Examinando por Autor "Bauer, F. E."
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Ítem BAT AGN Spectroscopic Survey – XIX. Type 1 versus type 2 AGN dichotomy from the point of view of ionized outflows(Oxford University Press, 2019-11) Rojas, A.F; Sani, E.; Gavignaud, I.; Ricci, C.; Lamperti, I.; Koss, M.; Trakhtenbrot, B.; Schawinski, K.; K., Oh.; Bauer, F. E.; Bischetti, M.; Boissay-Malaquin, R.; Bongiorno, A.; Harrison, F.; Kakkad, A.D; Masetti, N.; Ricci, F.; Shimizu, T.; Stalevski, M.; Stern, D.; Vietri, G.We present a detailed study of ionized outflows in a large sample of ∼650 hard X-raydetected active galactic neuclei (AGNs). Using optical spectroscopy from the BAT AGN Spectroscopic Survey (BASS), we are able to reveal the faint wings of the [OIII] emission lines associated with outflows covering, for the first time, an unexplored range of low AGN bolometric luminosity at low redshift (z ∼0.05).We test if and how the incidence and velocity of ionized outflow is related to AGN physical parameters: black hole mass (MBH), gas column density (NH), Eddington ratio (λEdd), [O III], X-ray, and bolometric luminosities. We find a higher occurrence of ionized outflows in type 1.9 (55 per cent) and type 1 AGNs (46 per cent) with respect to type 2 AGNs (24 per cent). While outflows in type 2 AGNs are evenly balanced between blue and red velocity offsets with respect to the [OIII] narrow component, they are almost exclusively blueshifted in type 1 and type 1.9 AGNs. We observe a significant dependence between the outflow occurrence and accretion rate, which becomes relevant at high Eddington ratios [log(λEdd) −1.7]. We interpret such behaviour in the framework of covering factor-Eddington ratio dependence. We do not find strong trends of the outflow maximum velocity with AGN physical parameters, as an increase with bolometric luminosity can be only identified when including samples of AGNs at high luminosity and high redshift taken from literature.Ítem Persistent and occasional: Searching for the variable population of the ZTF/4MOST sky using ZTF Data Release 11(EDP Sciences, 2023-07-01) Sánchez-Sáez, P.; Arredondo, J.; Bayo, A.; Arévalo, P.; Bauer, F. E.; Cabrera-Vives, G.; Catelan, M.; Coppi, P.; Estévez, P. A.; Förster, F.; Hernández-García, L.; Huijse, P.; Kurtev, R.; Lira, P.; Muñoz Arancibia, A. M.; Pignata, G.We present a variability-, color-, and morphology-based classifier designed to identify multiple classes of transients and persistently variable and non-variable sources from the Zwicky Transient Facility (ZTF) Data Release 11 (DR11) light curves of extended and point sources. The main motivation to develop this model was to identify active galactic nuclei (AGN) at different redshift ranges to be observed by the 4MOST Chilean AGN/Galaxy Evolution Survey (ChANGES). That being said, it also serves as a more general time-domain astronomy study. Methods. The model uses nine colors computed from CatWISE and Pan-STARRS1 (PS1), a morphology score from PS1, and 61 single-band variability features computed from the ZTF DR11 g and r light curves. We trained two versions of the model, one for each ZTF band, since ZTF DR11 treats the light curves observed in a particular combination of field, filter, and charge-coupled device (CCD) quadrant independently. We used a hierarchical local classifier per parent node approach, where each node is composed of a balanced random forest model. We adopted a taxonomy with 17 classes: non-variable stars, non-variable galaxies, three transients (SNIa, SN-other, and CV/Nova), five classes of stochastic variables (lowz-AGN, midz-AGN, highz-AGN, Blazar, and YSO), and seven classes of periodic variables (LPV, EA, EB/EW, DSCT, RRL, CEP, and Periodic-other). Results. The macro-averaged precision, recall, and F1-score are 0.61, 0.75, and 0.62 for the g-band model, and 0.60, 0.74, and 0.61, for the r-band model. When grouping the four AGN classes (lowz-AGN, midz-AGN, highz-AGN, and Blazar) into one single class, its precision, recall, and F1-score are 1.00, 0.95, and 0.97, respectively, for both the g and r bands. This demonstrates the good performance of the model in classifying AGN candidates. We applied the model to all the sources in the ZTF/4MOST overlapping sky (-28 = Dec = 8.5), avoiding ZTF fields that cover the Galactic bulge (|gal_b| = 9 and gal_l = 50). This area includes 86 576 577 light curves in the g band and 140 409 824 in the r band with 20 or more observations and with an average magnitude in the corresponding band lower than 20.5. Only 0.73% of the g-band light curves and 2.62% of the r-band light curves were classified as stochastic, periodic, or transient with high probability (Pinit = 0.9). Even though the metrics obtained for the two models are similar, we find that, in general, more reliable results are obtained when using the g-band model. With it, we identified 384 242 AGN candidates (including low-, mid-, and high-redshift AGN and Blazars), 287 156 of which have Pinit = 0.9. © 2023 EDP Sciences. All rights reserved.Ítem A random forest-based selection of optically variable AGN in the VST-COSMOS field(EDP Sciences, 2021-01-01) De Cicco, D.; Bauer, F. E.; Paolillo, M.; Cavuoti, S.; Sánchez-Sáez, P.; Brandt, W. N.; Pignata, G.; Vaccari, M.; Radovich, M.Context. The survey of the COSMOS field by the VLT Survey Telescope is an appealing testing ground for variability studies of active galactic nuclei (AGN). With 54 r-band visits over 3.3 yr and a single-visit depth of 24.6 r-band mag, the dataset is also particularly interesting in the context of performance forecasting for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). Aims. This work is the fifth in a series dedicated to the development of an automated, robust, and efficient methodology to identify optically variable AGN, aimed at deploying it on future LSST data. Methods. We test the performance of a random forest (RF) algorithm in selecting optically variable AGN candidates, investigating how the use of different AGN labeled sets (LSs) and features sets affects this performance. We define a heterogeneous AGN LS and choose a set of variability features and optical and near-infrared colors based on what can be extracted from LSST data. Results. We find that an AGN LS that includes only Type I sources allows for the selection of a highly pure (91%) sample of AGN candidates, obtaining a completeness with respect to spectroscopically confirmed AGN of 69% (vs. 59% in our previous work). The addition of colors to variability features mildly improves the performance of the RF classifier, while colors alone prove less effective than variability in selecting AGN as they return contaminated samples of candidates and fail to identify most host-dominated AGN. We observe that a bright (r ≲ 21 mag) AGN LS is able to retrieve candidate samples not affected by the magnitude cut, which is of great importance as faint AGN LSs for LSST-related studies will be hard to find and likely imbalanced. We estimate a sky density of 6.2 × 106 AGN for the LSST main survey down to our current magnitude limit.