CMS Muon Meeting. HLT DT Calibration. (on Data Challenge Dedicated Stream) G. Cerminara N. Amapane M. Giunta

Transcription

1 CMS Muon Meeting HLT DT Calibration (on Data Challenge Dedicated Stream) G. Cerminara N. Amapane M. Giunta

2 Overview Goal: develop the tools for HLT calibration for DTs in ORCA Calibration algorithms + tools to handle/apply calibration constants For the complete DT system Today s presentation: a preliminary exercise! Playground to develop and understand the tools in ORCA Not supposed to be realistic! Current assumptions: T known from test pulses Alignment known from optical measurements (decouple alignment and calibration for the time being) G. Cerminara CMS Muon Meeting, Aachen, April 9, 4

3 DT Calibration TDC synchronization (T pedestals) Not considered here Determination of drift velocity A) Using meantimers B) Using residuals of reconstructed segments Available input: low lumi:.7 KHz L1 output (1.3 KHz in barrel) Hz/chamber single µ threshold U.G., Calibration Workshop, 7/11/3 ~minutes to collect O(1 3 ) segments/sl (depending on available bandwidth) G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 3

4 Calibration in ORCA DT calibration stream (included in DC4 production) Contains a copy of the DT digis for events with one reconstructed µ Facilities implemented in ORCA: Handling of per-wire digi offset To allow per-wire T subtraction Handling of calibration constants Interface to a fake condition database serving per-wire constants RecHit reconstruction, different algorithms: Using GARFIELD parametrization (CIEMAT) Accounts for non-linearity and dependence on θ, B Using constant v d and σ (tunable on a per-wire basis) G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 4

5 Example of Miscalibration Let s imagine a 3% v d miscalibration RHit residual Entries 6198 Mean.36 RMS e+4 / 77 Constant 1.45e+4 Mean Rφ RecHit Residual x Rec x µ true Sigma x (cm) G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 5

6 3% Miscalibration (cont.) RZ,wheel RZ, wheel ±1 RHit residual Entries 187 Mean.3 RMS / 71 Constant 91.6 Mean.343 Sigma.351 RHit residual 1 8 Entries Mean.31 RMS / 77 Constant 166 Mean.316 Sigma G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 6

7 RHit residual Entries 7143 Mean.1553 RMS / 77 Constant Mean.15 Sigma.8963 Miscalibr. (cont.) RZ, wheel ± RecHit Res x (cm) G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 7

8 Calibration Exercise Starting from mis-calibrated constants, perform segment reconstruction Compute meantimers with SL granularity Get v d and resolution Write calibration table (for the full detector) Use this table to check the residuals obtained on calibrated RecHit G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 8

9 Calibration Results RHit residual Rφ RecHit Residual Entries 6198 Mean.479 RMS e+4 / 77 Constant 1.661e+4 Mean.5418 Sigma x (cm) G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 9

10 Calibration Results (II) RZ,wheel RZ, wheel ±1 RHit residual 1 1 Entries 187 Mean.531 RMS / 65 Constant 183 Mean.743 Sigma.56 RHit residual Entries Mean RMS / 77 Constant 1475 Mean -.17 Sigma G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 1

11 Calibr. Results (III) RZ, wheel ± RecHit Res. RHit residual Entries 7143 Mean RMS / 77 7 Constant 67.9 Mean Sigma.7986 before after x (cm) G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 11

12 Plans Try residual method Depends on quality of segment reconstruction Easier to compute resolutions Optimize the granularity Per SL is probably too coarse; per wire requires too much statistics Define regions with homogeneous B field within SLs May also separate regions along wires (e.g. last few cm) Using 3D segments Increases complexity of calibration tables Take incident angle into account In each region, compute parameters for few θ bins More statistics required Starts being complex to produce and to use in reconstruction Alternative approach: calibrate the DT parametrization! G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 1

13 How it works: RecHits from Parametrization Based on the inverse function developed by J. Puerta and P. Garcia Abia: x = f -1 (t, θ, B wire, B norm ) not known at the level of individual digi! A 3-step procedure, while building segments 1. coarse knowledge of θ, B. θ from segment in SL 3. B from 3D position of segment t = peak of (asymmetric) distribution x = measured coordinate G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 13

14 6 Entries Mean -.13 RMS / 5 Constant 59 4 Mean Sigma Residuals Rφ layers 1. Stage 3. Stage (Ideal case: perfect knowledge of θ, B) Entries Mean RMS / 37 Constant Mean -.35 Sigma Resolution better than meantimer resolution since the cell non-linearity is taken into account! G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 14

15 Residuals RZ layers 1. Stage 3. Stage (Ideal case: perfect knowledge of q, B) Entries 737 Mean RMS / 37 Constant 1631 Mean Sigma Entries 737 Mean -.36 RMS / 37 Constant 476 Mean Sigma Spread is larger than in Rφ layers larger angles, different field G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 15

16 Calibration of Parametrization Concept: add calibration parameters to the function E.g. multiplicative parameters, for the linear part and for the deviation from linearity: x = f -1 (t, θ, B wire, B norm, p 1,p ) Fit the additional parameters to the data In principle, a simple least-squares fit In practice could be implemented with a iterative filter Advantages (providing it works!) It will provide the best possible resolution, since non-linearity is taken into account It will handle the dependency on θ, B with no need of complicated tools (i.e. partitioning in homogeneous B regions, computation and of calibration consts as a function of θ) G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 16

17 Conclusions First HLT calibration tools implemented in ORCA Prototype of a calibration job with meantimers Many ideas in progress! Plans to test it on 3 and hopefully 4 test beam data! G. Cerminara CMS Muon Meeting, Aachen, April 9, 4 17