Applicability of multicomponent study on Bayesian searches for targeted anisotropic stochastic gravitational-wave background

Stochastic background gravitational waves have not yet been detected by ground-based laser interferometric detectors, but recent improvements in detector sensitivity have raised considerable expectations for their eventual detection. Previous studies have introduced methods for exploring anisotropic background gravitational waves using Bayesian statistics. These studies represent a groundbreaking approach by offering physically motivated anisotropy mapping that is distinct from the Singular Value Decomposition regularization of the Fisher Information Matrix. However, they are limited by the use of a single model, which can introduce potential bias when dealing with complex data that may consist of a mixture of multiple models. Here, we demonstrate the bias introduced by a single-component model approach in the parametric interpretation of anisotropic stochastic gravitational-wave backgrounds, and we confirm that using multiple-component models can mitigate this bias.