Discovery of a Remarkably Powerful Broad Absorption Line Quasar Outflow in SDSS J135246.37+423923.5
Hyunseop Choi, Karen M. Leighly, Donald M. Terndrup, Sarah C. Gallagher, Gordon T. Richards
DDraft version January 22, 2020
Typeset using L A TEX preprint style in AASTeX62
Discovery of a Remarkably Powerful Broad Absorption Line Quasar Outflow inSDSS J135246.37+423923.5
Hyunseop Choi, Karen M. Leighly, Donald M. Terndrup,
1, 2
Sarah C. Gallagher,
3, 4, 5, 6 and Gordon T. Richards Homer L. Dodge Department of Physics and Astronomy, The University of Oklahoma, 440 W. Brooks St., Norman,OK 73019 Department of Astronomy, The Ohio State University, 140 W. 18th Ave., Columbus, OH 43210 Department of Physics & Astronomy, The University of Western Ontario, London, ON, N6A 3K7, Canada Canadian Space Agency, 6767 Route de l’Aeroport, Saint-Hubert, Quebec, J3Y BY9 Institute for Earth and Space Exploration, The University of Western Ontario, London, ON, N6A 3K7, Canada The Rotman Institute of Philosophy, The University of Western Ontario, London, ON, N6A 3K7, Canada Department of Physics, Drexel University, 32 S. 32nd St., Philadelphia, PA 19104
ABSTRACTBroad absorption line (BAL) features in quasar spectra reveal an unambiguous signa-ture of energetic outflows from central supermassive black holes, and thus BAL quasarsare prime targets for investigating the potential process of luminous quasar feedbackon galaxies. We analyzed the rest-UV spectrum of an “overlapping trough” iron low-ionization broad absorption line quasar (FeLoBAL) SDSS J135246.37+423923.5 usingthe novel spectral synthesis code
SimBAL (Leighly et al. 2018) and discovered an ex-traordinarily fast and energetic BAL outflow. Our analysis revealed outflow velocitiesreaching ∼ − − with a velocity width of ∼ − which is the largestFeLoBAL outflow velocity measured to date. The column density of the outflow gasis log N H ∼ . − ] with the log kinetic luminosity log L KE ∼ . − ] whichexceeds the bolometric luminosity of the quasar and is energetic enough to effectivelydrive quasar feedback. The energy estimate for the outflow is far greater than theestimates from any BAL object previously reported.The object also shows “anomalous reddening” and a significant scattered componentthat we were able to model with SimBAL . We found the first definitive case for radiationfiltering in an additional zero-velocity absorption component that required an absorbedcontinuum to produce the particular absorption lines observed (Mg II , Al III and Al II )without also producing the high ionization lines such as C IV . INTRODUCTIONBroad absorption line (BAL) quasars (BALQs) have been studied extensively in the pastseveral decades since their discovery (Lynds 1967), and their distinctive blueshifted BAL featuresprovide clear evidence for quasar outflows (e.g., Weymann et al. 1991). Once corrected for selectioneffects, BALQs are found in 20% ∼
40% of the total quasar population (Foltz et al. 1990; Weymannet al. 1991; Tolea et al. 2002; Reichard et al. 2003; Trump et al. 2006; Dai et al. 2008; Knigge et al.2008; Allen et al. 2011). BALQs are further divided into subgroups based on their spectroscopicproperties. High-ionization BALQs (HiBALs) show only the absorption transitions from highly a r X i v : . [ a s t r o - ph . GA ] J a n Choi et al. ionized atoms (C IV , Si IV , N V , O VI ), while low-ionization (LoBALQs) show both the high-ionization transitions and absorption lines from lower-ionization ions (Mg II , Al II , Al III ) in theirrest-UV spectra. There is also another class of rarer BALQs called FeLoBALQs that show Fe II absorption lines. These objects have large gas column densities, thick enough to extend beyond thehydrogen ionization front (Hazard et al. 1987). Although FeLoBALs comprise less than ∼
2% of theobserved quasar population (Dai et al. 2012), their outflows can have the highest column densitiescompared to other types of BAL outflows (Lucy et al. 2014). Some FeLoBAL objects with broadsaturated troughs, where the troughs overlap to nearly completely absorb the continuum emissionshortward of 2800 ˚A, are called ‘overlapping trough’ objects (e.g., Hall et al. 2002), and they areexpected to have the largest hydrogen column densities (log N H ) in their outflows.Outflowing winds with energy exceeding 0.5% ∼
5% of the quasar luminosity (e.g., Scannapieco& Oh 2004; Di Matteo et al. 2005; Hopkins & Elvis 2010) are thought to be able to effectively causeAGN feedback. Outflow energies depend on the amount of material (log N H ) that is being carriedby the wind, and more importantly, the velocity of the outflow through ˙ E k = 8 πµm p Ω RN H v (Dunnet al. 2010). The combination of large column density (log N H ) and high velocity produce energeticoutflows.A few discoveries of high-velocity HiBAL outflows ( v ∼ v ∼ IV BAL feature at v ∼ v ∼ IV absorptionlines (and Si IV or N V lines in some cases) and lacked diagnostic lines to probe the density of theoutflow. Moreover, HiBALQs are not expected to have the highest log N H .LoBALQs and FeLoBALQs have significantly higher column densities, and therefore, high-velocity outflows in these objects may yield produce the most energetic outflows. Borguet et al. (2013)and Chamberlain et al. (2015) analyzed the rest-UV spectra of LoBALQs SDSS J1106+1939 andSDSS J0831+0354, respectively. They found high-velocity LoBAL outflows with high energies andconstrained their physical properties ( ∼ − − and ∼ − − , respectively; see § N H ) and massive outflows, potentiallyharboring energetic outflows, only a few FeLoBAL objects have been analyzed to determine thephysical properties of their outflows (de Kool et al. 2001, 2002a,b; Dunn et al. 2010; Bautista et al.2010; Lucy et al. 2014). Because the common method (e.g., Arav et al. 2013) used to analyze BALtroughs involves individual line identification, it becomes extremely challenging to extract physicalproperties of an outflow that has a large number of Fe II absorption features that are blended together. SimBAL was first introduced by Leighly et al. (2018) as a novel spectral synthesis code devel-oped to analyze BAL outflows. Because
SimBAL uses forward modeling with spectral synthesis, thecode can be used to analyze even the most complex BAL spectroscopic features with significant lineblending. The code has produced an excellent fit to SDSS J0850+4451 (Leighly et al. 2018), a LoBALobject; moreover its sophisticated treatment of modeling the partial coverage of BAL absorbers ledto further understanding of the geometry and the structure of the outflow (Leighly et al. 2019).For thick BAL outflows, part of the radiation can be significantly absorbed by gas closer to thecentral engine before reaching the gas further away producing a phenomenon called “radiation filtering owerful BAL outflow in SDSS J1352+4239
SimBAL models andfound no evidence supporting the phenomenon in SDSS J0850+4451. Miller et al. (2018) suggesteda potential two-phase photoionization condition arising from radiation filtering in LBQS 1206+1052.Despite the effort to understand the radiation filtering, no definitive observational evidence has beenfound. Not only do BALQs show interesting outflow signatures, they also are known to show strongerreddening and a higher scattering fraction (e.g., Sprayberry & Foltz 1992; Brotherton et al. 1997;DiPompeo et al. 2011; Krawczyk et al. 2015). Some extragalactic objects are known to show “anoma-lous reddening”, where their reddening curves do not resemble any of the commonly used reddeningcurves derived from the Milky Way galaxy (e.g., Cardelli et al. 1989) or the Magellanic Clouds (e.g.,Prevot et al. 1984), possibly due to a particular dust composition near the quasar (Hall et al. 2002;Leighly et al. 2009; Jiang et al. 2013; Fynbo et al. 2013; Zhang et al. 2015; Krogager et al. 2015;Meusinger et al. 2016). The nature of the strong reddening observed in BALQs may offer cluesto the physical conditions and geometry of the outflows in these objects. Moreover, the dust hassignificantly larger scattering cross-section than the ions and can provide significant acceleration tothe outflows (e.g., Fabian et al. 2008, 2018). Dusty outflows are able to harness the radiation pres-sure more efficiently and could potentially explain the acceleration mechanism of some of the BALoutflows with the highest velocities.In this paper, we report the discovery of the most energetic BAL outflow analyzed to date.SDSS J135246.37+423923.5, hereafter referred to as SDSS 1352+4239, is an overlapping trough objectthat was initially observed by the Sloan Digital Sky Survey (SDSS). This object has all the fascinatingBAL characteristics in its spectrum, including a wide overlapping trough, anomalous reddening anda substantial scattered light signature. With new near-infrared observations of SDSS 1352+4239, wemeasured an accurate redshift, z=2.26, from the Balmer emission lines. From the correct redshiftwe were able to identify the fastest FeLoBAL outflow ever observed ( v ∼ − − ). Weperformed detailed analysis with SimBAL to determine the physical conditions of the outflowingcloud and constrain the energetics of the outflow. We were able to not only characterize the mainBAL outflow but we also found evidence for radiation shielding in the zero-velocity BAL system. In §
2, we briefly reintroduce
SimBAL and the changes that have been made since its debut in Leighlyet al. (2018). In §
3, we describe the new observation and data reduction done for SDSS 1352+4239.We introduce a general reddening curve used to model the unusual continuum shape in § SimBAL to analyze SDSS 1352+4239 in §
5. We report theenergetics derived from the
SimBAL fit of the outflow in § § § SIMBAL
Constraining the physical conditions of the outflowing clouds can be very challenging due toline blending and the non-black saturation of absorption lines from partial coverage of the emissionsources. The standard method for analyzing BALQ spectra relies on the apparent optical depth(AOD) analysis (e.g., Arav et al. 2013). This method requires line identification and optical depthmeasurement of each absorption line. The optical depths are converted to ionic column densities and
Choi et al. compared to the output from 1D photoionizations simulations using
Cloudy (Ferland et al. 2017) tofind the physical conditions of the gas along the line of sight. Because the AOD analysis can onlyprovide lower limits for the column density estimates for the identified absorption lines and fails toprovide accurate line ratios due to non-black saturation, accurate measurements of the density andthe location of the gas with respect to the ionizing continuum source is difficult.An alternative approach to studying BALQ spectra with the novel spectral synthesis code
SimBAL was introduced by Leighly et al. (2018).
SimBAL uses grids of ionic column densitiescalculated using the photoionization code
Cloudy (Ferland et al. 2017) and a Bayesian model calibra-tion method to model BALQ spectra. Because
SimBAL employs a forward modeling technique anda sophisticated mathematical implementation of partial covering to model the absorption features(Leighly et al. 2019), it can accurately reproduce the complex absorption features in BALQSOs andconstrain the physical properties of the outflow as a function of velocity. With a given set of pa-rameters,
SimBAL combines ionic column density information from the
Cloudy grids, line transitionstrengths from atomic data and the parameterized kinematics of the outflow to create a syntheticspectrum. Additionally, the Bayesian model calibration method used in
SimBAL yields error esti-mates for the physical parameters that describe the gas in the outflow. A detailed discussion on how
SimBAL operates and a flowchart describing the relationship of the components can be found in § U , densitylog n [cm − ], thickness of the gas relative to the hydrogen ionization front log N H − log U [cm − ], out-flow velocity v (km s − ), velocity width σ (km s − ), and a covering fraction parameter log a (discussedfurther below). The first three parameters define the physical conditions of the outflowing gas interms of the photoionization state and the last three parameters define the kinematics of the gas aswell as the state of non-black saturation by modeling the partial coverage using the covering fractionparameter. SimBAL can model a broad absorption feature with either one or multiple Gaussianopacity profiles or the “tophat accordion” model where a broad velocity profile is divided up intomultiple velocity-adjacent “tophat” bins (Leighly et al. 2018). The number of bins is fixed for a givenmodel. Each bin can have its own set of physical parameters (i.e., ionization parameter, density andlog N H log U ) and a covering-fraction parameter. Alternatively, parameters can be tied togetherfor several velocity bins. As discussed in detail in Leighly et al. (2019), the inhomogeneous partialcovering model in SimBAL uses a powerlaw distribution of opacity τ where τ = τ max x a (Sabra &Hamann 2005; Arav et al. 2005). SimBAL uses log a to control the partial coverage and x ∈ (0 , a close to 0, and low covering can be modeled with high values of a . Further discussion ofinhomogeneous partial covering is given in Leighly et al. (2019).The version of SimBAL used in Leighly et al. (2018, 2019) used the 2013 version of
Cloudy .After that analysis was initiated, version C17 of
Cloudy (Ferland et al. 2017) was released, whichallowed more complete and accurate photoionization calculations with a significantly larger atomicdatabase. Compared to Leighly et al. (2018), the ionic column density grids that have been calculatedwith version C17 of
Cloudy include the column densities of Fe II ions with a greater number of excitedstate levels and multiple iron-peak element ions including Co and Zn at multiple ionization states. SimBAL previously used a line list with 6267 transitions (78 ions; 179 counting the number of excitedenergy states); the updated line list includes 76488 transitions (281 ions; 997 counting the number owerful BAL outflow in SDSS J1352+4239
SimBAL involves the gridsampling. The photoionization state of the gas changes dramatically near the hydrogen ionizationfront. A simple even sampling by a modest amount across the column density or the log N H − log U parameter is insufficient to characterize the rapid change of ionic column densities across the hydrogenionization front. For example, the ionic column densities of some species that are mostly found inthe partially ionized zone such as Fe II increase by more than 4 dex as the hydrogen ionization frontis traversed (e.g., Lucy et al. 2014, their Fig. 10). A finer sampling is needed to properly capture thesteep increase in ionic column density around the hydrogen ionization front. However, the remainderof the hydrogen column density range does not need a finer sampling and a grid with much finersampling requires a tremendous amount of calculation time as well as a large file size. Therefore weapproach this problem by adopting a flexible indexing scheme where we identify the location of thehydrogen ionization front and apply the oversampling only around the region where the ionic columndensities change very rapidly. In addition, the changes in physical condition before and after thehydrogen ionization front becomes more dramatic with higher ionization parameter. We took intoaccount this change in the “sharpness” of the hydrogen ionization front when calculating the indexingscheme by increasing the grid density of the oversampled regions for higher ionization parameters(total 619,721 grid points).A third change involves continuum modeling of the spectra. In Leighly et al. (2018),continuum-normalized spectra were used for analysis. The issue is that the depth of the absorp-tion feature can either be overestimated or underestimated depending on the continuum placement.The new version of SimBAL models both the synthetic continuum model and the absorption modelsimultaneously, producing a full synthetic spectrum to be compared with the data as well as theunabsorbed spectrum model. Thus
SimBAL can fit both the emission features and the absorptionfeatures of the spectrum simultaneously to produce a more robust solution. This methodology al-lows more accurate measurement of the outflows. Moreover, simultaneous absorption and emissioncontinuum modeling enables the fitting of heavily absorbed objects (e.g., overlapping trough objects)that have thick outflows and show very little residual continuum emission. In this paper, we usean emission line template developed from an HST observation of Mrk 493 ( § SimBAL (Choi et al. in preparation). OBSERVATIONS AND ANALYSISThe observations of SDSS 1352+4239 discussed in this paper are listed in Table 1.3.1.
Gemini GNIRS Observation
SDSS 1352+4239 was observed using GNIRS on the Gillett Gemini (North) Telescope usinga standard cross-dispersed mode (the SXD camera with the 31 . / mm grating) and a 0 . (cid:48)(cid:48)
45 slit. Eight200-second exposures were made on 7 February 2015 in an ABBA dither pattern. Four 1-secondexposures were made of the A0 star HIP 61471 at a similar airmass for telluric correction. Thedata were reduced using the IRAF
Gemini package, coupled with the GNIRS XD reduction scripts,in the standard manner for near-infrared spectra, through the spectral extraction step. For telluriccorrection, the
Gemini spectra of the source and the telluric standard star were converted to a format Choi et al.
Table 1.
Observations of SDSS J1352+4239Observatory and Instrument Date Exposure (s) Observed Frame Band Pass (˚A) ResolutionSDSS 2003 June 24 6300.0 3810–9189 100 km s − Gemini (GNIRS) 2015 February 7 1600.0 8263–25208 240 km s − BOSS 2016 April 5 8100.0 3628–10387 89 km s − APO (Triplespec) 2018 February 25 5280.0 9097–24704 80 km s − that resembled IRTF SpeX data sufficiently that the Spextool xtellcor package (Cushing et al. 2004;Vacca et al. 2003) could be used. 3.2. APO Triplespec Observation
SDSS J1352+4239 was observed using Triplespec (Wilson et al. 2004) on the Apache PointObservatory Astrophysical Research Consortium 3.5-meter telescope on 25 February 2018 underphotometric conditions. The 240-second observations were made in a standard ABBA dither patternand split into two segments of 10 and 12 exposures. Twenty 20-second exposures of the A0 star HIP61471 were made before the first segment, and twelve 20-second exposures of the A0 star HIP 71172were made after the second segment. The 1 . (cid:48)(cid:48) − near 1.5 microns.The spectra were extracted in a standard manner using TripleSpecTool, a modification ofSpexTool (Cushing et al. 2004; Vacca et al. 2003). TripleSpecTool uses the airglow emission linesfor wavelength calibration. To account for a very small amount of flexure, wavelength calibrationsolutions were computed for each AB dither pair sequence of exposures. The telluric correction wasperformed using the adjacent observation of the A0 star (Vacca et al. 2003).The spectra were combined with the Gemini spectrum using a flux-weighted average, wherethe variance was based on the deviations of the spectrum around a best-fitting linear model to 21-pixelbins, after first down-sampling the APO spectra to the Gemini resolution. The combined spectrumis shown on the right panel in Fig. 1.3.3. The SDSS and BOSS Observations and Merging the Spectra
SDSS J1352+4239 was observed by SDSS and by the Baryon Oscillation Spectroscopic Survey(BOSS) program. We did not find any measurable flux offset or any strong evidence for spectralvariability in the two spectra. We chose to use the BOSS optical data from the SDSS archivebecause the data were taken closer to our near-infrared observations and the spectrum provideslarger wavelength range coverage than the SDSS spectrum. The BOSS and combined near-infraredGemini and APO spectra are shown in Figure 1. We used the flux density of BOSS spectrum andthe wavelength range between rest frame ∼ ∼ The Redshift owerful BAL outflow in SDSS J1352+4239 Figure 1.
The BOSS spectrum on the left shows an “overlapping trough” feature from the Fe II absorptionlines. The main iron trough and Mg II absorption features are marked on the left panel. BOSS spectrumshowed no strong emission features that could be used to estimate the redshift. Therefore we used H α in thecombined GNIRS+APO spectrum (right) to measure the redshift for SDSS J1352+4239. The flux level forthe Gemini and APO combined spectrum has been corrected to match BOSS flux density. The grey linesbelow the spectra show the uncertainties associated with the data. SDSS 1352+4239 was first cataloged in the SDSS Third Data Release catalog (Schneideret al. 2005), where the redshift was listed as 2.0385. Other published redshifts range from 2.000(Meusinger et al. 2012) to 2.049184 (Hewett & Wild 2010). The difficulty in estimating the redshiftoccurs because there are no strong emission lines in the SDSS spectrum. A broad bump just longwardof the Mg II absorption was identified as Mg II emission by Trump et al. (2006, their Fig. 10). Onthe other hand, the redshift of the absorption features is fairly obvious ( z = 1 . II and Fe II absorption lines (e.g., Lucy et al. 2014, Fig. 12).The redshift of SDSS 1352+4239 can be measured unambiguously from the infrared spectrum.We use H α because there are no prominent [O III ] lines and H β is blended with Fe II emission. Theline appears slightly asymmetric due to Fe II emission so we fit it with two Lorentzian profiles. Thepeak of the narrower one yields a redshift of 2 . ± . ∼
11% larger than any of the previousestimated values, implying that the outflow has a much larger velocity than previously suspected.3.5.
The Black Hole Mass
We estimated the black hole mass using the H β emission line. Strong Fe II emission is apparentthroughout the rest-frame optical spectrum, and especially around H β . We constrain the shape ofH β by simultaneously fitting Lorenzian profiles to each of H α , H β , and H γ , and constraining theirwidths to be the same and their relative central wavelengths based on known wavelengths of theselines. We used Sherpa for spectral fitting (Freeman et al. 2001). The strong Fe II emission wasmodeled using the catalog of Fe II emission lines obtained from I Zw 1 (V´eron-Cetty et al. 2004). http://github.com/sherpa/sherpa/, http://cxc.harvard.edu/sherpa/ Choi et al. F λ ( − e r g s − c m − A − ) Rest Wavelength (Angstroms)
Balmer Lines[OIII]FeII Template F λ ( − e r g s − c m − A − ) Rest Wavelength (Angstroms)
Figure 2.
The model fits to the combined Gemini and APO spectrum. The left panel shows the bandpassthat includes H β , and the right panel shows the bandpass that includes H α . The strong Fe II emissionobscures the H β line, so the two regions of the spectrum were fitted simultaneously, requiring that theFWHM of the Balmer lines to be equal. No obvious [O
III ] lines are visible in the spectrum, but they are included with a fixed width of1500 km s − and variable position and flux, with the 4960˚A component constrained to have the samewidth and fixed relative flux with respect to the 5008˚A component. The best-fitting model is shownin Fig. 2.To determine the radius of the broad line region, we refer to Bentz et al. (2013), who findthat log( R BLR ) = K + α log[ λL λ (5100) / erg s − ]. The continuum flux density at 5100˚A wasestimated from the combined Gemini and APO spectrum to be F = 48 . × − ergs s − cm − ˚A − .With the cosmological parameters used by Bentz et al. (2013) ( H = 72 km / s / Mpc, Ω M = 0 . Λ = 0 . D L = 18074 Mpc. Using K = 1 . +0 . − . and α = 0 . +0 . − . , we obtain an estimate of the radius of the H β emitting broad-line region of 1315 +480 − light days corresponding to 1 . +0 . − . parsec. For reference, we also calculated the location of theC IV emitting region using the equation given by Lira et al. (2018, Equation (1)). We estimatedthe continuum flux density at 1345˚A to be F = 343 . × − ergs s − cm − ˚A − after scaling thecomposite SED (Richards et al. 2006a) to match the near-infrared (rest-optical) photometry ( § IV emitting region of 199 +436 − light days or 0 . +0 . − . parsec.The model fit yields a FWHM of the Balmer lines of 4720 km s − for a Lorentzian profile.We estimate the black hole mass in the usual way. We refer to Collin et al. (2006), who provideline-shape-based correction factors based on the ratio of the FWHM to σ line , where σ line is the linedispersion. For a Lorentzian profile, F W HM/σ line ⇒
0, and therefore f = 1 .
5. We estimate thatthe black hole mass is 8 . × M (cid:12) . CONTINUUM MODELING AND SPECTRAL ENERGY DISTRIBUTION4.1.
The Long-Wavelength Spectrum
SDSS J1352+4239 shows a peculiar continuum shape compared to a typical quasar spectrum.We used the composite quasar SED from Richards et al. (2006a) and the composite spectrum fromFrancis et al. (1991) to analyze the shape of the underlying AGN continuum of the object using both owerful BAL outflow in SDSS J1352+4239 log Rest Frequency [Hz] l o g ν L ν [ e r g s − ] GeminiBOSSMean SED SDSS2MASSWISE1000 2000 4000 6000 8000 10000
Rest Wavelength [Å] F λ ( − e − g s − c ( − − ) D t Po2e− L 2 FitCo(posite Spect−0(E(issio) Li)eCo−−ected Photo(et−ySMC-ReddenedComposite SpectrumDataPower Law FitComposite SpectrumEmission LineCorrected PhotometrySMC-ReddenedComposite Spectrum
Figure 3.
SDSS J1352+4239 is plotted with the mean SED from Richards et al. (2006a) in the upper panel.The lower panel shows the power law continuum fit to long wavelengths ( λ > E ( B − V )=0.17, plotted in dotted blue in the lower panel, demonstratesthat the SMC reddening curve fails to reproduce the continuum shape of SDSS 1352+4239. While theobserved and composite continuum shapes are similar longward of ∼ ∼ § the spectrum and the photometry from SDSS, 2MASS and WISE (Fig. 3). In Figure 3, comparedwith the composite spectrum (Francis et al. 1991), the spectrum of SDSS J1352+4239 is similar to atypical unreddened quasar at wavelengths longward of ∼ emcee (Foreman-Mackey et al.2013) to fit the SMC (Prevot et al. 1984) reddened composite SED to the rest frame optical / near- http://dan.iel.fm/emcee/current/ Choi et al. infrared photometry points and found no evidence for reddening in the optical / near-infrared regionof the spectrum ( E ( B − V ) < − .
82 ( ± . − .
83, Krawczyk et al. 2015), and noreddening ( E ( B − V ) < µ m to 3788 ˚A. Thus the object has atypical value of spectral slope and no evidence for reddening in the long wavelength region, despitesignificant reddening at shorter wavelengths.To estimate the bolometric luminosity, we used the bolometric correction factor (BC) fromGallagher et al. (2007a) who provide bolometric corrections for monochromatic luminosity at twodifferent wavelengths. The strong reddening in the spectrum is only seen at wavelengths shortwardof ∼ § . ± . − ], with the uncertainties estimatedfrom the uncertainties associated with the bolometric correction factor (BC = 10 . ± . L Bol > erg s − ). The bolometric luminosity ofSDSS J1352+4239 is comparable to the objects in the WISSH quasar sample (Bischetti et al. 2017)where they focused on a sample of WISE/SDSS selected hyper-luminous quasars to study the powerand the effect of the AGN feedback. The mass accretion calculated from the bolometric luminosity,assuming the energy conversion efficiency ( η ) of 0.1, is 176 M (cid:12) per year. Compared with the blackhole mass of 8 . × M (cid:12) , SDSS J1352+4239 is radiating at about 93% of the Eddington limit.4.2. Anomalous Reddening
As can be seen from Figure 3, the shape of the continuum for SDSS J1352+4239 is quitepeculiar, but it is not unprecedented. Among other BAL objects with anomalous reddening, Mrk231 shows steep reddening in the near-UV to optical part of the continuum (e.g., Smith et al. 1995;Veilleux et al. 2013). Leighly et al. (2014) fit the continuum in Mrk 231 and concluded that a TypeIa supernovae reddening curve (Goobar 2008) best describes the reddening behavior of Mrk 231.Jiang et al. (2013) derived a reddening curve from IRAS 14026+4341 by comparing the object to aquasar composite spectrum and found that their reddening curve could be explained by a particulardistribution of dust grain sizes (one lacking large grains, a max = 70 nm). However, in the case ofWPVS 007 (Leighly et al. 2009), no particular grain distribution was able to model their anomalousreddening curve.We tried using the reddening templates developed with WPVS 007 (Leighly et al. 2009) andIRAS 14026+4341 (Jiang et al. 2013) as well as the reddening model used for Mrk 231 (Leighly et al.2014) to model the break in the continuum shape. However, none of the anomalous reddening modelswere able to appropriately model the continuum shape of SDSS J1352+4239 because their slopes andthe locations of sharp reddening increase did not match the continuum shape of SDSS J1352+4239.Therefore, we developed a general anomalous reddening curve. Using the general reddeningequation A( λ ) = 2 . { C ( λ ) /S ( λ ) } where S( λ ) is the reddened spectrum and C( λ ) is the intrinsicspectrum, our general reddening curve has the form of a power law. A ( λ ( µ m)) = p ( λ − λ Break ) , ( p >
0) if λ ≤ λ Break λ > λ
Break owerful BAL outflow in SDSS J1352+4239 λ −1 ((m −1 ) A λ / A Å SDSS J1352+4239Zafar et al. 2015Leighly et al. 2014Jiang et al. 2013Leighly et al. 2009SMC
Wavelength (Å)
Figure 4.
The reddening curve for SDSS J1352+4239 found from
SimBAL fits using our model ( p =0 . ± . , λ Break = 0 . ± .
001 ( µ m)) compared with other reddening curves developed for anomalousreddening. The reddening curves have been normalized to A λ at 2000 ˚A. Anomalous reddening curvesby Leighly et al. (2009) and Jiang et al. (2013) show different break wavelengths and slopes. The SMCreddening curve and an empirical reddening curve derived from a sample of reddened quasars by Zafar et al.(2015) is also plotted ( A V = 0.51) for comparison. Our anomalous reddening curve generates reddening from a specified wavelength ( λ Break ) to shorterwavelengths with A( λ ) gradually increasing from zero, and therefore there is no reddening at longwavelength region as required. The reddening equation requires two parameters: the slope of thecurve ( p ) and a reddening starting wavelength ( λ Break ). Figure 4 illustrates various reddening curves.Our general reddening model provides excellent fits for other anomalously reddened BALQ spectraas well (Choi et al. in preparation).To fit the shorter wavelength spectrum, we fixed the power law spectral slope to the value wefound from the optical / near-infrared photometry fit, and only varied the two anomalous reddeningparameters and the power law normalization to model the continuum with
SimBAL .4.3.
Modeling the Line Emission
Visual inspection of SDSS J1352+4239 revealed that the object potentially has a weaker Mg II emission and stronger iron emission compared with the typical AGN spectrum. It is not possibleto model the individual emission lines due to the heavy absorption features seen throughout thebandpass. Instead, we constructed a set of broadband emission templates to model the emission lines.It is well known that the ratio between the strengths of the prominent emission lines (e.g. Mg II ,C IV ) and the strength of the iron emission differs from object to object (e.g., Sulentic et al. 2000).Therefore, we created separate emission line templates for the iron emission and several other emissionline templates for other emission lines so that our model can create the iron emission independentlyfrom other emission lines. Mrk 493 is a narrow-line Seyfert with a strong Fe II emission, making2 Choi et al. it a suitable target for AGN emission-line analysis. It was observed by Hubble Space Telescope tocreate a high resolution and good signal-to-noise ratio Fe II template. From this Mrk 493 spectrum,we derived empirical emission templates for the iron emission (the Fe II pseudo-continuum) and forother emission lines (e.g. Ly α , Si IV , C IV , C III ], Mg II , Balmer lines) separately and used theextracted templates to model the emission features of SDSS J1352+4239.In order to separate the Fe II emission from the other emission lines in the Mrk 493 spectrum,we used Sherpa to model the spectrum using a power law, existing Fe II templates (V´eron-Cetty et al.(2004): 4000 ˚A (cid:46) λ rest (cid:46) (cid:46) λ rest (cid:46) (cid:46) λ rest (cid:46) II emission lines and power law continuum to obtain the Fe II emission templates.Separate emission templates for other major emission lines were made from the non-Fe II emissionline component of the same model. We merged the resulting Fe II emission templates together tocreate a single broadband emission template (1500 ˚A (cid:46) λ (cid:46) II emission line templates to allow SimBAL more flexibility in fitting the majoremission-line features so that each templates can be scaled to their own independent normalizationcoefficients. The final emission-line templates consist of a single full wavelength range template forFe II emission lines and 4 emission templates divided in wavelength sections mentioned above for thenon-Fe II AGN emission lines. BEST-FITTING MODELWe created a complex spectral model for SDSS J1352+4239 to extract the physical propertiesof the outflow. Our best-fitting model is made of 4 major components including two absorbingcomponents. The continuum and line emission were modeled by a power law and emission linetemplates described in § § § § § f model = Reddening × { ( f Continuum + f LineEmission ) × I High − V elocity × I Zero − V elocity + f Scattered F lux } where f ( λ ) is the flux from each component and the final model and I ( λ ) is the normalized flux( I/I ) from each absorption component. Figure 5 shows the best fit model of SDSS J1352+4239.Depending on the geometry and the angular size scale of the BAL outflowing cloud, the cover-ing fraction for the accretion disk and the line-emitting gas (broad line region, BLR) can be different.Leighly et al. (2019) demonstrated how SimBAL can be used to test the scenarios where the outflow-ing cloud has multiple covering fractions for different AGN components. We tested both two-coveringmodels where the covering-fraction parameters for the line emission and the continuum emission wereallowed to differ and single-covering models and concluded that there is no strong evidence for a dif- PI: Park, “A Definitive UV − Optical Template for Iron Emission in Active Galactic Nuclei”, program number14744 owerful BAL outflow in SDSS J1352+4239 F λ ( − e r g s − c m − Å − ) DataScattered Fl(xContin((mBest Model
Rest Wa)elength (Å) F λ ( − e r g s − c m − Å − ) Data-28700km s −1 -30600km s −1 -32500km s −1 -35200km s −1 -37800km s −1 Zero-Velocity BAL
Figure 5.
Upper panel: Our best fitting model described in §
5. Lower panel: Decomposition of ten tophatbins is shown in different colors (from yellow to navy); the zero-velocity BAL component is plotted in cyan.The velocities of five of the ten tophat bins for the main complex are labeled on the figure. Each bin in theabsorption complex creates an absorption feature at a different velocity. The combination of 10 bins createthe full trough and we harvest the information about the physical parameters of the outflow as a functionof velocity. ferent covering fraction for emission lines and continuum emission in SDSS J1352+4239. Thereforewe used a model with a single covering fraction for both emission components.The tophat accordion model provided an exceptional fit of the complex velocity structures ofthe trough in SDSS J1352+4239, and yielded the physical parameters of the outflows as a functionof velocity (Fig. 6). We fit the high-velocity troughs with a 10-bin tophat model with an additional7-bin tophat model for the zero-velocity absorption feature we identify near the Mg II emission lines( § ∼ − − to ∼ − − with the total velocity width of ∼ − (Fig. 5).The physical parameters and the derived outflow properties for the high velocity trough andzero-velocity component ( § Choi et al.
Table 2.
Physical Parameters and Derived Outflow Properties from the Best-Fitting
SimBAL
Model
Outflow Properties Higher Velocity Group Lower Velocity Group High-Velocity Total a Zero-Velocity ComponentPhysical Parameters v outflow (km s − ) b − − − − − − − U . +0 . − . − . +0 . − . - − . . b log n [cm − ] 6 . +0 . − . +0 . − . - < . e log N H − log U [cm − ] b a bc − .
58 to 1.92Derived Outflow Propertieslog N H [cm − ], per bin bc N H [cm − ], total d . +0 . − . . +0 . − . . ± .
05 21 . +0 . − . log R [pc] 0.97 +0 . − . ± .
02 0.93–1.02 > . e log ˙ M [M (cid:12) yr − ] f . +0 . − . . +0 . − . . ± .
04 -log ˙ P [dyne] f . +0 . − . . +0 . − . . ± .
04 -log L KE [erg s − ] f . +0 . − . . +0 . − . . ± .
04 - a The values are the combined result of the left two columns. b The range of values estimated from the multiple bins is reported. c Large value of log a corresponds to small covering fraction d Covering fraction weighted values are reported ( § e Zero-velocity component is located at a larger distance than the main high velocity component ( § f The global covering fraction Ω = 0 . § trough in SDSS J1352+4239 was modeled with a 10-bin tophat accordion model where the binswere divided into two groups with a single ionization parameter and density for all bins in eachgroup as described in § U , log n [cm − ], log N H − log U [cm − ] and log a were directly taken from the the physical fit parameters of the best-fitting model. The hydrogencolumn density values that have been corrected for the partial coverage with log a and the outflowproperties (e.g., log ˙ M , log L KE ) have been calculated from the aforementioned fit parameters.For log N H − log U [cm − ], log a and log N H [cm − ], the ranges reflect the values we found for theindividual bins. Total log N H for the groups are also reported. Uncertainties for each parameter werecalculated from the posterior probability distributions of the MCMC chain. We did not attempt tomodel the posterior distribution (e.g., Gaussian distribution), instead we calculated the median, 1 σ ,2 σ and 3 σ values directly from the posteriors. The uncertainties reported in the Table 2 represents95% confidence regions. A global covering fraction (Ω) of 0.2 was used for the calculations and furtherdiscussion of this parameter can be found in § The High-Velocity Component
The 10 bins for the main high-velocity trough were grouped into two sets with each grouphaving a single density and ionization parameter. Our initial investigation with
SimBAL modelsrevealed that the bins at higher velocities and at lower velocities have clear differences in their physicalparameters, primarily in thier densities. Subsequently, we found that the two density groups also had owerful BAL outflow in SDSS J1352+4239 −0.50.00.5 l o g U l o g n [ c m − ] l o g N H − l o g U [ c m − ] l o g a −38000 −36000 −34000 −32000 −30000 −28000 Velocity Off et (km −1 ) l o g N H [ c m − ] log N H tot = 23.22±0.05 [cm −2 ] Figure 6.
Physical parameters as a function of velocity with error bars representing 95% confidence regions.The parameters plotted in the top 4 panels were directly fitted with
SimBAL and in the bottom panel, thehydrogen column density values (log N H ), corrected for the covering fraction from each bin, were calculatedfrom log U , log N H − log U and log a . The total log N H value for the outflow, calculated from adding thehydrogen column density values from all 10 bins is also reported in the bottom panel. The two groups( − ∼ − − and − ∼ − − ) are constrained to each have the same densityand ionization parameter (top two panels), while the log N H log U parameter and the covering fractionparameter (lower log a values indicate higher covering fraction) were allowed to vary independently for eachbin. The highest covering fraction (lowest log a value) occurs around ∼ − − and the columndensity parameter log N H log U also peaks around the same velocity. This shows that most of theopacity is generated near this velocity (see also Fig. 7). different characteristic ionization parameters. Therefore, we assigned a single ionization parameterand density to each group.Fe II has a plethora of excited state levels, ranging from low level excited states (0-0.12 eV)as well as high levels ( > II lines very densitysensitive (e.g., Lucy et al. 2014). Fe II ions are populated deep in the photoionized cloud away from6 Choi et al. the incoming radiation because the ionization potentials to create Fe II ions is relatively low (7.9eV). Therefore Fe II ions require a large column density to be significant (column density reachingbeyond hydrogen ionization front), otherwise most of the iron atoms will be in a higher ionizationstate than Fe II . Thus the presence of the excited state Fe II lines along with other low ionizationlines (e.g., Mg II ) helps SimBAL to constrain both the density and the thickness of the outflowinggas. We see in Figure 5 not only how all 10 bins model the trough together in combination but alsohow each tophat bin creates a large number of absorption lines. Together the physical parameters ateach velocity can be constrained.Figure 6 shows the outflow physical parameters as a function of velocity. We found thehigh velocity part of the outflow has lower density (log n ∼ .
12 [cm − ]) and higher ionization(log U ∼ .
82) than the lower velocity group (log n ∼ .
43 [cm − ], log U ∼ − . N H log U ) of ∼ − ] reflects the significant opacity fromFe II ions that we see in the data. The covering fraction parameter (log a ) changes strongly withthe velocity and the bottom panel in Figure 7 shows how the shape of the opacity profile of theabsorber closely follows the shape of log a . Moreover, the large covering fraction (low log a ) and highlog N H log U parameter found near ∼ − − indicates that a large amount of opacityis concentrated around that velocity region in the outflow. Similarly, Leighly et al. (2018) alsofound a “concentration” region in their SimBAL model of SDSS J0850+4451, i.e., an enhancementin column density for a few of the bins in their 11-bin tophat model. By summing the hydrogencolumn density values weighted by the covering fraction from all 10 bins, each calculated fromthe log U parameter, log N H log U parameter, and covering-fraction parameter (log a ) per bin(log N H = (log N H log U ) + log U − log(1 + 10 log a ) Arav et al. 2005; Leighly et al. 2018, 2019), weestimated a covering fraction weighted total hydrogen column density of log N H = 23 . ± .
05 [cm − ](95% confidence errors, bottom panel in Figure 6).Figure 7 shows how the two tophat groups model the wide absorption feature. The highervelocity component contributes less opacity than the lower velocity component; however, the lowervelocity component alone cannot produce the wide trough we see in the data. The lower velocitycomponent has gaps between ∼ ∼ ∼ II andother iron peak ions in the high-excited states are expected to be the main source of the opacity. Theproblem is that the lower velocity component cannot produce enough opacity in those regions withoutcreating a deep absorption feature near ∼ The Scattered Light Component
SDSS J1352+4239 shows an extreme case of non-black saturation in the main trough where theemission at the bottom of the trough increases as a function of wavelength and contains a significant owerful BAL outflow in SDSS J1352+4239 Higher Veloc ty: −38000 to − 33000 (km s −1 )Lower Veloc (y: −33000 (o − 28000 (km s −1 )Zero-Velocity BAL F λ ( − e r g s − c m − Å − ) AlIIICIVS IV
H gher Veloc (yLower Veloc (y
Res( Wa)eleng(h (Å)
MgII
Figure 7.
The top panel shows the two models generated from combining only the higher and lower velocitybins in dark green and orange, respectively. The regions where the higher velocity group plays a significantrole in producing sufficient opacity to model the trough are marked with arrows in the top panel. Thebottom two panels show how some of the common BAL absorption lines (Si IV , C IV , Al III , Mg II ) havebeen modeled by the higher velocity group and the lower velocity group. The best-fitting model, continuumand the scattered flux component are plotted in same colors as Fig. 5. amount of flux. Non-black saturation of BAL features is very common and is thought to originatefrom the BAL outflow not entirely covering the continuum sources, which includes the accretion diskcontinuum and broad emission line features (e.g., Barlow & Sargent 1997). Continuum scatteringis not uncommon in BALQs, and it is known from spectropolarimetry that frequently the troughsare highly polarized indicating an origin in scattered light (e.g., Cohen et al. 1995; Ogle et al. 1999).The shape of the offset found under the trough in SDSS J1352+4239 suggests that this component isscattered light from the accretion disk continuum and line emission with the wavelength dependencecreated by the reddening. We modeled the scattered light component by multiplying the scatteringfraction parameter by the emission model consisted of the sum of the reddened power law continuumand line emission and added this component to the absorbed emission model: f Scattered F lux ( λ ) = ( f Continuum ( λ ) + f LineEmission ( λ )) × Scattering F raction.
The reddening of the scattered flux is assumed to be the same as the continuum reddening, and weassume that the scattered light is not absorbed by the wind. Our best model creates the underlyingemission feature with a scattering fraction of ∼ ± >
20% found in IRAS 13349+2438 by Lee et al. (2013). A large scat-tering fraction suggests that SDSS J1352+4239 may be highly polarized. Considering the amount8
Choi et al.
DataBest ModelScattered Fl x
Rest Wavelength (Å) F λ ( − e r g s − c m − Å − ) No Scattering
Figure 8.
The top panel shows the data and the best fit model that has the scattered flux component init. The bottom panel shows a model that does not have the scattered light component. The scattered lightcomponent is clearly necessary to create an appropriate trough shape. of polarization depends both on the geometry of the scattering source and the scattered fraction,SDSS J1352+4239 may exhibit polarization less than this value. Previous spectropolarimetry ob-servations of BALQSOs revealed polarization reaching greater than ∼
10% in some objects (e.g.,Brotherton et al. 1997; Ogle et al. 1999).To test the necessity of the scattered flux component, we fit the data with a model that doesnot include it. The model fails to match the shape around ∼ − II trough. Figure 8 shows the comparison between the best fitting model and the model without thescattered component. Further discussion of possible origins of the scattered light is given in § The Zero-Velocity Component
We found a single prominent absorption feature between 2800˚A and 2850˚A that was not mod-eled with the blueshifted components (Fig. 5 and 7). We identified this feature as Mg II λλ , ∼ − − to ∼ − with the total velocity width of ∼ − . The zero-velocity component seems to be mostprominent in the Mg II lines and this doublet is the only feature that is not blended significantlywith the high-velocity lines. Our model also found the low-ionization lines Al III λλ , II λ ∼ ∼ II line being the shallower of the two.Notably, we find no strong evidence for high-ionization absorption lines such as Si IV λλ , IV λλ , III and Mg II are always accompanied by high-ionization lines (e.g., Voit et al. 1993). Moreover, the owerful BAL outflow in SDSS J1352+4239 III opacity than Al II opacity for the zero-velocitycomponent also predicts significant high-ionization lines.We suspect that the gas cloud for the zero-velocity component is illuminated by continuumthat lacks the high-energy photons necessary to create such ions because it has been transmittedthrough the high-velocity part of the outflow. That is, in the presence of a multiple gas clouds alonga line of sight, the gas cloud further from the radiation source may see an absorbed “filtered” SEDfrom the back of the gas cloud that is located closer to the radiation source. This phenomenon hasbeen investigated previosuly by Leighly et al. (2018), they explored the potential possibilities for theradiation filtering with SDSS J0850+4451 by creating synthetic spectra using the filtered SEDs. Boththe accelerating and decelerating outflow scenarios with radiation filtering produced features that arenot seen in the spectra of SDSS J0850+4451 and they concluded no support for the radiation shieldingof outflowing gas in that object. Miller et al. (2018) analyzed the BAL troughs in LBQS 1206+1052considering the possible “shading effect” using photoionization modeling and suggested that thetwo-phase model was consistent with the data, but was not statistically distinguishable from a one-phase model; that is, the two-phase model was not required for the data. SDSS J1352+4239, on theother hand, seems to require an absorption component (zero-velocity component) originating from anabsorbed SED to avoid creating the high-excitation ions at zero-velocity and it is not possible to doso with an unabsorbed SED. The evidence is that we see several moderate to strong low-ionizationabsorption lines (e.g. Mg II , Al III ) from the zero-velocity component but the high-ionization linesnormally associated with those lines are completely absent from the spectrum.To test the filtering model, we first tried using a modified line list to model the zero-velocitycomponent. We removed the high-ionization ion transitions (ionization potential > Cloudy and usedthe resulting transmitted continuum to illuminate the next adjacent bin for a subsequent
Cloudy simulation to create the next transmitted continuum. The final filtered SED for the high-velocitytrough was calculated from the transmitted continuum of the final bin. A more detailed descriptionof the construction of the filtered SED can be found in Leighly et al. (2018) Appendix A.2. Weuse the filtered SED from the accelerating outflow calculation because we do not find a significantdifference between the accelerating and the decelerating outflow scenarios. Figure 9 shows how thefiltered SED differs from the unfiltered AGN SED and how the filtered SED for SDSS J1352+4239,an FeLoBAL, differs from that of SDSS J0850+4451, a LoBAL. A new ionic column density grid wascalculated using the filtered SED for the zero-velocity component.We fixed the emission and high-velocity trough components from the preliminary best-fittingmodel and fit only the zero-velocity component with the new column density grid from the filteredcontinuum. The physical parameters for the new grid were allowed to vary as fitting parameters. Fig-ure 10 shows how the zero-velocity component from the filtered SED produces sufficient low-ionizationlines to match the data without overproducing high-ionization lines. The ionization parameters forthe bins ranged between − . . Choi et al. −2 −1 0 1 2 3 4 log Energy (Ryd) −4−202 l o g ν F ν ( a r b i r a r y un i t s ) Leighly et al. 2018SDSS J1352+4239
Figure 9.
The unabsorbed AGN SED is plotted in black and the filtered SED generated from
Cloudy withthe physical parameters retrieved from the
SimBAL fit of the blueshifted component is plotted in red. Thefiltered SED from SDSS J0850+4451 (Leighly et al. 2018) is plotted in blue as a comparison. The greendashed vertical line, brown dot-dashed vertical line and the black vertical dotted line show the ionizingpotentials for H I , He I , and He II , respectively. SDSS J1352+4239 shows stronger attenuation in the Lymancontinuum, as expected for high column density FeLoBAL, than the LoBAL SDSS J0850+4451 which hasa thinner outflow that does not encompass the hydrogen ionization front. Rest Wavelength (Å) F λ ( − e r g s − c − Å − ) Al IIIAl IIC IVSi IV
Continuu Best ModelZero-Velocity Component
Mg IIFe II
Figure 10.
The cyan line represents the zero-velocity component model from the filtered grid. The filteredSED model produces sufficient opacity from the low-ionization ions (Mg II , Al III and Al II ) while high-ionization lines (C IV and Si IV ) are suppressed. large mainly because the absorption feature is shallow and only a small number of lines are presentin the spectrum.In summary, the absorption feature centered around zero-velocity only showed absorption linesfrom low-ionization species. The zero-velocity component from an SED filtered by the high-velocityoutflow provided a good fit by producing sufficient opacity for the low-ionization transitions withoutproducing deep high-ionization absorption lines. The distinction between this result and previousones looking for evidence for filtering or shading (Miller et al. 2018) is that while the previous effortsfound that the data were consistent with filtering, our data show the lack of high-ionization linesthat must be the signature of this phenomenon, and therefore require a filtered continuum. owerful BAL outflow in SDSS J1352+4239 l o g R [ p c ] −38000 −36000 −34000 −32000 −30000 −28000 Velocity Offset (km s −1 ) l o g ̇ M [ M ⊙ y − ] log ̇M tot ⊙ 3.51 ̇0.04−0.06 [M ⊙ y −1 ] Figure 11.
The radius and outflow mass estimates for each velocity bin. The outflowing wind is located ∼
10 pc away from the central engine. The log n and log U values for the bins in the higher and lower velocitygroups were constrained to have the same value. The total outflowing mass of 3200 ( M (cid:12) yr − ) is noted onthe bottom panel. 6. DERIVED PHYSICAL PROPERTIES OF THE OUTFLOWUsing
SimBAL , we can measure the physical parameters of the outflow and the uncertaintiesassociated with those values. We extracted the radius of the outflow using the following relationship: U = φnc = Q πR nc , where φ is the photoionizing flux in, photons s − cm − , and Q is the number of photoionizing photonsper second emitted from the central engine. Therefore, with the density and ionization measurementsfrom SimBAL we can calculate the location of the outflow R. The value of Q was estimated by scalingthe Cloudy input SED to the quasar spectrum and integrating the scaled SED for energies greaterthan the hydrogen ionization potential of 13.6 eV. We estimate log Q = 57.3 - 57.4 [photons s − ] whenscaled the flux density at 4000 ˚A ( F = 72 . × − ergs s − cm − ˚A − ) and to the near-infrared(rest-optical) photometry, respectively. We derived the radius of each bin using the sets of physicalparameters constrained by the tophat accordion model (Figure 11). We found that the location ofthe outflow is ∼
10 pc away from the center.Once we know the radius of the outflow, we can further calculate the mass outflow rate ofthe outflow and the kinetic luminosity associated with it. We computed the outflow mass using theequation from Dunn et al. (2010) ˙ M = 8 πµm p Ω RN H v, where the mean molecular weight is assumed to be µ = 1 .
4, the global covering fraction is given byΩ, and R , N H , and v are calculated from the best-fitting parameters from SimBAL . We calculatethe mass outflow rate for each bin (Figure 11) and sum them to estimate the total mass outflow rateof log ˙ M = 3 . ± .
04 [M (cid:12) yr − ]. The outflowing mass rate of 3210 +270 − (M (cid:12) yr − ) is about 18 timesthe mass accretion rate ( § . Choi et al. to 5% for effective quasar feedback that could reproduce the observed scaling relations between thehost galaxy and the central black hole (e.g., Di Matteo et al. 2005; Hopkins & Elvis 2010). Using theequation ˙ E k = ˙ M v /
2, we measure the log kinetic luminosity to be 48.1 ± .
04 [erg s − ] and L KE /L Bol of ∼
1. This value of kinetic luminosity is the largest ever found from BAL quasars and sets a newrecord for the strength of the quasar outflowing wind. We compare with other large L KE outflows in § ∼
40% of the solid angle, and that the fraction of objects with BAL featuresreflect the amount of sky covered by the quasar outflows in an individual object. Supporting thisview is the fact that (Hi)BALQs have similar broad band spectral energy distribution as the normalquasars (e.g., Gallagher et al. 2002, 2006, 2007b). However, the above number is derived from HiBALswith C IV lines, and LoBAL fractions can be as low as ∼
1% in a quasar sample (e.g., Trump et al.2006; Dai et al. 2012). Assuming this is the case, we would infer the global covering fraction for(Fe)LoBALs to be as low as ∼ ∼
40% has been found from a luminousinfrared selected sample (Dai et al. 2008). This value is about double of what Hewett & Foltz (2003)found from the optically selected sample but this discrepancy is not very surprising consideringBALQs tend to be more frequently reddened than non-BALQs (Krawczyk et al. 2015). Therefore,in principle, one can adopt the value of global covering fraction as large as 0.4 for all BALs or as lowas 0.01 for FeLoBALs depending on the assumption made to translate the statistical BAL fractionsinto global covering fractions.Instead of using a single global covering fraction, we constructed a model to explore the ideathat a single outflow exists in the vicinity of the central engine and multiple sightlines observe theoutflowing gas as different types of BAL (e.g., HiBAL, LoBAL or FeLoBAL) depending on the viewingangle and the column density the sightline passes through (Fig. 12). We estimated the mass outflowrate according to this scenario by gradually lowering the column densities of all the bins by thesame small amount while keeping all other parameters fixed to mimic the effect of sightlines passing owerful BAL outflow in SDSS J1352+4239 N H log U column densityparameter and recorded the parameters when the model no longer produced Fe II absorption linesand transformed to a LoBAL. We continued lowering the log N H log U column density parameteruntil the Mg II absorption lines disappeared to create a HiBAL. From this exercise we were able toestimate log N H values for different sightlines that can produce different BAL spectral types of thesame outflowing cloud reponsible for the trough in SDSS J1352+4239 ( N HHiBAL and N HLoBAL ). Wethen modify the use of single global covering fraction with the following equationΩ N H ⇒ Ω HiBAL N HHiBAL + Ω
LoBAL N HLoBAL + Ω
F eLoBAL N HF eLoBAL . Using the result from Dai et al. (2012), we set Ω
HiBAL , Ω
LoBAL , and Ω
F eLoBAL to be 0.14, 0.04, and0.02. Figure 12 shows the result of our exercise with the changes in the column density noted on theillustration. We obtain log L KE of ∼ − ] following the above interpretation. We concludethat the true value lies between 47.6 (computed using the scenario described here and in Figure 12)and 48.4 (computed using the maximum value Ω=0.4 from Dai et al. (2008)). Applying the samemethod, we obtain the range of mass outflow rate log ˙ M = 3.0 - 3.8 [M (cid:12) yr − ]. We note that thecurrent version of SimBAL that uses the grids calculated from the version C17 of
Cloudy is onlyavailable for the solar metallicity. A higher metallicity grid would yield a smaller column density andtherefore a smaller outflow rate (Leighly et al. 2018). DISCUSSION7.1.
A Plausible Geometry of the Outflows In § R τk =0 . νL ν ( V )) / (10 erg s − ) from Kishimoto et al. (2007), derived from near-infrared reverberationmonitoring, we estimated the distance to the innermost edge of the torus to be 3.5 pc. Furthermore,we estimated the dust sublimation radius R sub (cid:39) . R sub = 0 . L / pc fromLaor & Draine (1993). This indicates that the outflow is located in the vicinity of the dusty torus. § IV absorption features and suggested that such absorptionsignatures can originate from infalling clouds or rotating disk winds. SDSS J1352+4239, on the otherhand, does not show any redshifted high-ionization lines like the sample Hall et al. (2013) studied, soit is not possible to use their interpretation of the phenomenon directly. Also, none of the objects intheir sample shows strong blueshifted troughs, therefore it is possible that the physical conditions inSDSS J1352+4239 are very different from their objects. We speculate that this potential infalling gascould be originating from an earlier ejection episode and we are seeing the signature of the infallingremnant.Figure 12 shows a physical picture of our spectral model. From analyzing the best-fittingspectral model, we know the location of the BAL outflow is near the torus. Both the absorbedspectrum and the scattered flux are reddened, so the dusty reddening source must lie at a larger radius.The zero-velocity component must be located between the main outflow and the reddening sourceas the reddening source would transmit too few ionizing photons. We constrained the ionization4 Choi et al.
Figure 12.
The cartoon illustrates how each spectral model component corresponds to different physicalAGN components around the central black hole. The dashed lines represent the photons reaching thescattering medium to create the scattered flux and the solid lines represent the photons reaching the observer.The dotted lines represent different sightlines for HiBAL, LoBAL and FeLoBAL quasars ( § N H ) required to transform the spectrum from FeLoBAL to the other types and thedifferent global covering fractions (Ω) are labeled on the figure. The main BAL cloud is located slightlyfurther away from the central engine than the innermost edge of the torus, and the zero-velocity cloud mustbe located between the main cloud and the reddening source. The horizontal bar at the bottom of the figurerepresents the location on the accretion disk where the temperature is about 50,000 K ( § IV and H β emitting broad-line regions ( § R inner , R sub , and R wind ; § parameters for the zero-velocity component to be log U < . n < . − ] in order for the gas to be located further than the high velocityoutflow gas. We do not have enough information from the spectrum to determine the exact geometryof the scattering cloud. Potential follow up spectropolarimetry observations may help us gain aninsight into the geometry of some of the physical components in SDSS J1352+4239 we discussedthroughout the paper. 7.2. Acceleration Mechanisms
We calculated the momentum flux of the outflow from the equation ˙ P = ˙ M v (e.g., Faucher-Gigu`ere et al. 2012), and we found log ˙ P of 38.85 ± .
04 [dyne] (38.36 - 39.15 following the globalcovering fraction interpretation in § P of 37 - 38.5.Compared to log L Bol /c of 37.5, we find that the ratio between the momentum flux of the outflow andthe photon flux is around 20. The ratio of 20 is far greater than the what is expected of the momentum owerful BAL outflow in SDSS J1352+4239 −38000 −36000 −34000 −32000 −30000 −28000 Velocity Offset (km s −1 ) l o g F M Figure 13.
The force multiplier (FM) values computed for each bin using
Cloudy . The horizontal dashed linerepresents FM = L Edd / L Bol above which the absorber can be radiatively driven. Because SDSS J1352+4239is radiating at near Eddington limit, the FM threshold necessary for the radiative driving is low ( ∼
1) andthe FM values for each bin are also rather higher due to lower ionization parameters. For comparison, seeFig. 17 in Leighly et al. (2018) for LoBAL object SDSS J0850+4451. conserving wind where the maximum momentum flux of the outflow for a single scattering is L Bol /c ormomentum flux ratio of ∼ P . In the energy conserving scenario the outflowing winds get an additional push by theshocks generated from ISM interactions (e.g., Faucher-Gigu`ere & Quataert 2012). Such a mechanismcan generate a momentum boost and increase the momentum flux ratio between the outflowinggas and radiation by an order of magnitude. King & Pounds (2015) discuss various accelerationmechanisms for AGN outflows and compare the size scales of the energy conserving outflows and themomentum conserving outflows. An energy conserving mechanism mainly explains the ∼ kpc sizescale outflows where the Compton cooling time-scale becomes greater than the flow time-scale andthe full energy of the fast nuclear wind is communicated due to inefficient cooling (e.g., King et al.2011). The Compton cooling time for SDSS J1352+4239 is t c (cid:39) . × R kpc (cid:39)
12 yr (King et al.2011, Equation (7)) and we can calculate the flow time t flow = Rv (cid:39)
330 yr ( R ∼
10 pc , v ∼ . ∼ ∼
10 pc). The other mechanisminvolves scattering by dust, which has a larger scattering cross-section than resonance scatteringby ions (e.g., Fabian et al. 2008, 2018). Based on the size scale and the reddening observed inSDSS J1352+4239, it seems plausible that the outflow is a momentum conserving wind with theadditional momentum being harnessed by the dust. Thompson et al. (2015) points out that if theeffective infrared optical depth is significantly large at the cloud launch point, the outflowing gas canhave momentum ratio greater 1 with the momentum conserving mechanism.We further explored the acceleration mechanism responsible for the high-velocity outflow usingforce multiplier (FM) analysis. The FM is defined as the ratio of the total cross-section to theThompson cross-section. We used the best fit parameters from the model and
Cloudy to calculatethe force multiplier values for each bin. Figure 13 shows the FM values as a function of velocity.In order for radiative driving of absorbers to occur, FM (cid:62) ( L Edd / L
Bol ) − is a necessary condition6 Choi et al. (e.g., Netzer 2013). Leighly et al. (2018) calculated the FM values for their
SimBAL model ofLoBAL object SDSS J0850+4451 and found that not all tophat bins satisfied the above conditionand suggested that alternative driving mechanism might be necessary. However, SDSS J0850+4451is radiating at only 6% L Edd . SDSS J1352+4239, on the other hand, is radiating near the Eddingtonlimit (log ( L Edd / L
Bol ) ∼
0) therefore even with lower FM values, the absorber can be radiativelydriven as all 10 bins have FM values greater than ( L Edd / L
Bol ) − . This intuitively makes sense sincethe radiative driving relies on the power of radiation relative to the black hole mass. The FM valuesare smaller for the higher velocity bins because they have higher ionization parameter. Photoionizedgas with higher ionization will have fewer ions that can provide UV line opacity and therefore havelower FM.FM values alone do not fully explain how the main outflow in SDSS J1352+4239 was able toreach its high-velocity and large momentum ratio with a large outflow mass. Therefore we used theequation of motion to further probe how much radiative acceleration can be obtained with the givenFM values we found for the main outflow in SDSS J1352+4239. We use the equation for acceleration, v dvdR (cid:39) M ( R ) σ T L πR m p c − GM BH R where the first term represents the radiative acceleration with the force multiplier ( M ( R )) and thesecond term is the force of gravity from the black hole. Integrating this equation assuming a constantforce multiplier value ( F M ) we retrieve the following equation v ∞ = 32 , R − / . (6 . × − L F M − . M ) / km s − where v ∞ is the wind terminal velocity, R . is the inner wind radius or the launch radius in unitsof 0.1 pc, L is the luminosity of the quasar in the units of 10 erg s − and M is the black holemass in the units of 10 M (cid:12) . Figure 14 shows the wind velocities calculated from the above equation.The wind velocities for the lower velocity bins can reach the observed outflow velocities with thelaunch radius ( r l ∼ . r ∼
10 pc). But the higher velocitybins require a much smaller launch radius ( r l < . T ( R ) = (3 GM ˙ M / πR σ ) / where σ is the Stefan-Boltzmann constant, M is the massof the black hole and ˙ M is the accretion rate. This value is significantly smaller than the location of owerful BAL outflow in SDSS J1352+4239 −38000 −36000 −34000 −32000 −30000 −28000 Velocity Offset (km s −1 ) v ∞ r l = 5.0 (pc)r l = 0.1 (pc) Figure 14.
The wind terminal velocities for different inner wind radii ( r l = 5 . the outflow. Assuming constant outflow velocity of − − , it would take about 320 years forthe outflow to reach current location of 10 pc if the gas was launched at 50,000 K emission region ofthe accretion disk. The value is substantially larger than the rough estimate of the cloud dissipationtime (e.g., Hamann et al. 2013, t ∼ ∆ R Cloud / ∆ v ∼ s yr for SDSS J1352+4239). Therefore, wesuspect the outflow is being radiative driven by both the absorption lines and dust, launched nearthe torus at a large distance away from the disk.For example, Czerny et al. (2017) discuss a failed radiatively accelerated dusty outflow(FRADO) model to understand the motion of the clouds within the broad line region. Their modelis for the broad line region but it is possible that some of the clouds elevated by radiation pressurefrom the disk or dust would be entrained into the outflow. And these dusty gas clouds with highopacity can form an outflow that can potentially create BAL troughs.7.3. Comparison with Other Known Energetic Quasar Outflows
We compared our results with other exceptionally energetic outflows in the literature (Table 3).Borguet et al. (2013) found an outflow with log L KE of at least 46 [erg s − ] in SDSS J1106+1939 and itwas the most energetic BALQSO outflow ever reported at the time of publication. SDSS J0831+0354was also discovered to have a strong outflow with with log L KE = 45.7 [erg s − ] (Chamberlain et al.2015). Since their discovery, several more BAL quasars with comparable energetics have been found.Fiore et al. (2017) collected a large sample of AGN outflow data and performed a quantitativeanalysis on the properties of the outflows. Some ultra-fast outflow (UFO) objects with absorptionlines in the X-ray band have strong winds in their systems due to the high velocity of the outflows.APM 08279+5255 is a lensed quasar with an X-ray UFO feature that has a near-relativistic outflowwith log L KE = 46.85 [erg s − ] (Chartas et al. 2009). The energy of the outflows we discoveredin SDSS J1352+4239 is greater than even the most energetic UFO outflow known. Estimating theoutflow radius is crucial in estimating the kinetic luminosity of the outflows and it is worth noting8 Choi et al.
Table 3.
Comparison with Other BAL Quasar Outflows
Object log L Bol log M BH ˙ M log L KE Ω Reference[erg s − ] [M (cid:12) ] (M (cid:12) yr − ) [erg s − ]SDSS J1106+1939 (LoBAL) 47.2 8.9 390 +300 − +0 . − . +530 − +0 . − . +50 − +0 . − . § Note —The mass outflow rate and the kinetic luminosity of the outflow in SDSS J1352+4239 were estimated using multiple globalfractions ( § that the outflow radius calculation for UFOs are different from the BALQs. To estimate the radius,the density of the gas needs to be carefully constrained. For BAL spectra, the density of the gas canbe directly constrained by analyzing the density sensitive absorption lines, on the other hand, UFOsand X-ray spectra rely on an indirect method where the density is estimated by interpreting thetrough variability (e.g., Risaliti et al. 2002; Hemler et al. 2019). Among the objects listed in Table 3,SDSS J1352+4239 is the only FeLoBAL object and the most luminous. FeLoBAL objects are knownto have higher column density relative to the hydrogen ionization front (Lucy et al. 2014) than theother BAL objects and it is possible that in a large FeLoBAL sample we might be able to find moreBAL objects with comparable or more energetic outflows (Choi et al. in preparation; Dabbieri et al.in preparation). 7.4. How Special is SDSS J1352+4239?
SDSS J1352+4239 is a very luminous quasar with an energetic outflow and an impressiveoverlapping trough feature in the rest-UV spectrum. The quasar luminosity function shows thatsuch luminous quasars are rare objects in the universe with space densities 1 ∼ ∼ ∼ ∼ owerful BAL outflow in SDSS J1352+4239 Implications for AGN Feedback and Evolution
Theoretical model calculations require outflows to have the kinetic luminosities of about0.5 ∼
5% of the bolometric luminosity to contribute to AGN feedback and influence the star formationin the host galaxies (e.g., Di Matteo et al. 2005; Scannapieco & Oh 2004; Hopkins & Elvis 2010). Theenergy in the outflow we discovered in SDSS J1352+4239 is roughly the same as the quasar bolo-metric luminosity and we can confidently conclude that the outflow has more than enough energy toinfluence the star formation in the host galaxy and provide feedback. The strength of the outflow( L KE ) is thought to scale with the bolometric luminosity of the quasar (e.g., Costa et al. 2014; Zubo-vas & King 2012). SDSS J1352+4239 has a very high bolometric luminosity, greater than most of thequasars known to have extreme AGN luminosities (e.g., Bischetti et al. 2017, WISE/SDSS selectedhyper-luminous (WISSH) quasars), and the observed energetic outflow ( § § with PACS (Poglitsch et al. 2010) and SPIRE (Griffin et al. 2010), and wasdetected with PACS at 70 microns. We obtained the PACS data from the Herschel Science Archive .The infrared data are plotted in Figure 15 along with composite quasar SEDs from Richards et al.(2006a), Elvis et al. (1994) and Netzer et al. (2007). No far-infrared excess is detected. Thereforethe photometry data do not support the need for an extra SED component from a starbust. SUMMARYIn recent years, several discoveries of powerful AGN outflows have been made (e.g., Borguetet al. 2013; Fiore et al. 2017; Chartas et al. 2009). A number of such discoveries were made fromthe studies of X-ray observations or emission lines in the optical or mm bands. UV outflows fromBAL quasars have received less attention even though their discovery predates the other channels bydecades. There has not been a well-defined statistical analysis of the BAL absorbers primarily duethe complex nature of the BAL spectra.
SimBAL (Leighly et al. 2018) enables the first quantitativeand systemic studies of UV BAL outflows and their potential for feedback. With
SimBAL , wewere able to analyze the complex absorption features in the overlapping trough quasar spectrum of PI: Meisenheimer, “The Dusty Young Universe: Photometry and Spectroscopy of Quasars at z > http://archives.esac.esa.int/hsa/whsa Choi et al.
Rest Wave ength (μmμ F u ( D e n s i t ) ( m J ) μ Richards et a . 2006E vis et a . 1994Netzer et a . 2007Hersche SCUBA-2
Figure 15.
The broadband photometry data for SDSS J1352+4239 is plotted with mean quasar SEDsfrom Richards et al. (2006a) and Elvis et al. (1994). Both of these SEDs do not account for star formation,so the quasar intrinsic SED from Netzer et al. (2007) is plotted in orange as well. Black dots are thephotometry data from SDSS, 2MASS and WISE as described in § SDSS J1352+4239 and discover the most energetic AGN wind discovered to date with log kineticluminosity of 48 . ± .
04 [erg s − ]. Our principal results are as follows:1. In § α to measure the true redshift of 2 . ± . z ∼ . β line is 8.6 × M (cid:12) and L Edd for the given blackhole mass is 1.08 × [erg s − ] ( § L Bol = 48 . − ] with the mass accretion rate of 176 M (cid:12) per year ( § §
5, we discussed the kinematics and the physical conditions associated with the outflow inSDSS J1352+4239. Our model finds the maximum wind velocity of ∼ − − makingit the fastest FeLoBAL outflow ever found. We estimate the total covering-fraction-weightedcolumn density of log N H = 23 . ± .
05 [cm − ].4. In §
6, we measured the mass outflow rate of 3210 +270 − (M (cid:12) yr − ) with the global coveringfraction Ω = 0 .
2. The mass outflow rate is about 18 times higher than the mass accretion rate.We found that this outflow has the largest kinetic luminosity ever found with log L KE = 48 . ± .
04 [erg s − ]. For an estimated log L Bol of 48 [erg s − ], we calculate the ratio L KE /L Bol ∼ § owerful BAL outflow in SDSS J1352+4239 § ∼ § SimBAL (Choi et al. in prepa-ration), and further effort toward creating large sample of quasars with FeLoBAL outflows usingmachine learning techniques is currently underway (Dabbieri et al. in preparation).The author thanks Dr. Karen Leighly for her constructive feedback and advising and thecurrent
SimBAL group: Dr. Donald Terndrup, Collin Dabbieri, Ryan Hazlett and Collin McLeod.The work is funded by NSF grant AST-1518382 to the University of Oklahoma.This work is based on observations obtained at the Gemini Observatory, which is operatedby the Association of Universities for Research in Astronomy, Inc., under a cooperative agreementwith the NSF on behalf of the Gemini partnership: the National Science Foundation (United States),National Science and Engineering Research Council (Canada), CONICYT (Chile), Ministerio deCiencia, Tecnolog´ıa e Innovaci´on Productiva (Argentina), Minist´erio da Ciˆencia, Tecnologia e In-ova¸c˜ao (Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea). This workis based on observations obtained with the Apache Point Observatory 3.5-meter telescope, whichis owned and operated by the Astrophysical Research Consortium. The computing for this projectwas partly performed at the OU Supercomputing Center for Education & Research (OSCER) at theUniversity of Oklahoma (OU).The authors wish to recognize and acknowledge the very significant cultural role and reverencethat the summit of Mauna Kea has always had within the indigenous Hawaiian community. We aremost fortunate to have the opportunity to conduct observations from this mountain.
Facility:
Gemini:Gillett (GNIRS), ARC: 3.5m (Triplespec), Herschel (PACS)
Software: emcee (Foreman-Mackey et al. 2013), Sherpa (Freeman et al. 2001), SimBAL (Leighlyet al. 2018), Cloudy (Ferland et al. 2017) REFERENCES
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