1. LIGO-G000193-00-M LIGO I Science Run Barry Barish PAC Meeting - LHO December 13, 2000

2. LIGO-G000193-00-M 2 The LIGO I Science Run Data & Computing Group Operations Plan 9 th Meeting of the LIGO PAC LIGO Livingston Observatory Livingston, Louisiana 13 December 2000 Albert Lazzarini LIGO Laboratory Caltech

3. LIGO-G000193-00-M 3 LIGO Plans schedule 1996Construction Underway (mostly civil) 1997Facility Construction (vacuum system) 1998Interferometer Construction (complete facilities) 1999Construction Complete (interferometers in vacuum) 2000Detector Installation (commissioning subsystems) 2001 Commission Interferometers (first coincidences) 2002Sensitivity studies (initiate LIGO I Science Run) 2003+ LIGO I data run (one year integrated data at h ~ 10 -21 ) 2005+Begin ‘advanced’ LIGO installation

4. LIGO-G000193-00-M 4 Revised Schedule As proposed to the NSF – May 2000

5. LIGO-G000193-00-M 5 Significant Events

6. LIGO-G000193-00-M 6 operating as a Michelson with Fabry-Perot arms reduced input laser power (about 100 mW) without recycling noise level is a factor of 10 4 - 10 5 above the final specification sources of excess noise are under investigation Strain Sensitivity Nov 2000 2-km Hanford Interferometer

7. LIGO-G000193-00-M 7 LIGO I steps to science run  commissioning interferometer »robust locking »three interferometers »sensitivity »duty cycle  interleave engineering runs »implement and test acquisition and analysis tools »characterization and diagnostics studies »reduced data sets »merging data streams »upper limits

8. LIGO-G000193-00-M 8 LIGO/LSC Data Analysis Model  Now: »Initial engineering runs starting to set the stage for how science, research is done »Data being archived at Caltech in HPSS »Access from archive according to LIGO Laboratory MOUs »“Stress testing” of software and hardware systems - both LDAS and GDS/DAQS/CDS »Initial data analyses focus on –sorting out commissioning issues, –understanding environment, –Calibrations, data conditioning, pre-processing

9. LIGO-G000193-00-M 9 LIGO/LSC Data Analysis Model  Near-term (2Q2001): »LIGO science will focus on using engineering runs to extract meaningful first upper limits »Organized around 4 upper limits papers using ~1 week of data in 2Q2001 »Opportunity to set current best upper limits on these classes of sources »Provides a basis to "exercise" the LSC data analysis groups »Provides a basis for future organization of the LIGO I Science Run search teams –groups will expand as interest grows in LIGO science.  Problems: »LDAS readiness to support the engineering run goal »Strategy is to limit scope primarily to LDAS supported goals

10. LIGO-G000193-00-M 10 Astrophysical Signatures data analysis  Compact binary inspiral: “chirps” »NS-NS waveforms are well described »BH-BH need better waveforms »search technique: matched templates  Supernovae / GRBs: “bursts” »burst search algorithms – eg. excess power; time-frequency patterns »burst signals in coincidence with signals in electromagnetic radiation »prompt alarm (~ one hour) with neutrino detectors  Pulsars in our galaxy: “periodic” »search for observed neutron stars (frequency, doppler shift) »all sky search (computing challenge) »r-modes  Cosmological Signals“stochastic background”

11. LIGO-G000193-00-M 11 LIGO/LSC Data Analysis Model  LIGO I Science Run (2Q2002): »Key astrophysical searches follow the LSC Data Analysis White Paper plan: »Organized around teams, as in near-term upper limit studies –Open to all who are willing to work »LIGO Lab LDAS resources to be used for searches will be shared among the teams »LSC member institutional resources used by individual researchers »Longer term: establish 5 LIGO/LSC Tier 2 centers (“University Research Centers” or URCs) to provide additional computational, data distribution resources across collaboration

12. LIGO-G000193-00-M 12 Inspiral Sources LSC Upper Limit Group Inspiral Sources Co-chair Patrick Brady, Gabriela Gonzalez ------------------------------------------------------------------- Bruce Allenballen@gravity.phys.uwm.edu Sukanta Bosebose@aei-potsdam.mpg.de Douglas BoydDouglas.Boyd@astro.cf.ac.uk Patrick Bradypatrick@gravity.phys.uwm.edu Duncan Brownduncan@gravity.phys.uwm.edu Jordan Campcamp_j@ligo.caltech.edu Nelson Christensennchriste@carleton.edu Jolien Creightonjolien@gravity.phys.uwm.edu S.V. Dhurandersdh@iucaa.ernet.in Gabriela Gonzalezgig1@psu.edu Andri Gretarssonandri@suhep.phy.syr.edu Gregg Harrygharry@phy.syr.edu* Syd Meshkovmeshkov_s@ligo.caltech.edu Tom Princeprince@srl.caltech.edu David Reitzereitze@phys.ufl.edu B.S. SathyaprakashB.Sathyaprakash@astro.cf.ac.uk Peter Shawhanshawhan_p@ligo.caltech.edu

13. LIGO-G000193-00-M 13 Interferometers astrophysical sources Compact binary mergers Sensitivity to coalescing binaries Binary inspiral ‘chirp’ signal 2002 2007 future

14. LIGO-G000193-00-M 14 Interferometer Data 40 m Real interferometer data is UGLY!!! (Gliches - known and unknown) LOCKING RINGING NORMAL ROCKING

15. LIGO-G000193-00-M 15 The Problem How much does real data degrade complicate the data analysis and degrade the sensitivity ?? Test with real data by setting an upper limit on galactic neutron star inspiral rate using 40 m data

16. LIGO-G000193-00-M 16 “Clean up” data stream Effect of removing sinusoidal artifacts using multi-taper methods Non stationary noise Non gaussian tails

17. LIGO-G000193-00-M 17 Inspiral ‘Chirp’ Signal Template Waveforms “matched filtering” 687 filters 44.8 hrs of data 39.9 hrs arms locked 25.0 hrs good data sensitivity to our galaxy h ~ 3.5 10 -19 mHz -1/2 expected rate ~10 -6 /yr

18. LIGO-G000193-00-M 18 Detection Efficiency Simulated inspiral events provide end to end test of analysis and simulation code for reconstruction efficiency Errors in distance measurements from presence of noise are consistent with SNR fluctuations

19. LIGO-G000193-00-M 19 Setting a limit Upper limit on event rate can be determined from SNR of ‘loudest’ event Limit on rate: R < 0.5/hour with 90% CL  = 0.33 = detection efficiency An ideal detector would set a limit: R < 0.16/hour

20. LIGO-G000193-00-M 20  Two Sites - Three Interferometers »Single Interferometernon-gaussian level ~50/hr »Hanford (Doubles) correlated rate (x1000) ~1/day »Hanford + Livingston uncorrelated (x5000) <0.1/yr Coincidences between LLO & LHO

21. LIGO-G000193-00-M 21 Burst Souces LSC Upper Limit Group Burst Sources Co-chair Sam Finn, Peter Saulson ----------------------------------------------------------- Warren Andersonwganderson@utb1.utb.edu Barry Barishbarish@ligo.caltech.edu Biplab Bhawalbbhawal@ligo.caltech.edu Jim Braujimbrau@faraday.uoregon.edu Eric Blackblack_e@ligo.caltech.edu Kent Blackburnblackburn_k@ligo.caltech.edu Ed Dawdaw@lsuligo.phys.lsu.edu Ronald Dreverrdrever@caltech.edu Sam Finnfinn@phys.psu.edu Ray Freyrayfrey@cosmic.uoregon.edu Ken Ganezerganezer@DHVX20.CSUDH.EDU Joe Giaimegiaime@lsuligo.phys.lsu.edu Gabriela Gonzalezgig1@psu.edu Andri Gretarssonandri@suhep.phy.syr.edu Bill Hamiltonhamilton@dave.phys.lsu.edu Warren Johnsonjohnson@dave.phys.lsu.edu Masahiro Ito S. Klimenkoklimenko@phys.ufl.edu Al Lazzarinilazz@ligo.caltech.edu Szabi Markamarka_s@ligo.caltech.edu Genakh Mitselmakhermitselmakher@phys.ufl.edu Soumya Mohantymohanty@aei-potsdam.mpg.de Benoit Moursmours_b@ligo.caltech.edu Soma Mukherjeesoma@aei-potsdam.mpg.de Fred Raabfjr@ligo.caltech.edu Ravha Rahkola Peter Saulsonsaulson@ligo-la.caltech.edu

22. LIGO-G000193-00-M 22 pulsar proper motions Velocities -  young SNR(pulsars?)  > 500 km/sec Supernovae asymmetric collapse?

23. LIGO-G000193-00-M 23 LIGO I science run  Strategy »initiate science run when good coincidence data can be reliably taken and straightforward sensitivity improvements have been implemented (~ 7/02) »Then, interleave periods of science running with periods of sensitivity improvements  Goals »obtain 1 year of integrated data at h ~ 10 -21 »searches in coincidence with astronomical observations (eg. supernovae, gamma ray bursts) »searches for known sources (eg. neutron stars) »stand alone searches for compact binary coalescence, periodic sources, burst sources, stochastic background and unknown sources at h ~ 10 -21 sensitivities  Exploit science at h ~ 10 -21 before initiating ‘advanced’ LIGO upgrades

24. LIGO-G000193-00-M 24 LIGO/LSC Data Analysis Model  Throughout Engineering & Science Runs, the Laboratory’s Data & Computing Group fulfills the following roles: »LIGO science, data analysis: scientific staff are actively engaged in the astrophysics searches »Simulation & Modeling: detector support, data analysis »Continuous management and movement of large volumes of data »Maintaining pipeline analyses running, archive running »Software maintenance/improvements/enhancements »LSC support, visitors »LIGO Laboratory-wide IT support

25. LIGO-G000193-00-M 25 Data & Computing Group Principal LDAS activities during operations

26. LIGO-G000193-00-M 26 Data & Computing Group Principal Modeling & Simulation activities during operations

27. LIGO-G000193-00-M 27 Data & Computing Group Principal General Computing activities during operations

28. LIGO-G000193-00-M 28 LDAS Operations Statistics derived from actual experience

29. LIGO-G000193-00-M 29 * MIT, LHO, and LLO have local General Computing staff * LHO, and LLO have local LDAS staff

30. LIGO-G000193-00-M 30 Data and Computing Budget Breakdown

31. LIGO-G000193-00-M 31 LDAS Operations Budget Hardware Support

32. LIGO-G000193-00-M 32 Requested Increment - Operations

33. LIGO-G000193-00-M 33 Conclusions science run  Short term -- »implement LDAS –4 sites; computing; archiving »engineering runs –data handling and access, reduced data sets –diagnostics; characterize instrument and data –algorithms; statistics  Longer Term »LIGO Lab support for Science Run  Support Required »LDAS procurement and implementation »incremental resources requested –manpower –maintenance and networking –support of LSC