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The extremely high sensitivity and resolution of the Square Kilometre Array (SKA) will be useful for addressing a wide set of themes relevant for cosmology, in synergy with current and future cosmic microwave background (CMB) projects. Many of these themes also have a link with future optical-IR and X-ray observations. We discuss the scientific perspectives for these goals, the instrumental requirements and the observational and data analysis approaches, and identify several topics that are important for cosmology and astrophysics at different cosmic epochs.
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 physica lly 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.
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.
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 efficac y 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.
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 param eters. 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.
The Arcminute Microkelvin Imager (AMI) is a telescope specifically designed for high sensitivity measurements of low-surface-brightness features at cm-wavelength and has unique, important capabilities. It consists of two interferometer arrays operati ng over 13.5-18 GHz that image structures on scales of 0.5-10 arcmin with very low systematics. The Small Array (AMI-SA; ten 3.7-m antennas) couples very well to Sunyaev-Zeldovich features from galaxy clusters and to many Galactic features. The Large Array (AMI-LA; eight 13-m antennas) has a collecting area ten times that of the AMI-SA and longer baselines, crucially allowing the removal of the effects of confusing radio point sources from regions of low surface-brightness, extended emission. Moreover AMI provides fast, deep object surveying and allows monitoring of large numbers of objects. In this White Paper we review the new science - both Galactic and extragalactic - already achieved with AMI and outline the prospects for much more.
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