z max [mm] 50 [1] 120 [1] 380 [3] 660 [3] z min [mm] -50 [1] -120 [1] -380 [3] -660 [3] Stereo angle (π/2) [1] 0°/90° [3] d [%X 0 ] [2] 0.5 [4] Pitch [μm] passive24x24 [2] 50/50 [3] Remarks Pixels [1] Double-sided strips [3] [1]: Detector Outline Document (DOD) for the LDC, Aug [2]: M. Vos: Pixel R&D at IFIC Valencia, SiLC Meeting, Torino, Dec [3]: V. Saleviev, A. Savoy-Navarro, M. Vos: Silicon Tracking, ILD Meeting, Zeuthen, Jan [4]: M. Vos: The silicon tracker elements, SiLC phone conference,

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Basic detector description (TPC, SET) Description Inner wall196 pad rings Outer wall Silicon External Tracker Name XTPCW1TPC1-TPC196 [1] XTPCW2SET1SET2 R [mm] 300 [4] 300 [4] – 1580 [4] 1580 [4] 1600 [3] 1610 [3] z max [mm] 2160 [4] 2500 [3] z min [mm] [4] [3] Stereo angle (π/2)0°/90° [3] d [%X 0 ] 1.16 [7] (per layer)1.51 [7] 0.65 [3] Errors [μm] σ² = σ σ 1 ²  sin²  + c Diff 2  6mm/h  sin  ∆z[m], h = padrow pitch [5] passive σ 0 [μm]σ 1 [μm]c Diff [μm/√m] passive Double- sided strips 50 / 50 [3] RΦRΦ50 [5] 900 [5] 53 [5] z15 [5] 0580 [6] [5]: R. Settles: communication, [6]: V. Lepeltier: Private communication, 2006 [7]: MOKKA Database,

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Basic detector description (forward) = 7 discs Description Forward Tracker Discs Pixels Forward Tracker Discs Strips Name FTD1FTD2FTD3FTD4FTD5FTD6FTD7 z [mm]  220 [3]  350 [3]  500 [3]  850 [3]  1200 [3 ]  1550 [3 ]  1900 [3] R max [mm] 140 [3] 210 [3] 270 [3] 290 [3] R min [mm] 29 [3] 32 [3] 35 [3] 51 [3] 72 [3] 93 [3] 113 [3] Coord. angle  1 /  2 [°] 0/90  10 d [%X 0 ] 0.3 [7] Pitch [μm] 35x35 [3 ] 35/35 [3 ] Remarks Pixels Strips

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Display of basic detector description θ θ 2 = 32.5°: Barrel hits only

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Display of basic detector description

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Basic Setup = 7 fwd. discs Basic Setup: –as seen in the basic detector description Modifications of forward discs: –500 μm Si (0.50% X 0 ) instead of 350 μm Si (0.35% X 0 ) –50 μm pitch instead of 35 μm pitch Evaluation –Plot RMS of ∆p t /p t 2 for p t = 1, 3, 5, 10, 15, 20, 25, 35 GeV θ = 5-8°, 8-11°, 11-14°, 14-17° –1000 tracks per p t and θ range

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 1 (basic Setup), results 350 μm Si 500 μm Si 35 μm pitch 50 μm pitch

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Conclusions Study 1 Study 1: Basic Setup (7 fwd. discs) Optimization is strongly conditioned by the range θ = 5 - 8° (no hits in TPC and FTD1) 500 μm Si instead of 350 μm Si: –15% resolution loss for low p t, no change for high p t 50 μm pitch instead of 35 μm pitch: –20% resolution loss for low p t, 30% resolution loss for high p t For larger angles (θ > 8°) TPC starts to dominate the momentum resolution rather soon, thus the optimization must essentially cover the range at small angles and the transition region –accurate measurements of the TPC available; inclusion of the VTX, but loss of outer forward chambers –however, in the transition region the measurements inside and outside the TPC’s inner wall are quite decoupled due to multiple scattering (large scattering for small θ)

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Setup 2 = 8 fwd. discs Same modifications and evaluation as before Basic setup + additional forward disc at z = 2160 mm (affects only θ = 5-8°)

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 2 (Setup 2), results 350 μm Si 500 μm Si 35 μm pitch 50 μm pitch

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Conclusions Study 2 Setup 2 (8 fwd. discs): additional disc at z = 2160 mm Clear improvement of momentum resolution of tracks missing the TPC –(Those tracks also miss the Vertex Detector and the innermost Forward Pixel Disc!) –15% gain for low p t –20% gain for high p t Same impact of material budget and pitch as before –therefore adding an 8 th disc is not yet an “overinstrumentation”

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Setup 3 = 9 fwd. discs Same modifications and evaluation as before Basic setup => forward discs FTD4 - FTD7 replaced by 6 discs, distributed evenly in the range z = 710 – 2160 mm

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 3 (Setup 3), results 350 μm Si 500 μm Si 35 μm pitch 50 μm pitch

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Conclusions Study 3 Setup 3 (9 fwd. discs): FTD4-FTD7 replaced by 6 discs, distributed evenly in the range z = 710 – 2160 mm Overinstrumented when using 500 μm Si! –No resolution gain compared to Setup 2 Material budget starts to dominate even when using 350 μm Si Using 8 forward discs seems to be the best choice!

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Optimizations of Setup 2 From now on: only 350 μm Si (0.35% X 0 ) and 35 μm pitch Best choice up to now: Setup 2 –Setup 2: Basic setup with additional 8 th forward disc at z = 2160 mm –Yielded improved momentum resolution for tracks NOT hitting the TPC, with an additional measurement at higher z (bigger lever arm) –But: tracks with θ < 8° miss FTD1! 1 st optimization: –Setup 4 (8 fwd discs): Reduce inner radius of FTD1 from 29 mm to 19 mm to cover tracks with θ down to 5° (ignoring radiation problems resulting in higher inefficiency, cluster size, etc.) 2 nd optimization: –Setup 5 (9 fwd. discs): Setup 4 => add one more forward disc with even bigger lever arm at z = 2290 mm (just in front of ECAL at z = 2300 mm [4] )

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Optimized Setups 4 and 5 Setup 2: Setup 5: Setup 4:

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Further optimization of Setup 2 3 rd optimization: –Setup 6 (8 fwd. discs): Setup 4 => rearrange the detector positions such that they are distributed according to a cosine distribution –i.e. more discs at both ends, less discs in the middle –No further modifications (material, pitch). Evaluations as before Setup 4: Setup 6:

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 4 (Setups 4, 5, 6), results Setup μm Si, 35 μm pitch (for comparison) Setup 4 R min (FTD1) adjusted Setup 5 additional 9 th disc Setup 6 8 discs cos-distributed

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Conclusions Study 4 Optimization of Setup 2 (8 fwd. discs) –Setup 4 (8 fwd. discs): R min of FTD1 adjusted, neglecting radiation problems clear improvement for tracks with θ < 8°: –7% resolution gain for low p t –25% resolution gain for high p t –Setup 5 (9 fwd. discs): add. disc at z = 2290 mm further improvement for tracks with θ < 8°: –15% resolution gain for low p t –10% resolution gain for high p t –Setup 6 (8 fwd. discs): cos-distributed no more improvement in the forward region

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 5: Optimization of the SIT The SIT links the two main detector modules –Precise momentum measurement in TPC –Precise position measurement in VTX Can the detector resolution be improved by optimizing the SIT? –Compare four setups with different positions of the SIT’s layers –Plot Δp t /p t 2 and the 3D impact in dependence of p t for four θ ranges

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 5: Optimization of the SIT

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 5: Relative error of Δp t /p t 2

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 5: 3D impact

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Conclusions Study 5 Shifts and removal of SIT do NOT change momentum and position resolution –Momentum determined by TPC –Position determined by Vertex Detector –SIT (in it’s current setup) does not add information to the fit Needed for pattern recognition???

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 6: Contribution of the SIT Study 5: Momentum and position resolution unaffected by modifications of the SIT Which properties does the SIT have to have to contribute to the detector resolution? Modify two properties to find out: –Decrease strip distance while keeping original thickness –Decrease thickness while keeping original strip distance

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 6: Strip distance

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Study 6: Thickness

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Conclusions Study 6 Modification of the thickness does not show a contribution –Material budget does not influence the resolution At a strip distance of about 10 – 15 µm the SIT starts to contribute to the position measurement, but only for high momentum. Note: Vertex detector with thin layers (maintains SIT information) and quite big error (just digital resolution, no clusters) –Even the SIT’s contribution to the position measurement would vanish when using a more precise vertex detector

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan Conclusions Study 6 Optimization of the SIT seems to be the most difficult task –Momentum measurement dominated by TPC –Position measurement dominated by the vertex detector –Both hardly affected by modifications of the SIT This example showed, how fast simulation can point out where optimizations make sense –Doesn’t make sense to try detector modifications using the full simulation and reconstruction chain MOKKA/MARLIN (distributed among different institutes, would take months) –Use full simulation to make an ‘ultimate check’ on a promising detector modification Fast simulation can deliver important input for full simulation!

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan DETECTOR DESCRIPTION FOR FAST SIMULATION BASIC IDEA: –Parallel to full detector description, define a basic detector description, limited to cylinders in the barrel and planes in the forward region. –It should serve as a starting point for local detector studies of the trackers. –Without agreement on a common starting version results of different detector optimization studies will never be comparable (neither with fast simulation, nor with MOKKA/MARLIN). –Increases flexibility and speed, and yields useful and comparable results, which may be validated by full simulation once in a while. OPTIMIZATION MINI-WORKSHOP (“brainstorming jamboree”) in Vienna, March 2008 (participation by invitation only): –Suggest to set up a small ad-hoc working group (a few key persons) for LDC/ILD optimization, based on fast simulation. Goals: agree on a basic detector description for fast simulation make it also readable for MOKKA (validitation with corrupted data)?!

Vienna Fast Simulation LDT Munich, Germany, 17 March 2008 M. Regler, M. Valentan The Vienna Fast Simulation Tool for charged tracks (LDT). Info on the web: ==> lictoy Acknowledgements The software was designed and developed by the Vienna ILC Project Group in response to encouragement from the SiLC R&D Project. Efficient helix tracking was actively supported by W. Mitaroff. Special thanks are due to R. Frühwirth for the Kalman filter algorithms used in the program.