MdcPatRec Tracking Status Zhang Yao, Zhang Xueyao Shandong University

2 Outline 1.Main Drift Chamber (MDC) geometry 2.Tracking background 3.Tracking algorithm 4.Modification of algorithms 5.Tracking Performance 6.Summary

3 Main Drift Chamber (MDC) geometry Interaction point Cosθ=0.83 Cosθ= sense wire layers group to 11 super-layer cosθ from to 0.93 Cell is nearly square in shape

4 MDC Tracking software MdcPatRec MDC tracking software purpose –Precise momentum measurement –Efficiency find tracks short and not form IP Migrated from BaBar Drifit Chamber Tracking software Personpower –Zhang Xueyao of Shangdong University –Zhang Yao of Shangdong University

5 MdcPatRec Tracking algorithm Make Hits Track Finding : 2-D tracking Segment finding Track Finding : 3-D tracking MdcDigi MdcHit Segment Circle Helix

6 Tracking algorithm(1) --- Segment finding Pattern No.0 (2,0)(2,1)(2,2)(2,3)(2,4)(2,5) (1,0)(1,1)(1,2)(1,3)(1,4)(1,5) (3,0)(3,1)(3,2)(3,3)(3,4)(3,5) (0,0)(0,1)(0,2)(0,3)(0,4)(0,5) clockwise One of segment pattern One 4-hit segment pattern Map to a group-word to match exist pattern We have 8 4-hit patterns and 20 3-hit patterns in all

7 Tracking algorithm(2) --- Track finding Combine axial segments Circle fitting Combine stereo segments Helix fitting

8 Modification of algorithm 1.MDC Geometry Create a new interface through MdcGeomSvc to MdcPatRec reconstruction algorithm 2.Segment construction Change the segment construction 3.Stereo segment fitting Use new algorithm of fitting suit to MDC geometry 4.Track parameter conversion Convert BaBar tracking parameter to BesIII parameter Add some new features to tracking result.

9 Original segment finding algorithm –construct 8 bit group-word according to one reference wire by wire Id –But the super-layer1 ~ 5 don’t have equal numbers of cell in each layer –The neighbors in wire Id is not the neighbors in position –CAN NOT construct by wire id in super-layer 1~5 … … Modification of algorithm(1) --- segment construction clockwise (2,0)(2,1)(2,2)(2,3)(2,4)(2,5) (1,0)(1,1)(1,2)(1,3)(1,4)(1,5) (3,0)(3,1)(3,2)(3,3)(3,4)(3,5) (0,0)(0,1)(0,2)(0,3)(0,4)(0,5) Reference wire Efficiency of segment finding rely on “neighbor”s finding

10 Use φ (azimuthal angle) of reference wire get “neighbors” Take 2 reference wire –Layer 2 and layer 0: take No. 2 wire as reference wire –Layer 3 : take No. 4 wire as reference wire Verify the shape of segment Layer id Reference wires All segments can pass this test Almost all hits can form segment Modification of algorithm(1) --- segment construction

11 Modification of algorithm(2) --- stereo segment fitting Lost hits in stereo super-layer (especially inner chamber) Stereo layers don’t share rotate angle in super-layer of inner chamber Calculate approximate z0 and cot θ by “stereo angle of super-layer” Calculate position of every hits in super- layers, do a linear fit, get z0 and cot θ Boss V5.0.0New st. fitting algorithm

12 Modification of algorithm(3) --- Track parameter conversion Five helix parameters and error matrix Other parameters of track and hits converted for TDS ambiguity flag left - 1 => left 0 right 1 => right 1 don’t know 0 => don’t know 2 N stereo hits number of hit in stereo layer φ terminal φ of hit with max flight length MdcRecHit Status If hit is used in helix fitting Convert BaBar parameters to BesIII parameters and stored to TDS

13 Tracking Performance Use new MDC geometry –Rotate cell number of stereo layer changed –Number of wires in super-layer No. 6 changed Single track event generated by –SingleParticleGun –fixed in transverse momentum

14 Tracking Performance(1) --- New stereo fitting Boss V5.0.0New st fitting algorithm Efficiency of stereo super-layer tracking improved Momentum resolution, spatial resolution improved Inner chamber hits increase! Hit distribution on layers

15 Tracking Performance(2) --- spatial distribution μ - at pt = 1GeV/c Distribution of d0 σ=0.15 mm μ - at pt = 1GeV/c Distribution of z0 σ=0.8 mm d0: signed distance from the pivot to track in x-y plane z0: signed distance from the pivot to track in z direction Note: d0 and z0 fitted with double Gaussian d0 (cm)z0 (cm)

16 Tracking Performance(3) --- Tracking uniformity μ - at p t = 1GeV/c, cos θ [–1,1],  [0, 2π] θ of Mc Truth φ of Mc Truth θ after recon. φ after recon. φ (rads) θ (rads)d0 (rads) Tracks

17 Tracking Performance(4) --- Momentum resolution Note: Fitted with single Gaussian in each bin. μ - at p t = 1GeV/c Momentum resolution σ = 0.4% Momentum resolution Vs Pt (e -,μ -,π,p)

18 Tracking Performance(5) --- spatial residual μ - at pt = 1GeV/c spatial residual σ = 110μm spatial residual Vs Pt (e -,μ -,π,p) pt (GeV/c) Note: Fitted with double Gaussian in each bin.

19 Tracking Performance(6) --- Tracking efficiency for single track Efficiency vs Pt (e -,μ -,π,p) Have good efficiency with decrease of Pt Can keep efficiency with 99% at noise level of 20% with noise type1 and type2 95% pt (GeV/c) Noise level (%) Noise level type0: = C type1:  1/r type2:  1/r 2 Noise level (%) Eff. Efficiency vs Noise e - (type0,1,2) Efficiency vs Noise type0 (e -,k,π - )

20 Summary 1.Released in Boss 5.0.0, can be used by analysis codes. 2.Segment tracking and stereo fitting improved 3.Requirements satisfied from tracking point of view: Good momentum and spatial resolution : σ xy = 110 μm, σ( δ pt /p t ) = 0.4%. (muons) High tracking efficiency: efficiency > 99% for single track pt > 300MeV Good tracking performance at high noise level 4.Work with MDC calibration next 5.Need further checking with low momentum, not form IP, and multi-track event

21 Thank you!