Identifying the electromagnetic counterparts of LISA massive black hole binaries in archival LSST data

TL;DR

This paper demonstrates that electromagnetic counterparts of LISA-detected massive black hole binaries can be reliably identified in archival LSST data by analyzing periodic quasar signals, enabling targeted follow-up observations.

Contribution

It introduces a method to identify EM counterparts of LISA binaries in LSST data using orbital frequency evolution and Monte Carlo simulations to reduce false alarms.

Findings

False alarm probability below 10^-5 for fiducial binaries

Genuine signals stand out in Lomb-Scargle periodograms despite noise

Identification possible weeks before merger

Abstract

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will catalogue the light-curves of up to 100 million quasars. Among these there can be up to approximately 100 ultra-compact massive black hole (MBH) binaries, which 5-15 years later can be detected in gravitational waves (GWs) by the Laser Interferometer Space Antenna (LISA). Here we assume that GWs from a MBH binary have been detected by LISA, and we assess whether or not its electromagnetic (EM) counterpart can be uniquely identified in archival LSST data as a periodic quasar. We use the binary's properties derived from the LISA waveform, such as the past evolution of its orbital frequency, its total mass, distance and sky localization, to predict the redshift, magnitude and historical periodicity of the quasar expected in the archival LSST data. We then use Monte Carlo simulations to compute the false alarm probability, i.e. the number of quasars in the LSST catalogue matching these properties by chance, based on the (extrapolated) quasar luminosity function, the sampling cadence of LSST, and intrinsic ``damped random walk (DRW)" quasar variability. We perform our analysis on four fiducial LISA binaries, with total masses and redshifts of $(M_{\rm bin}/{\rm M_{\odot}},z) = (3\times10^5,0.3)$, $(3\times10^6,0.3)$, $(10^7,0.3)$ and $(10^7,1)$. While DRW noise and aliasing due to LSST's cadence can produce false periodicities by chance, we find that the frequency chirp of the LISA source during the LSST observations washes out these noise peaks and allows the genuine source to stand out in Lomb-Scargle periodograms. We find that all four fiducial binaries yield excellent chances to be uniquely identified, with false alarm probabilities below $10^{-5}$, a week or more before their merger. This then enables deep follow-up EM observations targeting the individual EM counterparts during their inspiral stage.