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Detecting continuous nanohertz gravitational waves (GWs) generated byindividual close binaries of supermassive black holes (CB-SMBHs) is one of theprimary objectives of pulsar timing arrays (PTAs). The detection sensitivity isslated to increase significantly as the number of well-timed millisecondpulsars will increase by more than an order of magnitude with the advent ofnext-generation radio telescopes. Currently, the Bayesian analysis pipelineusing parallel tempering Markov chain Monte Carlo has been applied in multiplestudies for CB-SMBH searches, but it may be challenged by the highdimensionality of the parameter space for future large-scale PTAs. One solutionis to reduce the dimensionality by maximizing or marginalizing overuninformative parameters semi-analytically, but it is not clear whether thisapproach can be extended to more complex signal models without making overlysimplified assumptions. Recently, the method of diffusive nested (DNest)sampling shown the capability of coping with high dimensionality andmultimodality effectively in Bayesian analysis. In this paper, we apply DNestto search for continuous GWs in simulated pulsar timing residuals and find thatit performs well in terms of accuracy, robustness, and efficiency for a PTAincluding $\mathcal{O}(10^2)$ pulsars. DNest also allows a simultaneous searchof multiple sources elegantly, which demonstrates its scalability and generalapplicability. Our results show that it is convenient and also high beneficialto include DNest in current toolboxes of PTA analysis.

Search for Continuous Gravitational Wave Signals in Pulsar Timing Residuals: A New Scalable Approach with Diffusive Nested Sampling