MeerKAT

Abstract:

We present the first multiepoch broadband radio and millimeter monitoring of an off-nuclear tidal disruption event (TDE) using the Very Large Array, the Atacama Large Millimeter/submillimeter Array, the Allen Telescope Array, the Arcminute Microkelvin Imager Large Array, and the Submillimeter Array. The off-nuclear TDE AT 2024tvd exhibits double-peaked radio light curves and the fastest-evolving radio emission observed from a TDE to date. With respect to the optical discovery date, the first radio flare rises faster than Fν ∼ t9 at Δt = 88–131 days and then decays as fast as Fν ∼ t−6. The emergence of a second radio flare is observed at Δt ≈ 194 days with an initial fast rise of Fν ∼ t18 and an optically thin decline of Fν ∼ t−12. We interpret these observations in the context of a self-absorbed and free–free absorbed synchrotron spectrum, while accounting for both synchrotron and inverse Compton cooling. We find that a single prompt outflow cannot easily explain these observations and that it is likely that either there is only one outflow that was launched at Δt ∼ 80 days or there are two distinct outflows, with the second launched at Δt ∼ 170–190 days. The nature of these outflows, whether sub-, mildly, or ultrarelativistic, is still unclear, and we explore these different scenarios. Finally, we find a temporal coincidence between the launch time of the first radio-emitting outflow and the onset of a power-law component in the X-ray spectrum, attributed to inverse Compton scattering of thermal photons.

Abstract:

Abstract A tidal disruption event (TDE) occurs when a star travels too close to a supermassive black hole. In some cases, accretion of the disrupted material onto the black hole launches a relativistic jet. In this paper, we present a long-term observing campaign to study the radio and submillimeter emission associated with the fifth jetted/relativistic TDE: AT 2022cmc. Our campaign reveals a long-lived counterpart. We fit three different models to our data: a nonthermal jet, a spherical outflow consisting of both thermal and nonthermal electrons, and a jet with thermal and nonthermal electrons. We find that the data are best described by a relativistic spherical outflow propagating into an environment with a density profile following R −1.8. Comparison of AT 2022cmc to other TDEs finds agreement in the density profile of the environment but also that AT 2022cmc is twice as energetic as the other well-studied relativistic TDE, Swift J1644. Our observations of AT 2022cmc allow a thermal electron population to be inferred for the first time in a jetted transient, providing new insights into the microphysics of relativistic transients jets.

Abstract:

A tidal disruption event (TDE) occurs when a star travels too close to a supermassive black hole. In some cases, accretion of the disrupted material onto the black hole launches a relativistic jet. In this paper, we present a long-term observing campaign to study the radio and submillimeter emission associated with the fifth jetted/relativistic TDE: AT 2022cmc. Our campaign reveals a long-lived counterpart. We fit three different models to our data: a nonthermal jet, a spherical outflow consisting of both thermal and nonthermal electrons, and a jet with thermal and nonthermal electrons. We find that the data are best described by a relativistic spherical outflow propagating into an environment with a density profile following R−1.8. Comparison of AT 2022cmc to other TDEs finds agreement in the density profile of the environment but also that AT 2022cmc is twice as energetic as the other well-studied relativistic TDE, Swift J1644. Our observations of AT 2022cmc allow a thermal electron population to be inferred for the first time in a jetted transient, providing new insights into the microphysics of relativistic transients jets.

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:

Abstract We investigate the clustering of Lyman-break galaxies at redshifts of 3 ≲ z ≲ 5 within the COSMOS field by measuring the angular two-point correlation function. Our robust sample of ~60,000 bright (mUV ≲ 27) Lyman-break galaxies was selected based on spectral energy distribution fitting across 14 photometric bands spanning optical and near-infrared wavelengths. We constrained both the 1- and 2-halo terms at separations up to 300 arcsec, finding an excess in the correlation function at scales corresponding to <20 kpc, consistent with enhancement due to clumps in the same galaxy or interactions on this scale. We then performed Bayesian model fits on the correlation functions to infer the Halo Occupation Distribution parameters, star formation duty cycle, and galaxy bias in three redshift bins. We examined several cases where different combinations of parameters were varied, showing that our data can constrain the slope of the satellite occupation function, which previous studies have fixed. For an MUV-limited sub-sample, we found galaxy bias values of $b_g=3.18^{+0.14}_{-0.14}$ at z ≃ 3, $b_g=3.58^{+0.27}_{-0.29}$ at z ≃ 4, $b_g=4.27^{+0.25}_{-0.26}$ at z ≃ 5. The duty cycle values are $0.62^{+0.25}_{-0.26}$, $0.40^{+0.34}_{-0.22}$, and $0.39^{+0.31}_{-0.20}$,respectively. These results suggest that, as the redshift increases, there is a slight decrease in the host halo masses and a shorter timescale for star formation in bright galaxies, at a fixed rest-frame UV luminosity threshold.