1. Seth Timpano Louis Rubbo Neil Cornish Characterizing the Gravitational Wave Background using LISA

2. Outline Motivation Galactic Sources of Gravitational Waves Modeling a Source LISA and Detector Simulations The Full Modulated Signal Bright Sources Confusion Background Tests of Normality

3. Galactic Sources of Gravitational Radiation Binaries have time varying quadrupole moments Large number of binaries Galactic Sources –Unevolved Binaries: 7  10 10 –Catacylsmics: 1.8  10 6 –WUMa: 3  10 7 –Neutron Star Binaries: 1  10 6 –Neutron Star/Black Hole: 5  10 5 –Close White Dwarfs: 3  10 6 3  10 7 ??? D. Hils, P. Bender, and R.F. Webbink, Astrophys. J. 360, 75, 1990

4. Modeling an Individual Source General Gravitational Wave Polarization Coefficients Amplitudes

5. Galactic Model Galactic Disk Sun-Centered Ecliptic Coordinates

7. Barycenter Combine all source types to arrive at a total barycenter background.

8. Source Number Density Number of sources per Frequency bin versus frequency.

9. LISA NASA/ESA mission 2014 Orbital Configuration –1 AU –60 degree inclination –3 spacecraft –5e6 km arm-length Sensitive to both + & x Frequency Response –10 -5 to 10 0 Hz Sources –Galactic Binaries –SMBH Mergers –EMRIs

10. Signal Modulation –Frequency Modulation Doppler Effect –Amplitude Modulation Time Varying Antenna Patterns –Phase Modulation +,x sensitivity

11. Extended Low Frequency Approximation Arbitrary Observation Time: Frequency Evolution: Arm Response Functions: Total Response:

12. Correlations Low Frequency ApproximationRigid Adiabatic Approximation Extended Low Frequency Approximation

13. The Accelerated LISA Simulator Low Frequency Approximation Extended Low Frequency Approximation Rigid Adiabatic Approximation f < 3mHzf < 7mHzf < 100mHz

14. The Simulated Background

15. The Barycenter Background

16. The Simulated Background

17. Noise Co-added to Signal

18. Outlier Removal Exact Removal Removal Procedure –Determine initial Confusion Background –Remove all sources with SNR > 5 –Update Confusion Background –Remove all sources with SNR > 5 –Repeat 4 more times

19. Confusion Background Definition of the Confusion Background Estimate of the Confusion Background

20. Outlier Properties Source Number and Type Distance versus Frequency Source Density

21. Gaussian?...No Are the Fourier coefficients of the power spectrum normally distributed? Fails to be Gaussian due to outliers in the tails of the distribution. Central Limit Theorem?

22. Gaussian?...Yes What happens when we remove all the bright sources? The Confusion background is Gaussian.

23. Galactic Model of Gravitational Radiation Detector Simulation Identification of Outliers and Source Removal Distinguish Background from Noise Summary