Kiloparsec-scale AGN outflows and feedback in merger-free galaxies
Monthly Notices of the Royal Astronomical Society Oxford University Press 507:3 (2021) 3985-3997
Authors:
Rj Smethurst, Bd Simmons, A Coil, Cj Lintott, W Keel, Kl Masters, E Glikman, Gck Leung, J Shanahan, Il Garland
Abstract:
Recent observations and simulations have challenged the long-held paradigm that mergers are the dominant mechanism driving the growth of both galaxies and supermassive black holes (SMBH), in favour of non-merger (secular) processes. In this pilot study of merger-free SMBH and galaxy growth, we use Keck Cosmic Web Imager spectral observations to examine four low-redshift (0.043 < z < 0.073) disc-dominated ‘bulgeless’ galaxies hosting luminous active galactic nucleus (AGN), assumed to be merger-free. We detect blueshifted broadened [O III] emission from outflows in all four sources, which the [OIII]/Hβ ratios reveal are ionized by the AGN. We calculate outflow rates in the range 0.12−0.7 M⊙ yr−1, with velocities of 675−1710 km s−1, large radial extents of 0.6−2.4 kpc, and SMBH accretion rates of 0.02−0.07 M⊙ yr−1. We find that the outflow rates, kinematics, and energy injection rates are typical of the wider population of low-redshift AGN, and have velocities exceeding the galaxy escape velocity by a factor of ∼30, suggesting that these outflows will have a substantial impact through AGN feedback. Therefore, if both merger-driven and non-merger-driven SMBH growth lead to co-evolution, this suggests that co-evolution is regulated by feedback in both scenarios. Simulations find that bars and spiral arms can drive inflows to galactic centers at rates an order of magnitude larger than the combined SMBH accretion and outflow rates of our four targets. This work therefore provides further evidence that non-merger processes are sufficient to fuel SMBH growth and AGN outflows in disc galaxies.
Secularly powered outflows from AGN: the dominance of non-merger driven supermassive black hole growth
Monthly notices of the Royal Astronomical Society Oxford University Press 489:3 (2019) 4014-4031
Authors:
RJ Smethurst, BD Simmons, Christopher Lintott, J Shanahan
Abstract:
Recent observations and simulations have revealed the dominance of secular processes over mergers in driving the growth of both supermassive black holes (SMBH) and galaxy evolution. Here we obtain narrowband imaging of AGN powered outflows in a sample of 12 galaxies with disk-dominated morphologies, whose history is assumed to be merger-free. We detect outflows in 10/12 sources in narrow band imaging of the [OIII] 5007 A˚ emission using filters on the Shane-3m telescope. We calculate a mean outflow rate for these AGN of 0.95±0.14 M⊙ yr−1. This exceeds the mean accretion rate of their SMBHs (0.054±0.039 M⊙ yr−1) by a factor of ∼18. Assuming that the galaxy must provide at least enough material to power both the AGN and the outflow, this gives a lower limit on the average inflow rate of ∼1.01±0.14 M⊙ yr−1, a rate which simulations show can be achieved by bars, spiral arms and cold accretion. We compare our disk dominated sample to a sample of nearby AGN with merger dominated histories and show that the black hole accretion rates in our sample are 5 times higher (4.2σ) and the outflow rates are 5 times lower ( 2.6σ). We suggest that this could be a result of the geometry of the smooth, planar inflow in a secular dominated system, which is both spinning up the black hole to increase accretion efficiency and less affected by feedback from the outflow, than in a merger-driven system with chaotic quasi-spherical inflows. This work provides further evidence that secular processes are sufficient to fuel SMBH growth.
Supermassive black holes in disk-dominated galaxies outgrow their bulgesand co-evolve with their host galaxies
Monthly Notices of the Royal Astronomical Society Oxford University Press 470:2 (2017) 1559-1569
Authors:
BD Simmons, RJ Smethurst, Christopher Lintott
Abstract:
The deep connection between galaxies and their supermassive black holes is central to modern astrophysics and cosmology. The observed correlation between galaxy and black hole mass is usually attributed to the contribution of major mergers to both. We make use of a sample of galaxies whose disk-dominated morphologies indicate a major-merger-free history and show that such systems are capable of growing supermassive black holes at rates similar to quasars. Comparing black hole masses to conservative upper limits on bulge masses, we show that the black holes in the sample are typically larger than expected if processes creating bulges are also the primary driver of black hole growth. The same relation between black hole and total stellar mass of the galaxy is found for the merger-free sample as for a sample which has experienced substantial mergers, indicating that major mergers do not play a significant role in controlling the coevolution of galaxies and black holes. We suggest that more fundamental processes which contribute to galaxy assembly are also responsible for black hole growth.
SNITCH: seeking a simple, informative star formation history inference tool
Monthly Notices of the Royal Astronomical Society Oxford University Press 484:3 (2019) 3590-3603
Authors:
Rebecca J Smethurst, M Merrifield, Christopher Lintott, KL Masters, BD Simmons, A Fraser-Mckelvie, T Peterken, M Boquien, RA Riffel, N Drory
Abstract:
Deriving a simple, analytic galaxy star formation history (SFH) using observational data is a complex task without the proper tool to hand. We therefore present SNITCH, an open source code written in PYTHON, developed to quickly (2 min) infer the parameters describing an analytic SFH model from the emission and absorption features of a galaxy spectrum dominated by star formation gas ionization. SNITCH uses the Flexible Stellar Population Synthesis models of Conroy, Gunn & White (2009), the MaNGA Data Analysis Pipeline and a Markov Chain Monte Carlo method in order to infer three parameters (time of quenching, rate of quenching, and model metallicity) which best describe an exponentially declining quenching history. This code was written for use on the MaNGA spectral data cubes but is customizable by a user so that it can be used for any scenario where a galaxy spectrum has been obtained, and adapted to infer a user defined analytic SFH model for specific science cases. Herein, we outline the rigorous testing applied to SNITCH and show that it is both accurate and precise at deriving the SFH of a galaxy spectra. The tests suggest that SNITCHis sensitive to the most recent epoch of star formation but can also trace the quenching of star formation even if the true decline does not occur at an exponential rate. With the use of both an analytical SFH and only five spectral features, we advocate that this code be used as a comparative tool across a large population of spectra, either for integral field unit data cubes or across a population of galaxy spectra.
Galaxy zoo: Probabilistic morphology through Bayesian CNNs and active learning
Monthly Notices of the Royal Astronomical Society Oxford University Press 491:2 (2019) 1554-1574
Authors:
Mike Walmsley, Lewis Smith, Chris Lintott, Yarin Gal, Steven Bamford, Hugh Dickinson, Lucy Fortson, Sandor Kruk, Karen Masters, Claudia Scarlata, Brooke Simmons, Rebecca Smethurst, Darryl Wright
Abstract:
We use Bayesian convolutional neural networks and a novel generative model of Galaxy Zoo volunteer responses to infer posteriors for the visual morphology of galaxies. Bayesian CNN can learn from galaxy images with uncertain labels and then, for previously unlabelled galaxies, predict the probability of each possible label. Our posteriors are well-calibrated (e.g. for predicting bars, we achieve coverage errors of 11.8 per cent within a vote fraction deviation of 0.2) and hence are reliable for practical use. Further, using our posteriors, we apply the active learning strategy BALD to request volunteer responses for the subset of galaxies which, if labelled, would be most informative for training our network. We show that training our Bayesian CNNs using active learning requires up to 35–60 per cent fewer labelled galaxies, depending on the morphological feature being classified. By combining human and machine intelligence, Galaxy zoo will be able to classify surveys of any conceivable scale on a time-scale of weeks, providing massive and detailed morphology catalogues to support research into galaxy evolution.
