Detection and parameter estimation of supermassive black hole ringdown signals using a pulsar timing array

Gravitational wave (GW) searches using pulsar timing arrays (PTAs) are commonly assumed to be limited to a GW frequency of $\ensuremath{\lesssim}4\ifmmode\times\else\texttimes\fi{}{10}^{\ensuremath{-}7}\text{ }\text{ }\mathrm{Hz}$ given by the Nyquist rate associated with the average observational cadence of 2 weeks for a single pulsar. However, by taking advantage of asynchronous observations of multiple pulsars, a PTA can detect GW signals at higher frequencies. This allows a sufficiently large PTA to detect and characterize the ringdown signals emitted following the merger of supermassive binary black holes (SMBBHs), leading to stringent tests of the no-hair theorem in the mass range of such systems. Such large-scale PTAs are imminent with the advent of the FAST telescope and the upcoming era of the Square Kilometer Array (SKA). To scope out the data analysis challenges involved in such a search, we propose a likelihood-based method coupled with particle swarm optimization and apply it to a simulated large-scale PTA comprised of 100 pulsars, each having a timing residual noise standard deviation of 100 nsec, with randomized observation times. Focusing on the dominant (2, 2) mode of the ringdown signal, we show that it is possible to achieve a 99% detection probability with a false alarm probability below 0.2% for an optimal signal-to-noise ratio (SNR) $>10$. This corresponds, for example, to an equal-mass nonspinning SMBBH with an observer frame chirp mass ${M}_{c}=9.52\ifmmode\times\else\texttimes\fi{}{10}^{9}{M}_{\ensuremath{\bigodot}}$ at a luminosity distance of ${D}_{L}=420\text{ }\text{ }\mathrm{Mpc}$.