Status of Pixel Offline Software

1. ID week CERN, October 28th 2013 Status of Pixel Offline Software F. Djama, Ph. Grenier, S. Miglioranzi

2. Introduction • LS1 activities • Be ready for commissioning and data taking with IBL, nSQPand DBM. • Consolidate and improve present software. • Include radiation effects in simulation and reconstruction. • Outline • Simulation: • Geometry • Digitization • Reconstruction • Clusterization • Performance • Tracking • B-tagging • Software

3. Geometry S. Elles Last months dedicated efforts to deliver a more realistic updated geometry description for the detector and services. New geometry tag (ATLAS-IBL(3D25)-04-00-01) includes: • last IBL geometry updates. • IPT, IST, ISIS (Inner Positioning and Support tubes). • nSQP (new Service Quarter Panel). • new beam pipe. • DBM (Diamond Beam Monitor). current geometry is very close to the final one. Somemechanical parts description might slightly change (endblocks, stave rings, ..). Short term plans: Validate in the next days this new description.  freeze it for DC14 ISIS (IST support) DBM IST nSQP

4. Geometry S. Elles New material budget estimations for the latest geometry available: • detector-only (as in TDR version) • including also Beam Pipe + structures + services https://twiki.cern.ch/twiki/bin/viewauth/Atlas/SimulationOfPixelGeometryAndMaterialUpgrade2013

5. Digitization S. Miglioranzi, M. Klein, M. Rudolph, F. Djama • IBL requires different digitization models (sensors technology) • New PixelDigitizationpkg in place: • Code has been optimized. • Different classes per charge model (SiPl, Si3D,DBM). • DBM model exist need to be imported in head tag. • Extension of DB and Services to IBL: • SW already delivered. • Need to prepare last IBL-aware DB folders. • DBM not included yet  needs latest geo tags. W.-M. Yao

6. Digitization of 3D Sensors at high incidence S. Terzo First data/MC comparison for high incidence on 3D sensors. 120 GeV pion at an incidence of θ = 80 (η =2.4 in ATLAS). Digitization: inductive model. Agreement should be better if we check incidence in real data: perform the sensor alignment. Model already in the IBL cache version of the ATLAS software

7. Digitization with Irradiation Effects C. Bertsche, M. Bomben, Ph. Grenier, G. Piacquadio • A lot of progress in implementing charge models for planar sensors, testing and debuging: • Electric field and Ramo potential mapping from TCAD. • TCAD reproduces well the chosen charge model (V. Chiochia et al., Nuclear Science, IEEE Transactions on , vol.52, no.4, pp. 1067- 1075, Aug. 2005) • Charge models validated by old results up to 6 1014neq/ cm2 . • Holes become important in case of trapping ! • Next step: validate charge models after irradiation with test beams of irradiated sensors. • A similar activity started for 3D sensors . M. Povoli

8. Ramo potential: TCAD simulations Ramo potential: one slice of a 3D simulation (X-Z plane) 3D simulation of ATLAS pixels: ¼ of a 3x3 matrix Ramo potential: profile along the bulk M. Bomben - TCAD simulations of planar sensors - ATLAS Pixel week - CERN, 13/06/2013

9. NN-Clusterization for IBL F. De Lorenzi • NN clustering is default pixel clustering algorithm  need to be re-trained for IBL. • In dense cores of high-pt jets, charges deposited by multiple particles can merge into a single cluster  degraded cluster resolution. • NN clustering splits merged clusters and computes positions and errors of subclusters. • NN training exercise of October 2012 failed (performances not as expected). • Some bugs identified in training code, old MC samples had geo and track problems • New training has now started (100K JZ4W from latest IBL+ATLAS prod used)  first results are promising… Histograms contain hits from all 4 pix barrel layers; Residual: NN-computed position - G4 position

10. Analog Clusterization for IBL M. Klein • What is used at the moment when running with IBL-geometry is digitalclustering. • Need to make the code more flexible to steer different clusterization algorithms for different layers. • Develop an analog clustering for IBL. • Possible optimization for the future: • use NN for cluster splitting. • analog position for the subclusters. • Work started few days ago…

11. Tracking Performance with IBL W.-M. Yao, M. Kwok, Y. Wu, Y. Fang, M. Garcia-Sciveres • Tracking performances vs PU (40,60,80,100). • At high pileup loss of efficiency & fakes increasing rate have been observed. Track fake rates vspt LF track effvspt LF track effvsη

12. Tracking Performance with IBL W.-M. Yao, M. Kwok, Y. Wu, Y. Fang, M. Garcia-Sciveres • Effects of dead modules on tracking quantities havealso been studied: • Disabling5,10,15% of modules (including IBL) • The degradation due to disabled modules up to 15%is modest at few % level

13. Schorlemmer B. Di Girolamo G. Piacquadio S. Pires M. Kwok W.-M. Yao Y. Fang M. Garcia-Sciveres B-tagging with IBL 0 IBL + 44 disabled Pix modules (with repairs) 5 IBL + 44 disabled Pix modules (with repairs) 5 IBL + 167 disabled Pix modules (no repairs) 5 IBL + 167 disabled Pix modules + readout ineff(no repairs) IBL 14TeV stdATLAS 14TeV WH-> l nu bbar MV1 μ=40 ttbar IP3D+SV1 • High Pt performance will improve with NN-clustering. • A note in preparation: • ttbar samples, PU = 0, 60. • Realistic dead module scenario (after nSQP connection at SR1). • Optimization with b-tag performance group started. ttbar IP3D+SV1

14. Other Topics L. Franconi • Connectivity and ByteStream coding for IBL : • Realistic IBL Cabling Map  joint effort of detector/DAQ/DCS group. • Proposal of FE-I4 ByteStreamCnv (P. Morettini) currently coded (with help of S. Roe). • Workaround for HLT and FTK: Dummy cabling Map (F. Djama) and FE-I3 inspired ByteStreamCnv (D. Emilyanov). • Luminosity-induced saturation effects : • At high lumi, hits will be lost due to buffer overflows and busy electronics. • Simulating FE-I3 readout process: • Bunches scheme. • Realistic ToT. • Goal: an inefficiency table (eta, lumi) to be used by digitization. • FE-I4 model also needed. • Next step: simulate MCCs. • Condition Data Base : • Folders and Services coded. • Ready to be implemented in a release. J. Black, T. Nelson W.-M. Yao

15. S. Miglioranzi Releases and core sw: • IBL developments and validation studies are currently performed in rel 17.3.X(.Y). • Validated caches used for IBL+ATLAS MC Production so far : 17.3.10.1.Z, IBLProd. • IBL+ATLAS MC Prod twikihttps://twiki.cern.ch/twiki/bin/viewauth/AtlasProtected/AtlasProductionGroupMC12Upgrade • Last validated cache was 17.3.11.1 (contains Supercell info). • Plan to release a full build 17.3.12 in the next days (this week?) including new geo-related sw. • 17.3.12 will be “in sync” with 17.2.12: •  differs for: 64bit, supercell and TrigMC tags. T0 upgrade DC14 releases plans: 17.2.11.13 Atlas Prod 17.2.12 17.7.0.5 Atlas Prod 17.3.12 17.3.11.2 Atlas Prod https://twiki.cern.ch/twiki/bin/viewauth/Atlas/InDetIBL_Example 18.1.0

16. Software Improvements S. Miglioranzi • Large and important activity to improve our software: • Identifiers • Hard coded numbers • Prepare easy ITK implementation • Code cleaning • … • Coordinated by S. Miglioranzi. • PixelDigitization package: M. Klein • Geometry: S. Elles • Conditions: W.-M. Yao • We receive valuable help from J. Chapman, N. Styles, R.D. Schaffer…

17. Summary 2012/2013 have been crucial years for the development and finalization of the IBL software  but still tight schedule ahead ! • Current geometry simulation is realistic: • Preliminary validation is ongoing and PhysVal should start soon. • Plans to use it for DC14. • Only minor changes foreseen in the future. • Digitization is in place: • Digitization models available for all the different technologies. • Reconstruction: • Existing reconstruction software robust  already working for IBL. • Optimization can be done and it has already started. • Clusterizationis a hot topic  more people involved on that now. • Involvement of other CP groups has started  vital to keep close. connection and feedback to get the best performance out of IBL.

18. Schedule Forseen schedule in april 2013: Hopefully only few weeks delay…

19. Backup

20. Geometry – DBM & DBM services Included in the new ATLAS-IBL(3D25)-04-yy-zz tags ISIS (IST support) & IST nSQP

22. Geometry – Run1 Pixel Detector • Pixel current geometry description: cooling fluid modeling: • Studies of hadronic interactions in cooling fluid. • In pixels show large data/MC discrepancy •  better modeling needed. Data MC hadronic interactions in cooling vs Z • PP0 region required optimization/improvement: • Inner PP0 material overestimated in current • GeoModel 2.3<|η|<2.5 • SCT extension eff studies sensitive to PP0 region • New improved description by looking at construction • files and directly to the dismounted SQP in SR1 SCT extension efficiency ATLAS-GEO-20-20-04 https://indico.cern.ch/getFile.py/access?contribId=3&resId=0&materialId=slides&confId=252811

24. Tracking Activities ID Alignment: • Code developments/adaptation to include IBL already started. • Alignment of the IBL/Pixels during cosmic runs. • Further understanding of Silicon deformation. • Improving run-by-run alignment, reduce track parameters systematics… Vertex Reconstruction: • Improve the power of the vertex reconstruction as in-time pile-up estimator in the next run. • Work is ongoing on the seeding algorithm. • New Tracking +IBL re-optimization is starting now…