Investigations in time and of space using the FIRST survey : radio source variability and the evolution of FR II quasars

The FIRST survey covered ~ 10,000 deg² of the sky over a decade, providing unprecedented levels of flux density sensitivity (~ 1 mJy) at 1.4 GHz, uniformity to within 15% (at ~ 0.15 mJy rms), 5".4 angular resolution, astrometric accuracy to better than 1" and has cataloged ≥ 800,000 sources. It has made enormous contributions to diverse scientific ends including such subjects as radio source populations, quasars, large-scale structure and clustering of radio sources, gravitational lensing, cosmology, etc. I present the motivation, analysis and results of two projects also intended to demonstrate the power and expand the scope of the FIRST survey's scientific reach. A comprehensive search for variable and transient radio sources has been conducted using the ~ 55,000 snapshot images of the FIRST survey. An analysis leading to the discovery of 1,651 variable and transient objects down to mJy levels over a wide range of timescales (few minutes to years) is presented. The multi-wavelength matching for counterparts reveals the diverse classes of objects exhibiting variability. Interestingly, ~ 60% of the objects in the sample have either no classified counterparts or no corresponding sources at any other wavelength and require multi-wavelength follow-up observations. I discuss these classes of variables and speculate on the identity of objects that lack multi-wavelength counterparts. Thus, the FIRST survey has yielded the largest sample by far of radio variables and transients to date to unprecedented levels of sensitivity and sky coverage and demonstrates the promise of future radio instruments which have transient-detection as one of their key science projects. For decades, radio astronomers have attempted to use double-lobed radio sources to constrain the angular size-redshift (θ − z) relation and to derive cosmological parameters therefrom. Most of the early attempts have, embarrassingly, shown general consistency with a static Euclidean universe rather than with Friedmann models. These earlier results can be attributed to a combination of selection effects, sample definition problems, and inconsistencies in analysis. However, some recent and more successful analyses have still failed to distinguish among different Friedmann models. A catalog of ~ 680 FR II quasars was constructed from the FIRST sources with redshifts taken from the SDSS spectroscopic QSO catalog and a similar sized sample from the SDSS photometric QSO catalog which are the largest quasar compilations to date. Using statistical analyses, no evidence for intrinsic evolution of sizes with redshift is found. A static Euclidean model for the universe is clearly ruled out. However, new degeneracies between parameters in the multi-dimensional χ²-surface are found which can only be resolved with additional, independent information. Notable differences are found between the spectroscopic and photometric samples raising questions about the nature and origin of these populations

Interferometric Image Reconstruction using Closure Invariants and Machine Learning

Closure invariants in interferometry carry calibration-independent information about the morphology of an observed object. Excepting simple cases, a mapping between closure invariants and morphologies is not well established. We aim to demonstrate that closure invariants can be used to classify the morphology and estimate the morphological parameters using simple Machine Learning models. We consider 6 morphological classes -- point-like, uniform circular disc, crescent, dual disc, crescent with elliptical accretion disc, and crescent with double jet lobes -- described by phenomenological parameters. Using simple logistic regression, multi-layer perceptron (MLP), convolutional neural network, and random forest models on closure invariants obtained from a sparse aperture coverage, we find that all models except logistic regression are able to classify the morphology with an $F_1$ score $\gtrsim 0.8$. The classification accuracy notably improves with greater aperture coverage. We also estimate morphological parameters of uniform circular disc, crescent, and dual disc using simple MLP models, and perform a parametric image reconstruction. The reconstructed images do not retain information about absolute position or intensity scale. The estimated parameters and reconstructed images are found to correspond well with the inputs. However, the prediction accuracy worsens with increasing morphological complexity. This proof-of-concept method opens an independent approach to interferometric imaging under challenging observing conditions such as that faced by the Event Horizon Telescope and Very Long Baseline Interferometry in general, and can complement other methods to robustly constrain an object's morphology.Comment: Submitted to RAS Techniques and Instruments (RASTI) special edition "Next-Generation Interferometric Image Reconstruction". 13 pages including appendix, 35 figures grouped into 8 captioned figure