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The formation and growth processes of supermassive black holes (SMBHs) are not well constrained. SMBH population models, however, provide specific predictions for the properties of the gravitational-wave background (GWB) from binary SMBHs in merging galaxies throughout the Universe. Using observations from the Parkes Pulsar Timing Array, we constrain the fractional GWB energy density with 95% confidence to be ${Omega}_{GW}(H_0/73 {rm km} {rm s}^{-1} {rm Mpc}^{-1})^2 < 1.3 times 10^{-9}$ at a frequency of 2.8 nHz, which is approximately a factor of six more stringent than previous limits. We compare our limit to models of the SMBH population and find inconsistencies at confidence levels between 46% and 91%. For example, the standard galaxy formation model implemented in the Millennium simulations is inconsistent with our limit with 50% probability.
We have searched for continuous gravitational wave (CGW) signals produced by individually resolvable, circular supermassive black hole binaries (SMBHBs) in the latest EPTA dataset, which consists of ultra-precise timing data on 41 millisecond pulsars
Pulsar timing observations are used to place constraints on the rate of coalescence of supermassive black-hole (SMBH) binaries as a function of mass and redshift. In contrast to the indirect constraints obtained from other techniques, pulsar timing o
Pulsar timing arrays (PTAs) are expected to detect gravitational waves (GWs) from individual low-redshift (z<1.5) compact supermassive (M>10^9 Msun) black hole (SMBH) binaries with orbital periods of approx. 0.1 - 10 yrs. Identifying the electromagne
Precision timing of large arrays (>50) of millisecond pulsars will detect the nanohertz gravitational-wave emission from supermassive binary black holes within the next ~3-7 years. We review the scientific opportunities of these detections, the requi
We present new limits on an isotropic stochastic gravitational-wave background (GWB) using a six pulsar dataset spanning 18 yr of observations from the 2015 European Pulsar Timing Array data release. Performing a Bayesian analysis, we fit simultaneou