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"Colliding Black Holes" Credit: National Center for Supercomputing Applications (NCSA)

Probing the Universe for Gravitational Waves Barry C. Barish Caltech Argonne National Laboratory 16-Jan-04. "Colliding Black Holes" Credit: National Center for Supercomputing Applications (NCSA). LIGO-G030523-00-M. Einstein’s Theory of Gravitation.

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"Colliding Black Holes" Credit: National Center for Supercomputing Applications (NCSA)

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  1. Probing the Universe for Gravitational WavesBarry C. BarishCaltechArgonne National Laboratory16-Jan-04 "Colliding Black Holes"Credit:National Center for Supercomputing Applications (NCSA) LIGO-G030523-00-M

  2. Einstein’s Theory of Gravitation • a necessary consequence of Special Relativity with its finite speed for information transfer • gravitational waves come from the acceleration of masses and propagate away from their sources as a space-time warpage at the speed of light gravitational radiation binary inspiral of compact objects

  3. Einstein’s Theory of Gravitation gravitational waves • Using Minkowski metric, the information about space-time curvature is contained in the metric as an added term,hmn. In the weak field limit, the equation can be described with linear equations. If the choice of gauge is thetransverse traceless gaugethe formulation becomes a familiar wave equation • The strainhmntakes the form of a plane wave propagating at the speed of light (c). • Since gravity is spin 2, the waves have two components, but rotated by 450 instead of 900 from each other.

  4. Detectionof Gravitational Waves Gravitational Wave Astrophysical Source Terrestrial detectors Virgo, LIGO, TAMA, GEO AIGO Detectors in space LISA

  5. Frequency range for EM astronomy Electromagnetic waves • over ~16 orders of magnitude • Ultra Low Frequency radio waves to high energy gamma rays

  6. Frequency range for GW Astronomy Audio band Gravitational waves • over ~8 orders of magnitude • Terrestrial and space detectors Space Terrestrial

  7. Detecting a passing wave …. Free masses

  8. Detecting a passing wave …. Interferometer

  9. As a wave passes, the arm lengths change in different ways…. Interferometer Concept • Arms in LIGO are 4km • Measure difference in length to one part in 1021 or 10-18 meters • Laser used to measure relative lengths of two orthogonal arms …causing the interference pattern to change at the photodiode Suspended Masses

  10. 3002 km (L/c = 10 ms) Simultaneous DetectionLIGO Hanford Observatory MIT Caltech Livingston Observatory

  11. LIGO Livingston Observatory

  12. LIGO Hanford Observatory

  13. LIGO Facilitiesbeam tube enclosure • minimal enclosure • reinforced concrete • no services

  14. LIGObeam tube • LIGO beam tube under construction in January 1998 • 65 ft spiral welded sections • girth welded in portable clean room in the field 1.2 m diameter - 3mm stainless 50 km of weld

  15. Vacuum Chambersvibration isolation systems • Reduce in-band seismic motion by 4 - 6 orders of magnitude • Compensate for microseism at 0.15 Hz by a factor of ten • Compensate (partially) for Earth tides

  16. Constrained Layer damped spring Seismic Isolationsprings and masses

  17. LIGOvacuum equipment

  18. Seismic Isolationsuspension system suspension assembly for a core optic • support structure is welded tubular stainless steel • suspension wire is 0.31 mm diameter steel music wire • fundamental violin mode frequency of 340 Hz

  19. Surface uniformity < 1 nm rms Scatter < 50 ppm Absorption < 2 ppm ROC matched < 3% Internal mode Q’s > 2 x 106 LIGO Opticsfused silica Caltech data CSIRO data

  20. Core Optics installation and alignment

  21. LIGO Commissioning and Science Timeline

  22. Lock Acquisition

  23. Detecting Earthquakes From electronic logbook 2-Jan-02 An earthquake occurred, starting at UTC 17:38.

  24. Detecting the Earth TidesSun and Moon Eric Morgenson Caltech Sophomore

  25. Tidal Compensation Data Tidal evaluation 21-hour locked section of S1 data Predicted tides Feedforward Feedback Residual signal on voice coils Residual signal on laser

  26. Controlling angular degrees of freedom

  27. Seismic Noise Quantum Noise Radiation pressure Residual gas scattering "Shot" noise Wavelength & amplitude fluctuations Thermal (Brownian) Noise Interferometer Noise Limits test mass (mirror) LASER Beam splitter photodiode

  28. What Limits LIGO Sensitivity? • Seismic noise limits low frequencies • Thermal Noise limits middle frequencies • Quantum nature of light (Shot Noise) limits high frequencies • Technical issues - alignment, electronics, acoustics, etc limit us before we reach these design goals

  29. LIGO Sensitivity Evolution Hanford 4km Interferometer Dec 01 Nov 03

  30. Science Runs A Measure of Progress Milky Way Virgo Cluster Andromeda NN Binary Inspiral Range E8 ~ 5 kpc S1 ~ 100 kpc S2 ~ 0.9Mpc S3 ~ 3 Mpc Design~ 18 Mpc

  31. Best Performance to Date …. Range ~ 6 Mpc

  32. Astrophysical Sourcessignatures • Compact binary inspiral: “chirps” • NS-NS waveforms are well described • BH-BH need better waveforms • search technique: matched templates • Supernovae / GRBs: “bursts” • 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 Signal “stochastic background”

  33. Compact binary collisions • Neutron Star – Neutron Star • waveforms are well described • Black Hole – Black Hole • need better waveforms • Search: matched templates “chirps”

  34. Template Bank 2110 templatesSecond-orderpost-Newtonian • Covers desiredregion of massparam space • Calculatedbased on L1noise curve • Templatesplaced formax mismatchof  = 0.03

  35. Then inverse Fourier transform gives you the filter output at all times: Find maxima of over arrival time and phaseCharacterize these by signal-to-noise ratio (SNR) and effective distance Optimal Filtering frequency domain • Transform data to frequency domain : • Generate template in frequency domain : • Correlate, weighting by power spectral density of noise:

  36. Matched Filtering

  37. Loudest Surviving Candidate • Not NS/NS inspiral event • 1 Sep 2002, 00:38:33 UTC • S/N = 15.9, c2/dof = 2.2 • (m1,m2) = (1.3, 1.1) Msun What caused this? • Appears to be due to saturation of a photodiode

  38. Sensitivity neutron binary inspirals Star Population in our Galaxy • Population includes Milky Way, LMC and SMC • Neutron star masses in range 1-3 Msun • LMC and SMC contribute ~12% of Milky Way Reach for S1 Data • Inspiral sensitivity Livingston: <D> = 176 kpc Hanford: <D> = 36 kpc • Sensitive to inspirals in Milky Way, LMC & SMC

  39. Results of Inspiral Search Upper limit binary neutron star coalescence rate LIGO S1 Data R < 160 / yr / MWEG • Previous observational limits • Japanese TAMA  R < 30,000/ yr / MWEG • Caltech 40m  R < 4,000/ yr / MWEG • Theoretical prediction R < 2 x 10-5 / yr / MWEG Detectable Range of S2 data will reach Andromeda!

  40. Astrophysical Sourcessignatures • Compact binary inspiral: “chirps” • NS-NS waveforms are well described • BH-BH need better waveforms • search technique: matched templates • Supernovae / GRBs: “bursts” • 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 Signal “stochastic background”

  41. Detection of Burst Sources • Known sources -- Supernovae & GRBs • Coincidence with observed electromagnetic observations. • No close supernovae occurred during the first science run • Second science run – We are analyzing the recent very bright and close GRB030329 • NO RESULT YET • Unknown phenomena • Emission of short transients of gravitational radiation of unknown waveform (e.g. black hole mergers).

  42. Time-Frequency Plane Search Pure Time-Domain Search ‘TFCLUSTERS’ ‘SLOPE’ frequency time ‘Unmodeled’ Bursts search for waveforms from sources for which we cannot currently make an accurate prediction of the waveform shape. GOAL METHODS ‘Raw Data’ Time-domain high pass filter 8Hz 0.125s

  43. h amplitude 0 0 10 time (ms) Determination of Efficiency Efficiency measured for ‘tfclusters’ algorithm To measure our efficiency, we must pick a waveform. 1ms Gaussian burst

  44. Burst Upper Limit from S1 1ms gaussian bursts Result is derived using ‘TFCLUSTERS’ algorithm • Upper limit in straincompared to earlier (cryogenic bar) results: • IGEC 2001 combined bar upper limit: < 2 events per day having h=1x10-20 per Hz of burst bandwidth. For a 1kHz bandwidth, limit is < 2 events/day at h=1x10-17 • Astone et al. (2002), report a 2.2 s excess of one event per day at strain level of h ~ 2x10-18 90% confidence

  45. Astrophysical Sourcessignatures • Compact binary inspiral: “chirps” • NS-NS waveforms are well described • BH-BH need better waveforms • search technique: matched templates • Supernovae / GRBs: “bursts” • 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 Signal “stochastic background”

  46. Detection of Periodic Sources • Pulsars in our galaxy: “periodic” • search for observed neutron stars • all sky search (computing challenge) • r-modes • Frequency modulation of signal due to Earth’s motion relative to the Solar System Barycenter, intrinsic frequency changes. • Amplitude modulation due to the detector’s antenna pattern.

  47. PSR J1939+2134 1283.86 Hz Directed searches NO DETECTION EXPECTED at present sensitivities Crab Pulsar Limits of detectability for rotating NS with equatorial ellipticity e = dI/Izz: 10-3 , 10-4 , 10-5 @ 8.5 kpc.

  48. Two Search Methods • Frequency domain • Best suited for large parameter space searches • Maximum likelihood detection method + Frequentist approach • Time domain • Best suited to target known objects, even if phase evolution is complicated • Bayesian approach First science run --- use both pipelines for the same search for cross-checking and validation

  49. The Data time behavior days days days days

  50. The Data frequency behavior Hz Hz Hz Hz

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