European Pulsar Timing Array Limits On An Isotropic Stochastic Gravitational-Wave Background

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 simultaneously for the intrinsic noise parameters for each pulsar, along with common correlated signals including clock, and Solar System ephemeris errors, obtaining a robust 95$%$ upper limit on the dimensionless strain amplitude $A$ of the background of $A<3.0times 10^{-15}$ at a reference frequency of $1mathrm{yr^{-1}}$ and a spectral index of $13/3$, corresponding to a background from inspiralling super-massive black hole binaries, constraining the GW energy density to $Omega_mathrm{gw}(f)h^2 < 1.1times10^{-9}$ at 2.8 nHz. We also present limits on the correlated power spectrum at a series of discrete frequencies, and show that our sensitivity to a fiducial isotropic GWB is highest at a frequency of $sim 5times10^{-9}$~Hz. Finally we discuss the implications of our analysis for the astrophysics of supermassive black hole binaries, and present 95$%$ upper limits on the string tension, $Gmu/c^2$, characterising a background produced by a cosmic string network for a set of possible scenarios, and for a stochastic relic GWB. For a Nambu-Goto field theory cosmic string network, we set a limit $Gmu/c^2<1.3times10^{-7}$, identical to that set by the {it Planck} Collaboration, when combining {it Planck} and high-$ell$ Cosmic Microwave Background data from other experiments. For a stochastic relic background we set a limit of $Omega^mathrm{relic}_mathrm{gw}(f)h^2<1.2 times10^{-9}$, a factor of 9 improvement over the most stringent limits previously set by a pulsar timing array.

A Bayesian blind survey for cold molecular gas in the Universe

A new Bayesian method for performing an image domain search for line-emitting galaxies is presented. The method uses both spatial and spectral information to robustly determine the source properties, employing either simple Gaussian, or other physically motivated models whilst using the evidence to determine the probability that the source is real. In this paper, we describe the method, and its application to both a simulated data set, and a blind survey for cold molecular gas using observations of the Hubble Deep Field North taken with the Plateau de Bure Interferometer. We make a total of 6 robust detections in the survey, 5 of which have counterparts in other observing bands. We identify the most secure detections found in a previous investigation, while finding one new probable line source with an optical ID not seen in the previous analysis. This study acts as a pilot application of Bayesian statistics to future searches to be carried out both for low-$J$ CO transitions of high redshift galaxies using the JVLA, and at millimeter wavelengths with ALMA, enabling the inference of robust scientific conclusions about the history of the molecular gas properties of star-forming galaxies in the Universe through cosmic time.

Bayesian estimation of non-Gaussianity in pulsar timing analysis

We introduce a method for performing a robust Bayesian analysis of non-Gaussianity present in pulsar timing data, simultaneously with the pulsar timing model, and additional stochastic parameters such as those describing red spin noise and dispersion measure variations. The parameters used to define the presence of non-Gaussianity are zero for Gaussian processes, giving a simple method of defining the strength of non-Gaussian behaviour. We use simulations to show that assuming Gaussian statistics when the noise in the data is drawn from a non-Gaussian distribution can significantly increase the uncertainties associated with the pulsar timing model parameters. We then apply the method to the publicly available 15 year Parkes Pulsar Timing Array data release 1 dataset for the binary pulsar J0437$-$4715. In this analysis we present a significant detection of non-Gaussianity in the uncorrelated non-thermal noise, but we find that it does not yet impact the timing model or stochastic parameter estimates significantly compared to analysis performed assuming Gaussian statistics. The methods presented are, however, shown to be of immediate practical use for current European Pulsar Timing Array (EPTA) and International Pulsar Timing Array (IPTA) datasets.

How to take the interstellar weather with you in pulsar timing analysis

Here we present a Bayesian method of including discrete measurements of dispersion measure due to the interstellar medium in the direction of a pulsar as prior information in the analysis of that pulsar. We use a simple simulation to show the efficacy of this method, where the inclusion of the additional measurements results in both a significant increase in the precision with which the timing model parameters can be obtained, and an improved upper limit on the amplitude of any red noise in the dataset. We show that this method can be applied where no multi-frequency data exists across much of the dataset, and where there is no simultaneous multi-frequency data for any given observing epoch. Including such information in the analysis of upcoming International Pulsar Timing Array (IPTA) and European Pulsar Timing Array (EPTA) data releases could therefore prove invaluable in obtaining the most constraining limits on gravitational wave signals within those datasets.

TempoNest: A Bayesian approach to pulsar timing analysis

A new Bayesian software package for the analysis of pulsar timing data is presented in the form of TempoNest which allows for the robust determination of the non-linear pulsar timing solution simultaneously with a range of additional stochastic parameters. This includes both red spin noise and dispersion measure variations using either power law descriptions of the noise, or through a model-independent method that parameterises the power at individual frequencies in the signal. We use TempoNest to show that at noise levels representative of current datasets in the European Pulsar Timing Array (EPTA) and International Pulsar Timing Array (IPTA) the linear timing model can underestimate the uncertainties of the timing solution by up to an order of magnitude. We also show how to perform Bayesian model selection between different sets of timing model and stochastic parameters, for example, by demonstrating that in the pulsar B1937+21 both the dispersion measure variations and spin noise in the data are optimally modelled by simple power laws. Finally we show that not including the stochastic parameters simultaneously with the timing model can lead to unpredictable variation in the estimated uncertainties, compromising the robustness of the scientific results extracted from such analysis.

Variations in the Fundamental constants in the QSO Host J1148+5251 at z = 6.4 and the BR1202-0725 System at z = 4.7

We use sensitive observations of three high redshift sources; [CII] fine structure and CO(2-1) rotational transitions for the z=6.4 Quasar host galaxy (QSO) J1148+5251, and [CII] and CO(5-4) transitions from the QSO BR1202-0725 and its sub-millimeter companion (SMG) galaxy at z=4.7. We use these observations to place constraints on the quantity Dz = z(CO) - z(CII) for each source where z(CO) and z(CII) are the observed redshifts of the CO rotational transition and [CII] fine structure transition respectively, using a combination of approaches; 1) By modelling the emission line profiles using `shapelets to compare both the emission redshifts and the line profiles themselves, in order to make inferences about the intrinsic velocity differences between the molecular and atomic gas, and 2) By performing a marginalisation over all model parameters in order to calculate a non-parametric estimate of Dz. We derive 99% confidence intervals for the marginalised posterior of Dz of (-1.9 pm 1.3) x10^-3, (-3 pm 8) x10^-4 and (-2 pm 4) x10^-3 for J1148+5251, and the BR1202-0725 QSO and SMG respectively. We show the [CII] and CO(2-1) line profiles for J1148+5251 are consistent with each other within the limits of the data, whilst the [CII] and CO(5-4) line profiles from the BR1202-0725 QSO and SMG respectively have 65 and >99.9% probabilities of being inconsistent, with the CO(5-4) lines ~ 30% wider than the [CII] lines. Therefore whilst the observed values of Dz can correspond to variations in the quantity Delta F/F with cosmic time, where F=alpha^2/mu, with alpha the fine structure constant, and mu the proton-to-electron mass ratio, of both (-3.3 pm 2.3) x10^-4 for a look back time of 12.9 Gyr and of (-5 pm 15) x10^-5 for a look back time of 12.4 Gyr we propose that they are the result of the two species of gas being spatially separated as indicated by the inconsistencies in their line profiles.