On the LISA science performance in observations of short-lived signals from massive black hole binary coalescences

Abstract

The observation of massive black hole binary systems is one of the main science objectives of the Laser Interferometer Space Antenna (LISA). The instrument's design requirements have recently been revised: they set a requirement at $0.1\mathrm{mHz}$, with no additional explicit requirements at lower frequencies. This has implications for observations of the short-lived signals produced by the coalescence of massive and high-redshift binaries. Here we consider the most pessimistic scenario: the (unlikely) case in which LISA has no sensitivity below $0.1\mathrm{mHz}$. We show that the presence of higher multipoles (beyond the dominant $\ell =|m|=2$ mode) in the gravitational radiation from these systems, which will be detectable with a total signal-to-noise ratio $\sim 10^3$, allows LISA to retain the capability to accurately measure the physical parameters, the redshift, and to constrain the sky location. To illustrate this point, we consider a few select binaries in a total (redshifted) mass range of $4\times 10^6-4\times 10^7{M}_{\odot }$ whose ($\ell =|m|=2$) gravitational-wave signals last between $\approx 12$ hours and $\approx 20$ days in band. We model the emitted gravitational radiation using the highly accurate (spin-aligned) waveform approximant IMRPhenomXHM and carry out a fully coherent Bayesian analysis on the LISA noise-orthogonal time-delay-interferometry channels.

13 pages, 6 figures, comments welcome!

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• Advancing Space-Based Gravitational Wave Astronomy: Rapid Parameter Estimation via Normalizing Flows
• Stars or gas? Constraining the hardening processes of massive black-hole binaries with LISA
• Discovering neutron stars with LISA via measurements of orbital eccentricity in Galactic binaries
• Accelerating LISA inference with Gaussian processes
• Rapid Parameter Estimation for Merging Massive Black Hole Binaries Using Continuous Normalizing Flows
• Accurate and efficient simulation-based inference for massive black-hole binaries with LISA