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Precise measurements of the black hole mass are essential to gain insight on the black hole and host galaxy co-evolution. A direct measure of the black hole mass is often restricted to nearest galaxies and instead, an indirect method using the single-epoch virial black hole mass estimation is used for objects at high redshifts. However, this method is subjected to biases and uncertainties as it is reliant on the scaling relation from a small sample of local active galactic nuclei. In this study, we propose the application of conformalized quantile regression (CQR) to quantify the uncertainties of the black hole predictions in a machine learning setting. We compare CQR with various prediction interval techniques and demonstrated that CQR can provide a more useful prediction interval indicator. In contrast to baseline approaches for prediction interval estimation, we show that the CQR method provides prediction intervals that adjust to the black hole mass and its related properties. That is it yields a tighter constraint on the prediction interval (hence more certain) for a larger black hole mass, and accordingly, bright and broad spectral line width source. Using a combination of neural network model and CQR framework, the recovered virial black hole mass predictions and uncertainties are comparable to those measured from the Sloan Digital Sky Survey. The code is publicly available. [ABSTRACT FROM AUTHOR]

Given the anisotropic emission from quasar accretion discs, their viewing angle affects estimates of the quasar luminosity, black hole mass, and Eddington ratio. Discs appear overluminous when viewed pole-on and underluminous when viewed at high inclination. In radio-quiet quasars, the viewing angle is usually unknown, although spectroscopic indicators have been proposed. Here, we use a recently discovered universality in the variability structure function (SF) of quasar light curves (LCs), where all quasars show the same SF when clocks run in units of orbital time-scale. As an offset from the mean relation can be caused by incorrect orbital time-scales and thus incorrect luminosities, we correlate these offsets with suggested inclination indicators. We derive SFs from NASA/Asteroid Terrestrial-impact Last Alert System (ATLAS) LCs spanning ∼6 yr of observation, using a sample of 183 luminous quasars with measured H β lines as well as 753 quasars with C  iv and Mg  ii lines. Starting from the proposed orientation indicators, we expect quasars with narrower H β lines and with more blueshifted C  iv lines to be viewed more pole-on and thus appear overluminous. In contrast, our SF analysis finds that presumed pole-on discs appear underluminous, consistently for both line indicators. We discuss possible explanations for the behaviour of quasars with highly blueshifted C  iv lines irrespective of inclination angle, including dusty outflows that might render the accretion disc underluminous and flatter disc temperature profiles with longer orbital time-scales than in thin-disc models but reach no satisfying conclusion. [ABSTRACT FROM AUTHOR]

New classes of astronomical objects are often discovered serendipitously. The enormous data volumes produced by recent high-time resolution, radio-telescope surveys imply that efficient algorithms are required for a discovery. Such algorithms are usually tuned to detect specific, known sources. Existing data sets therefore likely contain unknown astronomical sources, which will remain undetected unless algorithms are developed that can detect a more diverse range of signals. We present the Single-dish PARKES data sets for finding the uneXpected (SPARKESX), a compilation of real and simulated high-time resolution observations. SPARKESX comprises three mock surveys from the Parkes ' Murriyang ' radio telescope. A broad selection of simulated and injected expected signals (such as pulsars and fast radio bursts), poorly characterized signals (plausible flare star signatures), and 'unknown unknowns' are generated for each survey. The goal of this challenge is to aid in the development of new algorithms that can detect a wide range of source types. We show how successful a typical pipeline based on the standard pulsar search software, presto , is at finding the injected signals. The data set is publicly available at https://doi.org/10.25919/fd4f-0g20 (Yong et al. 2022). [ABSTRACT FROM AUTHOR]

We describe a new software package for simulating channelized, high-time resolution data streams from radio telescopes. The software simulates data from the telescope and observing system taking into account the observation strategy, receiver system, and digitization. The signatures of pulsars, fast radio bursts and flare stars are modelled, including frequency-dependent effects such as scattering and scintillation. We also simulate more generic signals using spline curves and images. Models of radio frequency interference include signals from satellites, terrestrial transmitters and impulsive, broad-band signals. The simulated signals can also be injected into real data sets. Uses of this software include the production of machine learning training data sets, development, and testing of new algorithms to search for anomalous patterns and to characterize processing pipelines. [ABSTRACT FROM AUTHOR]

Since the discovery of active galactic nuclei (AGN) and their subclasses, a unification scheme of AGN has been long sought. Orientation-based unified models predict that some of the diversity within AGN subclasses can be explained by the different viewing angles of the observer. Several orientation categorizations have been suggested, but a widely applicable measure has yet to be found. Using the properties of the ultraviolet and optical broad emission lines of quasars, in particular the velocity offsets and line widths of high-ionization |$\rm{C\,\small {IV}}$| and low-ionization |$\rm{Mg\,\small {II}}$| lines, a correlation has been measured. It is postulated that this correlation is due to the viewing angle of the observer. Comparison with other orientation tracers shows consistency with this interpretation. Using a simulation of a wide angle disc-wind model for the broad emission line region, we successfully replicate the observed correlation with inclination. Future more detailed modelling will not only enable improved accuracy in the determination of the viewing angle to individual AGN but also substantially increase our understanding of the emitting regions of AGN. [ABSTRACT FROM AUTHOR]

A key to understanding quasar unification paradigms is the emission properties of broad absorption line quasars (BALQs). The fact that only a small fraction of quasar spectra exhibit deep absorption troughs blueward of the broad permitted emission lines provides a crucial clue to the structure of quasar emitting regions. To learn whether it is possible to discriminate between the BALQ and non-BALQ populations given the observed spectral properties of a quasar, we employ two approaches: one based on statistical methods and the other supervised machine learning classification, applied to quasar samples from the Sloan Digital Sky Survey. The features explored include continuum and emission line properties, in particular the absolute magnitude, redshift, spectral index, line width, asymmetry, strength, and relative velocity offsets of high-ionization C  iv λ1549 and low-ionization Mg  ii λ2798 lines. We consider a complete population of quasars, and assume that the statistical distributions of properties represent all angles where the quasar is viewed without obscuration. The distributions of the BALQ and non-BALQ sample properties show few significant differences. None of the observed continuum and emission line features are capable of differentiating between the two samples. Most published narrow disc-wind models are inconsistent with these observations, and an alternative disc-wind model is proposed. The key feature of the proposed model is a disc-wind filling a wide opening angle with multiple radial streams of dense clumps. [ABSTRACT FROM AUTHOR]