The minimum measurable eccentricity from gravitational waves of LISA massive black hole binaries

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY(2024)

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摘要
We explore the eccentricity measurement threshold of Laser Interferometer Space Antenna (LISA) for gravitational waves radiated by massive black hole binaries (MBHBs) with redshifted BH masses M-z in the range 10(4.5)-10(7.5) M-circle dot at redshift z = 1. The eccentricity can be an important tracer of the environment where MBHBs evolve to reach the merger phase. To consider LISA's motion and apply the time delay interferometry, we employ the LISABETA software and produce year-long eccentric waveforms using the inspiral-only post-Newtonian model TAYLORF2ECC. We study the minimum measurable eccentricity (e(min), defined one year before the merger) analytically by computing matches and Fisher matrices, and numerically via Bayesian inference by varying both intrinsic and extrinsic parameters. We find that e(min) strongly depends on M-z and weakly on mass ratio and extrinsic parameters. Match-based signal-to-noise ratio criterion suggest that LISA will be able to detect e(min) similar to 10(-2.5) for lighter systems (M-z less than or similar to 10(5.5) M-circle dot) and similar to 10(-1.5) for heavier MBHBs with a 90 per cent confidence. Bayesian inference with Fisher initialization and a zero noise realization pushes this limit to e(min) similar to 10(-2.75) for lower-mass binaries, assuming a <50 per cent relative error. Bayesian inference can recover injected eccentricities of 0.1 and 10(-2.75) for a 10(5) M-circle dot system with an similar to 10(-2) per cent and an similar to 10 per cent relative errors, respectively. Stringent Bayesian odds criterion (ln B >8) provides nearly the same inference. Both analytical and numerical methodologies provide almost consistent results for our systems of interest. LISA will launch in a decade, making this study valuable and timely for unlocking the mysteries of the MBHB evolution.
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black hole physics,gravitational waves,methods: data analysis,methods: statistical
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