Input
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The LiC Detector Toy M. Valentan, M. Regler, R. Frühwirth Austrian Academy of Sciences Institute of High Energy Physics, Vienna Input Simulation Reconstruction Output The MATLAB program allows a fast evaluation of the optimal resolution for charged particles with uncorrupted data. Detector inefficiency and multiple scattering are included. Detector surfaces can be cylinders or planes. Track fitting uses the Kalman filter, a recursive least-squares estimator. It proceeds from the outermost layer towards the beam tube. Initialization of the track parameters with large errors Extrapolati on Detector loop Propagate track parameters, using a reference track and a linearized model Linear error propagation Add multiple scattering Update Compute weighted mean of extrapolated track parameters and measurement Compute local χ 2 statistic and accumulate total χ 2 Store final track parameters, error matrix and total χ 2 Track parameters ,, (according to the chosen multiplicity). The state vector is propagated to the beam tube, where it is transformed to variables similar to the DELPHI- convention ,z,, including spatial variables. Event loop Track loop By default the event loop first generates a vertex (uniformly distributed in a certain range). However, the user can enter the vertex positions (x 0 ,y 0 ,z 0 ), provided by an arbitrary vertex generator. The track model is a helix. Tracking includes multiple scattering. Track simulation Momentum variables Multiple scattering takes place on every massive barrier, using independent normal distributed random quantities (according to the Highland formula). A local cartesian coordinate system is used with one axis tangent to the track. Measurement of R and z' (according to stereo angle chosen) Strips, Pads or normal distributed uncorrupted data only Coordinates Arbitrary inefficiency without spatial or angular dependence Strip detectors (single layer and double sided; inner layer with any stereo angle) Pixel detectors (by crossing 2 strip detectors with strictly correlated inefficiency) Simulation of digital and normal distributed errors. The z dependence in the TPC can be used as an example for a template. Reconstructi on Pull quantities MC residuals (fitted - true) Monte-Carlo pulls Phi z theta beta kappa mean: -0.0014137 -0.020775 0.006437 -0.0035657 -0.0024358 std: 0.99745 1.0021 0.99926 0.99836 0.997 Pulls at innermost detector RPhi z u v mean: 0.0085271 0.0029371 -0.0095907 0.0042998 std: 0.99706 0.998 1.0031 1.0088 Chi^2 ndf: 21.8725 mean: 21.9226 At the beam tube Test statistics (sample log file, 10000 tracks) R, z – barrel region u,v - forward region Average number of degrees of freedom Barrel region Forward region 10000 track with 0.7454<2.3562 Up: Monte-Carlo residuals at the beam tube, computed from generated and fitted state vectors Left: Relative deviation p T /p T Right: Relative deviation p T /p T 2 10000 track with 0.49087<0.098175 Up: Monte-Carlo residuals at the beam tube, computed from generated and fitted state vectors Left: Relative deviation p T /p T Right: Relative deviation p T /p T 2 Scale factor relative to the barrel region: 50 Scale factor relative to the barrel region: 100 Track loop 20 Inner Tracker (IT) 21 22 Number of layers : 5 23 Radii [mm] : 90, 90, 160, 300, 340 24 Upper limit in z [mm] : 110, -90, 360, 640, 2730 25 Lower limit in z [mm] : 90,-110, -360, -640,-2730 26 Efficiency Rphi : 0, 0, 0.95, 0.95, 0 27 Efficiency 2nd layer (eg. z) : -1, -1, 0.95, 0.95, -1 28 Stereo angle alpha [Rad] : 10*pi/180 29 Thickness [rad. lengths] : 0.07,0.07,0.0175,0.0175, 0.14 30 error distribution : 1 31 0 normal-sigma(RPhi) [1e-6m] : 32 sigma(z) [1e-6m] : 33 1 uniform-d(RPhi) [1e-6m] : 50 34 d(z) [1e-6m] : 50 Number of events rsp. tracks Momentum and direction Vertex Simulation features Test features Output features Simulation Parameters Detector Description Frame Detector 1 Detector 2 • Coaxial cylinders - Stereo angle - in T •PC z dependent • Plane wheels - Coordinates defined by two angles • Arbitrary size and position • 2D measurement - single and passive layers steered by inefficiency • Strips or pads • Start parameters uniformly distributed in the defined ranges • Simulation features: - Multiple scattering - Measurement errors • Test features: - Pulls and MC- pulls - ² • Output features: - Histograms of pulls - Histograms of residuals - 6D cartesian, Harvester
description
20 Inner Tracker (IT) 21 22 Number of layers : 5 23 Radii [mm] : 90, 90, 160, 300, 340 24 Upper limit in z [mm]: 110, -90, 360, 640, 2730 25 Lower limit in z [mm]: 90,-110, -360, -640,-2730 26 Efficiency Rphi: 0, 0, 0.95, 0.95, 0 - PowerPoint PPT Presentation
Transcript of Input
The LiC Detector ToyM. Valentan, M. Regler, R. Frühwirth
Austrian Academy of SciencesInstitute of High Energy Physics, Vienna
Input Simulation
Reconstruction Output
The MATLAB program allows a fast evaluation of the optimal resolution for charged particles with uncorrupted data. Detector inefficiency and multiple scattering are included. Detector surfaces can be cylinders or planes.
Track fitting uses the Kalman filter, a recursive least-squares estimator. It proceeds from the outermost layer towards the beam tube.
Initialization of the track parameters with large errors
Extrapolation
Detector loop
Propagate track parameters,using a reference track and a linearized model
Linear error propagationAdd multiple scattering
Update
Compute weighted mean ofextrapolated track parameters and measurement
Compute local χ2 statistic andaccumulate total χ2
Store final track parameters, error matrix and total χ2
Track parameters ,, (according to the chosen multiplicity).The state vector is propagated to the beam tube, where it is transformed to variables similar to the DELPHI-convention ,z,, including spatial variables.
Event loop
Track loop
By default the event loop first generates a vertex (uniformly distributed in a certain range). However, the user can enter the vertex positions (x
0,y
0,z
0),
provided by an arbitrary vertex generator.
The track model is a helix.Tracking includes multiple scattering.
Track simulation
Momentum variables
Multiple scattering takes place on every massive barrier, using independent normal distributed random quantities (according to the Highland formula).A local cartesian coordinate system is used with one axis tangent to the track.
Measurement of R and z' (according to stereo angle chosen)Strips, Pads or normal distributeduncorrupted data only
Coordinates
Arbitrary inefficiency without spatial or angular dependence
Strip detectors (single layer and double sided; inner layer with any stereo angle)Pixel detectors (by crossing 2 strip detectors with strictly correlated inefficiency)
Simulation of digital and normal distributed errors.The z dependence in the TPC can be used as an example for a template. Reconstruction
Pull quantities
MC residuals(fitted - true)
Monte-Carlo pulls Phi z theta beta kappamean: -0.0014137 -0.020775 0.006437 -0.0035657 -0.0024358std: 0.99745 1.0021 0.99926 0.99836 0.997
Pulls at innermost detector RPhi z u vmean: 0.0085271 0.0029371 -0.0095907 0.0042998std: 0.99706 0.998 1.0031 1.0088
Chi^2ndf: 21.8725mean: 21.9226
At the beam tube
Test statistics (sample log file, 10000 tracks)
R, z – barrel regionu,v - forward region
Average number of degrees of freedom
Barrel region Forward region
10000 track with 0.7454<2.3562
Up: Monte-Carlo residuals at the beam tube, computed from generated and fitted state
vectors
Left: Relative deviation pT/pT
Right: Relative deviation pT/p
T2
10000 track with 0.49087<0.098175
Up: Monte-Carlo residuals at the beam tube, computed from generated and fitted state
vectors
Left: Relative deviation pT/pT
Right: Relative deviation pT/p
T2
Scale factor relative to the barrel region: 50
Scale factor relative to the barrel region: 100
Track loop
20 Inner Tracker (IT)21 22 Number of layers : 523 Radii [mm] : 90, 90, 160, 300, 34024 Upper limit in z [mm] : 110, -90, 360, 640, 273025 Lower limit in z [mm] : 90,-110, -360, -640,-273026 Efficiency Rphi : 0, 0, 0.95, 0.95, 027 Efficiency 2nd layer (eg. z) : -1, -1, 0.95, 0.95, -128 Stereo angle alpha [Rad] : 10*pi/18029 Thickness [rad. lengths] : 0.07,0.07,0.0175,0.0175, 0.1430 error distribution : 131 0 normal-sigma(RPhi) [1e-6m] :32 sigma(z) [1e-6m] :33 1 uniform-d(RPhi) [1e-6m] : 5034 d(z) [1e-6m] : 50
Number of events rsp. tracks
Momentum and direction
Vertex
Simulation features
Test features
Output features
Simulation Parameters
Detector Description
Frame Detector 1 Detector 2
• Coaxial cylinders - Stereo angle - in T
•PC z dependent
• Plane wheels - Coordinates defined by two angles
• Arbitrary size and position
• 2D measurement - single and passive layers steered by inefficiency
• Strips or pads
• Start parameters uniformly
distributed in the defined ranges
• Simulation features:- Multiple scattering- Measurement errors
• Test features:- Pulls and MC-pulls- ²
• Output features:- Histograms of pulls- Histograms of residuals- 6D cartesian, Harvester
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