1. Linda R. Coney – 24th April 2009 Online Monitoring and Reconstruction Linda R. Coney 4 June, 2009

2. Linda R. Coney – 4 June 2009 Outline  Introduction  Data Structure  Unpacking DATE data  Online Monitoring  Online Reconstruction  Conclusions

3. Linda R. Coney – 4 June 2009 MICE Online  So far: u DAQ front end u Trigger u Event Building u Controls and Monitoring  Given that we are successfully running the experiment and creating data u How do we know the equipment is working well? u How do we check the data quality?  Two levels of real-time data quality checks u Online Monitoring s Look at raw data for each board in the DAQ s No translation into physical quantities u Online Reconstruction s Initial look at analysis variables  Next: see Henry’s talk about the Data Flow…

4. Linda R. Coney – 4 June 2009 DAQ Terminology  LDC – Local Data Collector  GDC – Global Data Collector  Equipment – module in DAQ crate  DATE – The DAQ Software

5. Linda R. Coney – 4 June 2009 Data Format  DAQ Events: u SuperEvent  contains SubEvents come from single crate (ie. come from LDC) u Header for Super/Sub events is the same u Event Fragment is data from single board in crate (equipment) s Fragments have different information for different board types u Two types of Events s CALIBRATION –Always 1 particle event s PHYSICS –Can have multiple particle events –Should have 2 crates –Data volume dominated by fADCs u Particle event info is board specific

6. Linda R. Coney – 4 June 2009 Raw Data Format … DAQ Event N+1 Payload … DAQ Event N+1 GDC Header DAQ Event N Payload … DAQ Event N GDC Header … Run File … LDC J+1 Payload … LDC J+1 Header LDC J Payload … LDC J Header … (Super-) Event … Particle Event M+1 Data: Board Manufacturer Format Particle Event M Data: Board Manufacturer Format … Event Fragment … Equipment K+1 Payload Equipment K+1 Header Equipment K Payload Equipment K Header … (Sub-) Event

7. Linda R. Coney – 4 June 2009 DATE Event Header Format Event Header Event Size Sync. Word Header Size Header Version EventType RunNb Event Id[0] Event Id[1] TriggerPattern[0] TriggerPattern[1] DetectorPattern[0] DetectorPattern[1] Attribute[0] Attribute[1] Attribute[2] LDC Id GDC Id TimeStamp[0] TimeStamp[1]  This structure comes from DATE

8. Linda R. Coney – 4 June 2009 DATE Equipment Header Format Equipment Data Size Equipment Type Equipment User Id Equipment Attribute[0] Equipment Attribute[1] Equipment Attribute[2] Equipment Word Size Equipment Header Conventional Table of Equipment Type: Random Generator0 Scalar V830111 VLSB104 fADC V1724120 Trailer110 TDC V1290102 Trigger Receiver101 V2718100 EquipmentType

9. Linda R. Coney – 4 June 2009 V. Verguilov Particle Data Format Example - CAEN V1290 TDC 313029282726252423222120191817161514131211109876543210 01000Event Count (starting at 0)GEO Address 00000TChannel NbTime Data........................ … …Variable Number of hits… … 00000TChannel NbTime Data 10000StatusWord CountGEO Address TDC V1290 … Particle Event M Data: Board Manufacturer Format Particle Event M+1 Data: Board Manufacturer Format … Data Type T = 1 for Trailing Edge Measurement Data

10. Linda R. Coney – 4 June 2009 Data Unpacking Classes

11. Linda R. Coney – 4 June 2009 Data Unpacking Classes  MDdataContainer - base class for all  MDEvent – handles sub and super events  MDeventFragment - container for the particle events, data from single board  MDpartEventXXX - classes manipulating the data (at event level) from each equipment using corresponding MDdataWordXXX class u MDpartEventV1724: GetPattern, GetChannelMask, GetTriggerTimeTag, GetSampleData (fADC) u MDpartEventV1290: GetHitMeasurement, GetHitType, GetHitChannel, GetNHits (TDC)  MDequipMap - Class using a hash to determine which object (MDpartEventXXX) can decode specific event, based on the Equipment Id of the event  MDdataWord - base class for word-level classes ( SetDataWord( void * d) )  MDdataWordXXX - classes implementing the data format (at word-level) of each equipment u MDdataWordV1724: GetSample u MDdataWordV1290: GetMeasurement, GetChannel, GetTDC, GetError, GetWordCount, GetBunchID, GetEventID u  MDdateFile - IO routines for the DATE raw data file  MDargumentHandler – class for manipulating command-line input

12. Linda R. Coney – 4 June 2009 Unpacking Flow Chart

13. Linda R. Coney – 4 June 2009 Online Monitoring

14. Linda R. Coney – 4 June 2009 Online Monitoring  Run unpacker on DATE data u Fill plots for each type of board s No geography information s No reconstruction s Boards have ID# but no information on what channel it is u Fill online monitoring histograms in real time while taking data u Use to debug operations u Provides data quality check u Provide graphical interface to display plots  There are 3 overall types of plots because there are 3 types of board u FADCs u Scalar u TDCs

15. Linda R. Coney – 4 June 2009 Scalar in DAQ  Scalars count hits inside the DAQ Spill Gate Part. Trigger Part. Trg Req. GVA1 GVA2 GVA3 CKOVA/B Clock 1MHz TOF0 Cumulative, average and Last Spill Available

16. Linda R. Coney – 4 June 2009 Online Monitoring Histograms  Example of monitoring plots from data run in November08  Preset histograms  TOF position info, Scalars

17. Linda R. Coney – 4 June 2009 Online Monitoring Actions  DAQ DATE Readout is finished   Create framework for decoding data   Implement unpacking for TOF, CKOV, KL   Test data readout, unpacking, and monitoring with real-time data   Include unpacking with G4MICE   Create online monitoring plots for TOF, CKOV   Upgrade FADC firmware (7/09) u Will decrease size of data  Modify FADC monitoring plots (7/09)  Implement unpacking for Tracker (08/09)  Create online monitoring plots for KL,Tracker, EMR (9/09, 2010)  Implement unpacking for EMR (2009)

18. Linda R. Coney – 4 June 2009 Online Reconstruction

19. Linda R. Coney – 4 June 2009 Online Reconstruction  G4MICE uses the unpacker to look at data from DATE  It then converts the raw data into information with physical meaning  Goal: u Provide a fixed set of histograms to be filled in real time during data taking u These histograms will contain quantities that can give information about the physics happening – first look at analysis quantities u Provides another data quality check s Are we taking the data we think we are? s Are the detectors & beam behaving as planned? u Provide graphical interface to display plots  Not meant to be final results  Collaboration chooses list of useful histograms

20. Linda R. Coney – 4 June 2009 Online Reconstruction Histograms  TOF u Reconstructed time-of-flight u Distribution in x, y across TOF0, TOF1, TOF2  2D x vs y  gives shape of beam  CKOV u Light yield  KL  EMR  Tracker(s) u Muon p x, p y, p z, p T, p at the 2 tracker reference planes u x,x’, y,y’ u 1D, 2D plots of position at 2 tracker reference planes u Light yield distributions for each station  PID determination  Beam emittance, amplitude

21. Linda R. Coney – 4 June 2009 Online Reconstruction Histograms  What is needed to produce these plots?  Online Reconstruction farm  G4MICE installed on farm  TOF reconstruction  CKOV reconstruction  Tracker reconstruction  KL reconstruction  Unpacking code for each detector  Check that G4MICE uses unpacker in a same way that Online Monitoring uses unpacker

22. Linda R. Coney – 4 June 2009 Current Status of Reconstruction  TOF Reconstruction and calibration well underway  CKOV reco same  Tracker reconstruction works

23. Linda R. Coney – 4 June 2009 Online Reconstruction Farm  Installed two farm computers in MICE control room March 09  Total of three quad-core processors  G4MICE installed on both  Tests run u Reconstructed tracker cosmic ray test data s 114 events/second u Ran simulation, digitization, and reconstruction of Step VI s Simulation: ~262 events/second s Simulation + Digi: ~236 events/second s Reconstruction: ~1920 events/second

24. Linda R. Coney – 4 June 2009 Online Reconstruction Histograms  What is needed to produce these plots?  Online Reconstruction farm   G4MICE installed on farm   TOF reconstruction   CKOV reco   Tracker reco   KL reco  Unpacking code for each detector u TOF, CKOV, GVA, KL  u Trackers, EMR (08/09, late 2009)  Check that G4MICE uses unpacker in same way that Online Monitoring uses unpacker u Can produce online monitoring plots with G4MICE  u Testing under way to compare to standard Online Monitoring plots (6/09)

25. Linda R. Coney – 4 June 2009 Conclusions  We are now able to u Read out and decode DATE DAQ from MICE beam data u Monitor Step I raw data quality and detector performance with Online Monitoring u Reconstruct TOF, CKOV, Tracker data  We will soon u Implement online reconstruction for Step I u Include tracker in online monitoring for Step II  We will eventually u Include necessary information for further steps u Routinely have shifters monitoring detectors and MICE physics in MLCR

27. The MICE Schedule Experiment designed to grow with each step providing important information