applying numerical relativity and eob to black hole binary observation sean mcwilliams nasa goddard...

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Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators: John Baker, Joan Centrella, Bernard Kelly, Jim Van Meter, Alessandra Buonanno, Yi Pan 10 August 2007

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Page 1: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

Applying Numerical Relativity and EOB to Black Hole Binary

Observation

Sean McWilliamsNASA Goddard Space Flight Center

University of MarylandCollaborators: John Baker, Joan Centrella, Bernard Kelly, Jim Van Meter, Alessandra Buonanno, Yi Pan

10 August 2007

Page 2: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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In this talk…• Creating optimal hybrid NR-PN waveforms

via phase evolution comparisons

• Using our hybrid waveform to investigate overall detectability for LIGO, Advanced LIGO, and LISA

• Using EOB to fit an analytic waveform to the numerical merger, comparing the fit to other PN methods in the late inspiral

• What’s next

Page 3: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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Phase comparisons

Out of sync In sync

• Waveforms evolve out of sync in phase and frequency• δφ depends on what time you set the waveforms to be equal

Calculating δφ vs. frequency does not yield the same results as calculating vs. time over a particular time interval.

Page 4: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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08.0cMNRcPNc Md

d

Md

d

)(

)(

)(

)(

5.3

• For data analysis, we construct a “best guess” waveform with a PN inspiral and NR merger

• We find

for , or t = -328M (circled below)

Page 5: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

5

Example signals for LIGO and Advanced LIGO

)(~

)( fhffhchar )(5)( ffSfh nrms

Page 6: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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Example signals for LISA

Page 7: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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Horizon of detectabilityHow close does an average oriented, average sky location LIGO

source need to be to have an SNR of 8, i.e. to be detectable?

Page 8: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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SNR vs. nonred-shifted mass and

redshift for Advanced LIGO and LISA

• 10s to 100s of mergers per year seen by LISA for 104 MSun < M < 106 MSun

(Sesana et al. 2007) • >10 mergers/year for M =

~103 MSun by AdLIGO and LISA (Fregeau et al. 2006), but rates are far less certain

Advanced LIGO

LISA

Page 9: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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Example of a simulated LISA signal

Michelson single arm X observable for two 105 MSun black holes (as measured in the binary COM frame) at z=15. The response

function for the example’s sky location is close to the average, but this signal is optimally oriented, so the

sky- and orientation-averaged SNR~300 is

roughly a factor sqrt(5) less than the true SNR for

this signal

Page 10: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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Matching NR

and EOB

4:11:1

h+ for 4:1 mass ratio, summed through l=4,

evaluated at =/3

The EOB model includes a

phenomeno-logical 4PN term in the effective potential A(r), and 3 QNMs

attached at the peak orbital

frequency and tuned to the Mf and af from the

numerical simulations.

See Yi Pan’s talk tomorrow, 5:10, in

Thomas 216 for more EOB-NR details

Page 11: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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PN late inspiral comparison

1:1 4:1

All PN flavors are compared to Tt3, which uses PN-expanded phase as a function of time. T re-expands the energy balance

equation in powers of orbital frequency. Tt1 solves energy balance numerically without re-expanding flux or energy.

Page 12: Applying Numerical Relativity and EOB to Black Hole Binary Observation Sean McWilliams NASA Goddard Space Flight Center University of Maryland Collaborators:

10 August 2007 Sean T. McWilliams UMD/NASA GSFC

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Plans for future work include

• Testing LIGO burst and inspiral algorithms by injecting NR-PN hybrid waveforms into the data.

• Performing studies of parameter estimation using NR waveforms with Advanced LIGO and LISA.

• Constructing templates for signal detection and parameter estimation investigations using NR runs and the EOB formalism which will incorporate spin effects.