The global influence of AGN-driven outflows remains uncertain, due to a lack of large samples with accurately-determined outflow properties. In the second paper of this series, we determine the mass and energetics of ionized outflows is 234 type II AGN, the largest such sample to date, by combining the infrared emission of the dust in the wind (paper I) with the emission line properties. We provide new general expressions for the properties of the outflowing gas, which depend on the ionization state of the gas. We also present a novel method to estimate the electron density in the outflow, based on optical line ratios and on the known location of the wind. The inferred electron densities, n e ∼ 10 4.5 cm −3 , are two orders of magnitude larger than typically found in most other cases of ionized outflows. We argue that the discrepancy is due to the fact that the commonly-used [SII]-based method underestimates the true density by a large factor. As a result, the inferred mass outflow rates and kinetic coupling efficiencies areṀ out ∼ 10 −2 (M /yr) and =Ė kin /L bol ∼ 10 −5 respectively, 1-2 orders of magnitude lower than previous estimates. Our analysis suggests the existence of a significant amount of neutral atomic gas at the back of the outflowing ionized gas clouds, with mass that is a factor of a few larger than the observed ionized gas mass. This has significant implications for the estimated mass and energetics of such flows.

How can we discover objects we did not know existed within the large datasets that now abound in astronomy? We present an outlier detection algorithm that we developed, based on an unsupervised Random Forest. We test the algorithm on more than two million galaxy spectra from the Sloan Digital Sky Survey and examine the 400 galaxies with the highest outlier score. We find objects which have extreme emission line ratios and abnormally strong absorption lines, objects with unusual continua, including extremely reddened galaxies. We find galaxy-galaxy gravitational lenses, double-peaked emission line galaxies, and close galaxy pairs. We find galaxies with high ionisation lines, galaxies which host supernovae, and galaxies with unusual gas kinematics. Only a fraction of the outliers we find were reported by previous studies that used specific and tailored algorithms to find a single class of unusual objects. Our algorithm is general and detects all of these classes, and many more, regardless of what makes them peculiar. It can be executed on imaging, time-series, and other spectroscopic data, operates well with thousands of features, is not sensitive to missing values, and is easily parallelisable.

We report on the determination of electron densities, and their impact on the outflow masses and rates, measured in the central few hundred parsecs of 11 local luminous active galaxies. We show that the peak of the integrated line emission in the AGN is significantly offset from the systemic velocity as traced by the stellar absorption features, indicating that the profiles are dominated by outflow. In contrast, matched inactive galaxies are characterised by a systemic peak and weaker outflow wing. We present three independent estimates of the electron density in these AGN, discussing the merits of the different methods. The electron density derived from the [SII] doublet is significantly lower than than that found with a method developed in the last decade using auroral and transauroral lines, as well as a recently introduced method based on the ionization parameter. The reason is that, for gas photoionized by an AGN, much of the [SII] emission arises in an extended partially ionized zone where the implicit assumption that the electron density traces the hydrogen density is invalid. We propose ways to deal with this situation and we derive the associated outflow rates for ionized gas, which are in the range 0.001–0.5 M⊙ yr−1 for our AGN sample. We compare these outflow rates to the relation between $\dot{M}_{\rm out}$ and LAGN in the literature, and argue that it may need to be modified and rescaled towards lower mass outflow rates.

The scaling relations between supermassive black holes and their host galaxy properties are of fundamental importance in the context black hole-host galaxy co-evolution throughout cosmic time. In this work, we use a novel algorithm that identifies smooth trends in complex datasets and apply it to a sample of 2 000 type I active galactic nuclei (AGN) spectra. We detect a sequence in emission line shapes and strengths which reveals a correlation between the narrow L([OIII])/L(Hβ) line ratio and the width of the broad Hα. This scaling relation ties the kinematics of the gas clouds in the broad line region to the ionisation state of the narrow line region, connecting the properties of gas clouds kiloparsecs away from the black hole to material gravitationally bound to it on sub-parsec scales. This relation can be used to estimate black hole masses from narrow emission lines only. It therefore enables black hole mass estimation for obscured type II AGN and allows us to explore the connection between black holes and host galaxy properties for thousands of objects, well beyond the local Universe. Using this technique, we present the M BH − σ and M BH − M * scaling relations for a sample of about 10 000 type II AGN from SDSS. These relations are remarkably consistent with those observed for type I AGN, suggesting that this new method may perform as reliably as the classical estimate used in non-obscured type I AGN. These findings open a new window for studies of black hole-host galaxy co-evolution throughout cosmic time.

Machine learning (ML) algorithms become increasingly important in the analysis of astronomical data. However, since most ML algorithms are not designed to take data uncertainties into account, ML based studies are mostly restricted to data with high signal-to-noise ratio. Astronomical datasets of such high-quality are uncommon. In this work we modify the long-established Random Forest (RF) algorithm to take into account uncertainties in the measurements (i.e., features) as well as in the assigned classes (i.e., labels). To do so, the Probabilistic Random Forest (PRF) algorithm treats the features and labels as probability distribution functions, rather than deterministic quantities. We perform a variety of experiments where we inject different types of noise to a dataset, and compare the accuracy of the PRF to that of RF. The PRF outperforms RF in all cases, with a moderate increase in running time. We find an improvement in classification accuracy of up to 10% in the case of noisy features, and up to 30% in the case of noisy labels. The PRF accuracy decreased by less then 5% for a dataset with as many as 45% misclassified objects, compared to a clean dataset. Apart from improving the prediction accuracy in noisy datasets, the PRF naturally copes with missing values in the data, and outperforms RF when applied to a dataset with different noise characteristics in the training and test sets, suggesting that it can be used for Transfer Learning.

The typical optical-UV continuum slopes observed in many type 1 active galactic nuclei (AGN) are redder than expected from thin accretion disk models. A possible resolution to this conundrum is that many AGN are reddened by dust along the line of sight. To explore this possibility, we stack 5000 SDSS AGN with luminosity L ≈ 10 45 erg s −1 and redshift z ∼ 0.4 in bins of optical continuum slope α opt and width of the broad Hβ emission line. We measure the equivalent width (EW) of the NaID absorption feature in each stacked spectrum. We find a linear relation between α opt and EW(NaID), such that EW(NaID) increases as α opt becomes redder. In the bin with the smallest Hβ width, objects with the bluest slopes that are similar to accretion disk predictions are found to have EW(NaID) = 0, supporting the line-of-sight dust hypothesis. This conclusion is also supported by the dependence of the Hα/Hβ line ratio on α opt . The implied relationship between continuum slope and dust reddening is given by E B−V ≈ 0.2 · (−0.1 − α opt ), and the implied reddening of a typical type 1 AGN with α opt = −0.5 is E B−V ≈ 0.08 mag. Photoionization calculations show that the lineof-sight dusty gas responsible for reddening is too ionized to produce the observed sodium features. Therefore, we argue that the sodium absorption arises in regions of the host ISM which are shielded from the AGN radiation, along lines-of-sight to the stars, and the correlation with α opt arises since ISM columns along shielded and non-shielded sightlines are correlated. This scenario is supported by the similarity of the relation between E B−V and NaI column implied by our results with the relation in the Milky-Way found by previous studies.

Active galactic nuclei (AGN) feedback operated by the expansion of radio jets can play a crucial role in driving gaseous outflows on galaxy scales. Galaxies hosting young radio AGN, whose jets are in the first phases of expansion through the surrounding interstellar medium (ISM), are the ideal targets to probe the energetic significance of this mechanism. In this paper, we characterise the warm ionised gas outflows in a sample of nine young radio sources from the 2 Jy sample, combining X-shooter spectroscopy and Hubble Space Telescope imaging data. We find that the warm outflows have similar radial extents (∼0.06−2 kpc) as radio sources, consistent with the idea that “jet mode” AGN feedback is the dominant driver of the outflows detected in young radio galaxies. Exploiting the broad spectral coverage of the X-shooter data, we used the ratios of trans-auroral emission lines of [S II] and [O II] to estimate the electron densities, finding that most of the outflows have gas densities (log(ne cm−3) ∼ 3 − 4.8), which we speculate could be the result of compression by jet-induced shocks. Combining our estimates of the emission-line luminosities, radii, and densities, we find that the kinetic powers of the warm outflows are a relatively small fraction of the energies available from the accretion of material onto the central supermassive black hole, reflecting AGN feedback efficiencies below 1% in most cases. Overall, the warm outflows detected in our sample are strikingly similar to those found in nearby ultraluminous infrared galaxies, but more energetic and with higher feedback efficiencies on average than the general population of nearby AGN of similar bolometric luminosity; this is likely to reflect a high degree of coupling between the jets and the near-nuclear ISM in the early stages of radio source evolution.

We report on our combined analysis of HST, VLT/MUSE, VLT/SINFONI, and ALMA observations of the local Seyfert 2 galaxy, NGC 5728 to investigate in detail the feeding and feedback of the AGN. The datasets simultaneously probe the morphology, excitation, and kinematics of the stars, ionized gas, and molecular gas over a large range of spatial scales (10 pc-10 kpc). NGC 5728 contains a large stellar bar which is driving gas along prominent dust lanes to the inner 1 kpc where the gas settles into a circumnuclear ring. The ring is strongly star forming and contains a substantial population of young stars as indicated by the lowered stellar velocity dispersion and gas excitation consistent with HII regions. We model the kinematics of the ring using the velocity field of the CO (2-1) emission and stars and find it is consistent with a rotating disk. The outer regions of the disk, where the dust lanes meet the ring, show signatures of inflow at a rate of 1 M yr −1 . Inside the ring, we observe three molecular gas components corresponding to the circular rotation of the outer ring, a warped disk, and the nuclear stellar bar. The AGN is driving an ionized gas outflow that reaches a radius of 250 pc with a mass outflow rate of 0.08 M yr −1 consistent with its luminosity and scaling relations from previous studies. While we observe distinct holes in CO emission which could be signs of molecular gas removal, we find that largely the AGN is not disrupting the structure of the circumnuclear region.