When vacuum breaks: a self-consistency test for astrophysical environments in extreme mass ratio inspirals

Abstract

Gravitational-wave signals are typically interpreted under the vacuum hypothesis, i.e. assuming negligible influence from the astrophysical environment. This assumption is expected to break down for low-frequency sources such as extreme mass ratio inspirals (EMRIs), which are prime targets for the Laser Interferometer Space Antenna (LISA) and are expected to form, at least in part, in dense environments such as Active Galactic Nuclei or dark-matter spikes/cores. Modeling environmental effects parametrically is challenging due to the large uncertainties in their underlying physics. We propose a non-parametric test for environmental effects in EMRIs, based on assessing the self-consistency of vacuum parameter posteriors inferred from different portions of the signal. Our results demonstrate that this approach can reveal the presence of astrophysical environments, or even deviations from General Relativity, without introducing additional parameters or assumptions about the underlying physics.

Figures (4)

• Figure 1: Two dimensional marginalized posteriors (with contours at $50\%$ and $90\%$ confidence level) for the primary mass $M$ and spin $a/M^2$, for an injection with disk migration torques but with vacuum EMRI templates, for different observation durations. Significant inconsistencies in the posteriors reveal the neglected environmental effect.
• Figure 2: One dimensional marginalized posteriors of $\log_{10} M/M_\odot,\, a/M ^2$ for different injections, namely: a vacuum EMRI with noise (green); a migration-affected EMRI with (red) and without (blue) noise. The inconsistency in the posteriors due to the environment can be distinguished from the effect of the noise realization.
• Figure 3: Top panel shows the orbital dephasing (as function of duration and orbital separation $r_0/M$) between a noiseless EMRI with migration torques and the corresponding vacuum case. For this injection, the bottom panel shows the residual SNR obtained from the maximum likelihood vacuum EMRI waveform.
• Figure 4: Posteriors for the migration + noise injection, for all the observation times considered. We omit the posteriors of $r_0/M$ and $\Phi_{\phi_0}$, as their true values change with the observation time. Note that the use of a wrong template has little effect on the extrinsic parameters posteriors, which are always consistent.