Breakthrough Listen

Abstract:

A key science goal of large sky surveys such as those conducted by the Vera C. Rubin Observatory and precursors to the Square Kilometre Array is the identification of variable and transient objects. One approach is analyzing time series of the changing brightness of sources, namely, light curves. However, finding adequate statistical representations of light curves is challenging because of the sparsity of observations, irregular sampling, and nuisance factors inherent in astronomical data collection. The wide diversity of objects that a large-scale survey will observe also means that making parametric assumptions about the shape of light curves is problematic. We present a Gaussian process (GP) regression approach for characterizing light-curve variability that addresses these challenges. Our approach makes no assumptions about the shape of a light curve and, therefore, is general enough to detect a range of variable and transient source types. In particular, we propose using the joint distribution of GP amplitude hyperparameters to distinguish variable and transient candidates from nominally stable ones and apply this approach to 6394 radio light curves from the ThunderKAT survey. We compare our results with two variability metrics commonly used in radio astronomy, namely ην and Vν, and show that our approach has better discriminatory power and interpretability. Finally, we conduct a rudimentary search for transient sources in the ThunderKAT data set to demonstrate how our approach might be used as an initial screening tool. Computational notebooks in Python and R are available to help deploy this framework to other surveys.

Abstract:

Radio continuum emission provides a unique opportunity to study star formation unbiased by dust obscuration. However, if radio observations are to be used to accurately trace star formation to high redshifts, it is crucial that the physical processes that affect the radio emission from star-forming galaxies are well understood. While inverse Compton (IC) losses from the cosmic microwave background (CMB) are negligible in the local universe, the rapid increase in the strength of the CMB energy density with redshift [] means that this effect becomes increasingly important at . Using a sample of high-redshift () Lyman-break galaxies selected in the rest-frame ultraviolet (UV), we have stacked radio observations from the MIGHTEE survey to estimate their 1.4-GHz flux densities. We find that for a given rest-frame UV magnitude, the 1.4-GHz flux density and luminosity decrease with redshift. We compare these results to the theoretical predicted effect of energy losses due to IC scattering off the CMB, and find that the observed decrease is consistent with this explanation. We discuss other possible causes for the observed decrease in radio flux density with redshift at a given UV magnitude, such as a top-heavy initial mass function at high redshift or an evolution of the dust properties, but suggest that IC scattering is the most compelling explanation.

Abstract:

We present new high-spectral-resolution MeerKAT observations of absorption against the central region of the restarted, giant, X-shaped radio galaxy PKS2014–55, which exhibits morphological evidence of three distinct cycles of activity. We report a wide component (FWHM 38 7 km ) redshifted to 96 50 km , a deep-narrow detection (FWHM 19 6 km ) which is redshifted to 160 40 km, and a shallow component (FWHM 22 6 km) redshifted to 240 40 km . One of the three components exceeds the typical rotational velocity of 100 km , suggesting complex kinematics of the inflowing gas. These observations support the correlation between the occurrence of absorption and the rejuvenation of radio activity.

Abstract:

Abstract In this work we study a robust, Ks-band complete, spectroscopically-confirmed sample of 104 unobscured (Type-1) quasars within the COSMOS and XMM-LSS fields of the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Survey, at 0.60 < zspec < 3.41. The quasars are selected via gJKs colour-space and, with 1.3-GHz flux-densities reaching rms ≈ 3.0 μ Jy beam−1, we find a radio-loudness fraction of 5percnt. Thanks to the deep, multiwavelength datasets that are available over these fields, the properties of radio-loud and radio-quiet quasars can be studied in a statistically-robust way, with the emphasis of this work being on the active-galactic-nuclei (AGN)-related and star-formation-related contributions to the total radio emission. We employ multiple star-formation-rate estimates for the analysis so that our results can be compared more-easily with others in the literature, and find that the fraction of sources that have their radio emission dominated by the AGN crucially depends on the SFR estimate that is derived from the radio luminosity. When redshift dependence is not taken into account, a larger fraction of sources is classed as having their radio emission dominated by the AGN. When redshift dependence is considered, a larger fraction of our sample is tentatively classed as ‘starbursts’. We also find that the fraction of (possible) starbursts increases with redshift, and provide multiple suggestions for this trend.