1. Chris Parkes for VELO software Group VELO Software Overview & Shutdown Planning Organisation Milestones 3 Critical Areas

2. 2 Areas & Responsibilities Overall Co-ord: CP PVSS: Stefano De Capua DAQ Recipes: Karol Hennessy Timing & Gain: Kazu Akiba Error Bank Analyses: Ann van Lysebetten Online Monitoring: Kurt Rinnert Data Quality: Eduardo Rodrigues Simulation & Reconstruction: Tomasz Szumlak Tracking: David Hutchcroft Alignment: Silvia Borghi Closing Strategy: Malcolm John > 20 people contributing Milestones defined for each, with one person responsible and priorities assigned

3. 3 Organisation Weekly Monday commissioning meeting –Report on previous week milestones –News from all, forum for discussing issues –Work plans for the week Integration Days: Thursdays –Integrate weekly releases (if any) at pit –Release: PVSS, recipes, Vetra Brief report bi-weekly Friday meeting –Report progress to whole group, no details –Specific presentations on items of general interest Shutdown progress logged on milestone Twiki page https://lbtwiki/bin/view/VELO/SoftwareMilestones

4. 4 Milestone Progress Proceeding close to schedule Some delays due to FEST’08 production

5. 5 Critical Path In September identified three key areas where progress is needed before we start running this year –Timing –TELL1 Parameter Uploading –Monitoring

6. 6 Timing studies Set up timing for sampling of pulse train and for optimal analogue signal height Automated timing scans implemented and being tested Firmware release being tested

7. 7 Digitisation Delay Time (CLK/channels) ADC Counts 34 6 5 Delayed pulse Measured Voltage ARx Clock Delayed Sampling phase

8. 8 ADC Counts 2550 100 75 First Time Sample Second Time Sample Third Time Sample Fourth Time Sample... Scan Points Delayed pulse Sampled points for a given clock Beetle Clock Analogue Sampling Delay Time (ns)

9. 9 TELL1 Data Processing Velo Data Processing Raw -> Clusters in TELL1 Pedestal Following Common Mode Suppression (MCMS) Beetle baseline shift Reordering Common Mode Suppression (LCMS) Clusterization Beetle Cross-talk Correction Cable Cross-talk Filter (FIR) Require 1M parameters Optimisation critical for data quality (see TED data talk) Pedestal & Clusterisation Thresholds most important Bit Perfect Emulation of Algorithms in full LHCb Software Framework Lower priority Lower priority RAW CLUSTERS

10. 10 Vetra – TELL1 Emulation Parameter uploading achieved for first time in December Firmware fixes made and used (November) Testing & evaluation underway

11. 11 Pedestal Processing Raw dataPedestal corrected data Pedestal correction monitoring Base line (zero) level after pedestal correction

12. 12 Beetle X-talk effect first channel in each analog link is affected Noise after pedestal correction Beetle X-talk correction monitoring Measured noise in first channel before correction Noise in first channel after correction Average noise measured in unafected channel Beetle X-talk correction

13. 13 ADC count Constant Pedestal Only ADC count All Parameters tuned Effect of tuning Non-Zero Suppressed Data critical – so that tuning parameters can be obtained Procedure to take automatically during data - One module at a time, under test

14. 14 Monitoring Monitoring package –Package for “high-level” (= ZS) data Monitoring based on clusters and tracks –Package for NZS data Noise calculation, time alignment study, beetle pulse shape, … Scripts and macros are being developed to analyse data Wiki pages with documentation and HowTo’s Review of Monitoring status in February

15. 15 Online monitoring Running since August Implementation of several plots New features to be exploited Online presenter

16. 16 Cluster Monitoring Cluster information: –Cluster ADC value –Active chip links –Number of strip in a cluster –Cluster ADC value versus sampling –Number of cluster per events –More… Some of these distributions versus sensor number and/or sensor strip

17. 17 Example distributions from VeloRecMonitors

18. 18 Track Monitoring Tracks –Number tracks –Pseudo-rapidity –Azimuthal Angle –Pseudo-efficiency –Biased and unbiased Residuals versus sensor number –Total number of R cluster per track –Vertex information –Hits distribution in xy and xz –Mean sigma of residuals versus of sensors –More…

19. 19 Track monitoring: J/  (  ) K s BiasedRes R  Sensor # Pseudo rapidity Azimuthal angle X(cm) Z(mm)

20. 20 Script and Macros Analysis of the data for the evaluation for: –Time alignment study, –Noise calculation, –High voltage scan, –beetle pulse shape, –More…

21. 21 Noise monitoring macros – example of GUI

22. 22 Noise monitoring macros – example of GUI Common mode subtraction No common mode

23. 23 Noise performance HP1HP2HP3HP4 Common mode pickup from beam requires data At pit and in previous testbeams parameters highly stable

24. 24 Noise – individual / whole system No evidence that operation of full system induces more noise than single sensors

25. 25 Noise versus Voltage Expected Signal / Noise

26. 26 IV - scans PVSS recipes available to automate IV scans Set initial voltage, target voltage, step, single or set of sensors A data file produced per sensor containing channel number, voltage, current, sensor temperature Analysis scripts for plotting IV scan data

27. 27 Software Commissioning Summary All baseline algorithms –Completed for summer ’08 Commissioning software –Milestones for data readiness in April 2009 –3 critical areas all proceeding according to plan TED data are the VELO ‘cosmics’ Tremendous success of first tracks This sample has been very useful for comissioning TED data this summer will allow us to: Optimise timing Test and tune FPGA algorithms Increase alignment accuracy