The Loud Tail of the Supermassive Black Hole Binary Population: Multimessenger Candidates and Prospects for SKAO

Author(s)

Raidal, Juhan, Vaskonen, Ville, Urrutia, Juan, Veermäe, Hardi

Abstract

We assess whether electromagnetically identified supermassive black hole (SMBH) binary candidates populate the rare, high-amplitude tail of the gravitational wave (GW) amplitude distribution. Using an SMBH binary population model fitted to the NANOGrav 15-year data, we find that 3C~66B and Mrk~501 are likely to stand out from the GW background, making them promising targets for individual-source searches. Furthermore, we show that individual detections can probe the binary hardening mechanism, as models with strong environmental hardening predict a higher abundance of individually resolvable binaries than purely GW-driven models. Applying the same population fits and accounting for the confusion noise from the unresolved population, we forecast that the Square Kilometre Array Observatory (SKAO) will resolve tens of individual binaries, with 3C~66B robustly detectable.

Figures

Posteriors of the SMBH binary model fit against the NANOGrav 15-year data. The contours indicate the $1,2,3\sigma$ credible regions. We also show the posteriors of the expected number of SKAO-resolvable binaries, $N_{\rm res}$, derived from the posteriors of model parameters.
Caption Posteriors of the SMBH binary model fit against the NANOGrav 15-year data. The contours indicate the $1,2,3\sigma$ credible regions. We also show the posteriors of the expected number of SKAO-resolvable binaries, $N_{\rm res}$, derived from the posteriors of model parameters.
Electromagnetically identified SMBH binary candidates (Table~\ref{tab:candidates}) in the plane of characteristic timing residual $\sigma_k$ versus GW frequency, placed at $f_{\rm GW}=2/T$ with the exception of OJ287, which is denoted by the red band. The uncertainty in mass ratio is shown by a solid line connecting the upper and lower magnitude estimates. The orange violins show the NANOGrav 15-year free-spectrum posteriors, and the shaded bands show the $68\%$, $95\%$, and $99\%$ ranges of the distribution obtained by mapping the posteriors shown in Fig.~\ref{fig:corner} onto the median GW spectrum in the GW-only (green) and GW+environment (blue) cases. The dashed and dotted green curves show the projected single-source and stochastic-background sensitivities of SKAO. The gray shading shows NANOGrav 15-year bound for individual SMBH binaries~\cite{NANOGrav:2023pdq}.
Caption Electromagnetically identified SMBH binary candidates (Table~\ref{tab:candidates}) in the plane of characteristic timing residual $\sigma_k$ versus GW frequency, placed at $f_{\rm GW}=2/T$ with the exception of OJ287, which is denoted by the red band. The uncertainty in mass ratio is shown by a solid line connecting the upper and lower magnitude estimates. The orange violins show the NANOGrav 15-year free-spectrum posteriors, and the shaded bands show the $68\%$, $95\%$, and $99\%$ ranges of the distribution obtained by mapping the posteriors shown in Fig.~\ref{fig:corner} onto the median GW spectrum in the GW-only (green) and GW+environment (blue) cases. The dashed and dotted green curves show the projected single-source and stochastic-background sensitivities of SKAO. The gray shading shows NANOGrav 15-year bound for individual SMBH binaries~\cite{NANOGrav:2023pdq}.
Posterior distributions of the expected number of binaries that are louder and at higher frequency than the candidate binaries in the GW-only (green) and GW+environment (coloured) models. Vertical dotted lines mark the medians and the dashed black line indicates $\bar N=1$. The probability of absence of louder sources, $P(0)$, is quoted for each model in the panel titles.
Caption Posterior distributions of the expected number of binaries that are louder and at higher frequency than the candidate binaries in the GW-only (green) and GW+environment (coloured) models. Vertical dotted lines mark the medians and the dashed black line indicates $\bar N=1$. The probability of absence of louder sources, $P(0)$, is quoted for each model in the panel titles.
SNRs $\rho = A^{(1)}/A_{\rm min}^{\rm eff}$ of the EM-identified candidates of Table~\ref{tab:candidates} for SKAO, including the confusion noise from unresolved binaries. The bars show the $68\%$, $95\%$ and $99\%$ credible ranges obtained by mapping the PTA posteriors of Fig.~\ref{fig:corner} onto $A_{\rm min}^{\rm eff}$ and marginalizing over the candidate mass uncertainties as in Fig.~\ref{fig:expected}, with the open circle marking the median. The vertical tick gives the median obtained when the confusion noise is neglected. The dashed line marks the detection threshold $\rho_{\rm th}=3$, and the right-hand axis quotes the probability that the candidate exceeds it.
Caption SNRs $\rho = A^{(1)}/A_{\rm min}^{\rm eff}$ of the EM-identified candidates of Table~\ref{tab:candidates} for SKAO, including the confusion noise from unresolved binaries. The bars show the $68\%$, $95\%$ and $99\%$ credible ranges obtained by mapping the PTA posteriors of Fig.~\ref{fig:corner} onto $A_{\rm min}^{\rm eff}$ and marginalizing over the candidate mass uncertainties as in Fig.~\ref{fig:expected}, with the open circle marking the median. The vertical tick gives the median obtained when the confusion noise is neglected. The dashed line marks the detection threshold $\rho_{\rm th}=3$, and the right-hand axis quotes the probability that the candidate exceeds it.
Posterior distribution of the expected number of individually resolvable sources $\bar N_{\rm res}$, Eq.~\eqref{eq:Nres}, for SKAO, obtained by mapping the NANOGrav 15-year posteriors of Fig.~\ref{fig:corner} onto $\bar N_{\rm res}$. The solid curves include the confusion noise from the unresolved binaries while the dashed curves use only the bare SKAO sensitivity. Blue and green show the GW+environment and GW-only models obtained with the variance-averaged likelihood, and red the GW+environment model obtained with the log-normal approximation. The vertical lines mark the medians.
Caption Posterior distribution of the expected number of individually resolvable sources $\bar N_{\rm res}$, Eq.~\eqref{eq:Nres}, for SKAO, obtained by mapping the NANOGrav 15-year posteriors of Fig.~\ref{fig:corner} onto $\bar N_{\rm res}$. The solid curves include the confusion noise from the unresolved binaries while the dashed curves use only the bare SKAO sensitivity. Blue and green show the GW+environment and GW-only models obtained with the variance-averaged likelihood, and red the GW+environment model obtained with the log-normal approximation. The vertical lines mark the medians.
Forecast distribution of SMBH binaries individually resolvable by SKAO in redshift $z$, chirp mass $\mathcal{M}$, and observed GW frequency $f$ for the best fit parameters of the PTA analysis. The left panels show the GW-only model and the right panels the GW+environment model, with the total expected number of resolvable sources $\bar{N}_{\rm res}$ indicated in each title and the colour scale giving the number of resolvable events per pixel. The symbols show the strongest candidate sources 3C~66B and Mrk~501.
Caption Forecast distribution of SMBH binaries individually resolvable by SKAO in redshift $z$, chirp mass $\mathcal{M}$, and observed GW frequency $f$ for the best fit parameters of the PTA analysis. The left panels show the GW-only model and the right panels the GW+environment model, with the total expected number of resolvable sources $\bar{N}_{\rm res}$ indicated in each title and the colour scale giving the number of resolvable events per pixel. The symbols show the strongest candidate sources 3C~66B and Mrk~501.
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