ABSTRACT
Pulsar Timing Array experiments probe the presence of possible scalar or pseudoscalar ultralight dark matter particles through decade-long timing of an ensemble of galactic millisecond radio pulsars. With the second data release of the European Pulsar Timing Array, we focus on the most robust scenario, in which dark matter interacts only gravitationally with ordinary baryonic matter. Our results show that ultralight particles with masses 10^{-24.0} eVâ²mâ²10^{-23.3} eV cannot constitute 100% of the measured local dark matter density, but can have at most local density ρâ²0.3 GeV/cm^{3}.
ABSTRACT
Gaussian process regression (GPR) is a non-parametric Bayesian technique for interpolating or fitting data. The main barrier to further uptake of this powerful tool rests in the computational costs associated with the matrices which arise when dealing with large datasets. Here, we derive some simple results which we have found useful for speeding up the learning stage in the GPR algorithm, and especially for performing Bayesian model comparison between different covariance functions. We apply our techniques to both synthetic and real data and quantify the speed-up relative to using nested sampling to numerically evaluate model evidences.
ABSTRACT
The paucity of observed supermassive black hole binaries (SMBHBs) may imply that the gravitational wave background (GWB) from this population is anisotropic, rendering existing analyses suboptimal. We present the first constraints on the angular distribution of a nanohertz stochastic GWB from circular, inspiral-driven SMBHBs using the 2015 European Pulsar Timing Array data. Our analysis of the GWB in the ~2-90 nHz band shows consistency with isotropy, with the strain amplitude in l>0 spherical harmonic multipoles â²40% of the monopole value. We expect that these more general techniques will become standard tools to probe the angular distribution of source populations.
