starburst–agn mixing – ii. optically selected active galaxies€¦ · starburst–agn mixing...

MNRAS 444, 3961–3974 (2014) doi:10.1093/mnras/stu1740

Starburst–AGN mixing – II. Optically selected active galaxies

Rebecca L. Davies,1‹ Lisa J. Kewley,1,2 I-Ting Ho2 and Michael A. Dopita1,3

1Research School of Astronomy and Astrophysics, Australian National University, Cotter Road, Weston Creek, ACT 2611, Australia2Institute for Astronomy, University of Hawaii, 2680 Woodlawn Drive, Honolulu, HI 96822, USA3Astronomy Department, King Abdulaziz University, PO Box 80203, Jeddah 21411, Saudi Arabia

Accepted 2014 August 22. Received 2014 August 22; in original form 2014 June 26

ABSTRACTWe use four galaxies from the Calar Alto Legacy Integral Field Area survey with clear signsof accretion on to supermassive black holes to investigate the relative contribution of starformation and active galactic nucleus (AGN) activity to the line emission of each galaxy asa function of radius. The combination of star formation and AGN activity produces curved‘mixing sequences’ on standard optical diagnostic diagrams, and the fraction of emissiondue to AGN activity decreases smoothly with distance from the centre of the galaxy. We usethe AGN activity profiles to calculate the size of the AGN narrow line regions, which haveradii of ∼6.3 kpc. We calculate the fractional contribution of the star formation and the AGNactivity to the global Hα, [O II] λλ 3727,3729 and [O III] λ 5007 luminosities of each galaxy,and show that both ionization sources contribute significantly to the emission in all three lines.We use weighted combinations of stellar and AGN photoionization models to produce mixingmodels, which are consistent with observations for 85 per cent of spaxels across the galaxies inour sample. We also present a new diagnostic for starburst–AGN mixing which requires onlythe [O II], [O III] and Hβ emission lines, and can therefore be used to calculate AGN fractionsup to z ∼ 0.85 in the optical and z ∼ 3.5 in the near-infrared. We anticipate that this diagnosticwill facilitate studies of the properties of AGN ionizing radiation fields and the relative opticalcontribution of star formation and AGN activity over cosmic time.

Key words: galaxies: individual: NGC 7130 – galaxies: individual: NGC 2410 – galaxies:individual: NGC 6394 – galaxies: individual: NGC 6762 – galaxies: individual: IC 0540 –galaxies: Seyfert.

1 IN T RO D U C T I O N

The relationship between star formation and active galactic nucleus(AGN) activity is one of the unsolved problems in galaxy evolu-tion. Scaling relations between black hole mass and host galaxyproperties such as stellar velocity dispersion, bulge mass and bulgeluminosity strongly suggest that black holes grow simultaneouslywith their host galaxies (e.g. Kormendy & Richstone 1995; Magor-rian et al. 1998; Ferrarese & Merrit 2000; Gebhardt et al. 2000;Marconi & Hunt 2003; Haring & Rix 2004; Gultekin et al. 2009;Kormendy & Bender 2009; McConnell & Ma 2013). AGN activitymay regulate star formation in the host galaxy, or circumnuclearstar formation may play an important role in fuelling the accre-tion activity of the central supermassive black hole. However, thephysical processes responsible for driving this co-evolution remainunclear. The disparity between the physical scales on which starformation and accretion on to supermassive black holes occur has

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significantly mitigated attempts to develop theoretical models forsuch a causal connection (see Alexander & Hickox 2012, for areview).

The star formation rates (SFRs) of AGN host galaxies are oftencomparable to or greater than the SFRs of inactive galaxies at thesame stellar mass and redshift (e.g. Silverman et al. 2009; Mullaneyet al. 2012; Page et al. 2012; Santini et al. 2012; Floyd et al. 2013;Karouzos et al. 2014). The incidence of AGN activity increases withdecreasing stellar age (Silverman et al. 2009), and a total of 30–50 per cent of Seyfert 2 hosts have young stellar populations (e.g.Gonzalez Delgado, Heckman & Leitherer 2001; Storchi-Bergmannet al. 2001; Cid Fernandes et al. 2004; Gonzalez Delgado et al.2005; Sarzi et al. 2007). These results suggest that AGN activitypreferentially occurs in galaxies with young stellar populations andactive H II regions. However, star formation can also be quenchedor suppressed through powerful galaxy-scale outflows driven byenergy released during AGN accretion (e.g. Di Matteo, Springel &Hernquist 2005; Springel, Di Matteo & Hernquist 2005; Bower et al.2006; Croton et al. 2006; Schawinski et al. 2007; Nesvadba et al.2010; DeBuhr, Quataert & Ma 2012; Maiolino et al. 2012; Karouzos

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et al. 2014). A large number of AGN host galaxies lie in the ‘GreenValley’ of the galaxy colour–magnitude diagram (e.g. Kauffmannet al. 2003; Sanchez et al. 2004; Georgakakis et al. 2008). The greencolours of these galaxies suggest that star formation is on the wayto being quenched as part of a transition phase from the blue cloudto the red sequence (Schawinski et al. 2010). AGN activity is alsocommonly observed in quiescent (e.g. Olsen et al. 2013) and post-starburst (e.g. Schawinski et al. 2007; Cales, Brotherton & Shang2013) galaxies.

Recent studies have indicated that active star formation may be anecessary condition for the onset of AGN activity, even if this starformation is later suppressed by AGN feedback. Davies et al. (2007)find evidence for a 50–100 Myr delay between the onset of star for-mation and the fuelling of an AGN; suggesting that mass-loss fromgiant stars may be an important source of low angular momentumgas to fuel the central black hole. Similarly, Wild, Heckman & Char-lot (2010) find that the average black hole accretion rate increasesrapidly ∼250 Myr after the onset of a starburst; consistent with amodel in which the supermassive black hole feeds on just a smallfraction of the mass shed from intermediate mass stars in the stellarbulge. The suppressed accretion efficiency during the early stagesof the starburst is likely to be caused by high-energy supernovafeedback.

Studying spatially-resolved star formation in AGN host galaxiesmay provide significant insight into the starburst–AGN connection.The era of integral field unit (IFU) surveys for local galaxies isbeginning with the commencement of programmes such as the CalarAlto Legacy Integral Field Area (CALIFA) survey (Sanchez et al.2012a, Walcher et al. 2014), the Sydney-AAO Multi-Object IntegralField Spectrograph (SAMI) Galaxy Survey (Croom et al. 2012), theMapping Nearby Galaxies with APO (MaNGA) survey (part ofSDSS-IV), the Hobby-Eberly Telescope Dark Energy Experiment(HETDEX; Hill et al. 2008) and the Siding Spring Southern SeyfertSpectroscopic Snapshot Survey (S7; e.g. Dopita et al. 2014). TheseIFU surveys will facilitate statistical analysis of the radial variationsin star formation histories, SFRs and the relative fraction of starburstto AGN power in AGN host galaxies.

The [N II]/Hα versus [O III]/Hβ diagnostic diagram (Baldwin,Phillips & Terlevich 1981; Veilleux & Osterbrock 1987) is com-monly used to separate star formation from AGN activity. Theemission-line pairs used in each ratio ([N II] λ 6548 and Hα λ 6583,[O III] λ 5007 and Hβ λ 4861) are very close in wavelength, makingthe diagnostic virtually insensitive to reddening. The [O III]/Hβ ratiois sensitive to the electron temperature and ionization parameter ofthe line-emitting gas, and the [N II]/Hα ratio is a tracer of metallicitydue to the secondary nucleosynthetic production of nitrogen at highmetallicities (see Kewley et al. 2013b for further discussion). Purestar-forming galaxies and AGN host galaxies occupy two distinctsequences on the [N II]/Hα versus [O III]/Hβ diagnostic diagram (seee.g. Kauffmann et al. 2003; Kewley et al. 2006, 2013b). The posi-tions of H II regions along the star-forming sequence are determinedprimarily by their chemical abundances (Dopita & Evans 1986; Do-pita et al. 2000). The hardness of the stellar ionizing radiation fieldincreases with decreasing metallicity, perhaps due to stellar rota-tion or the effects of metal opacity (see e.g. de Mink et al. 2009;Levesque, Kewley & Larson 2010; Eldridge & Stanway 2012). TheAGN sequence branches from the enriched end of the star-formingsequence and moves towards larger [N II]/Hα and [O III]/Hβ ratiosas the AGN fraction and/or metallicity increases. The hard ionizingradiation field of the AGN enhances the [N II]/Hα and [O III]/Hβ ra-tios above their normal values for star-forming galaxies (see Kewleyet al. 2013b for more details). The composite region of the AGN

sequence (between the Kewley et al. 2001 theoretical upper boundand the Kauffmann et al. 2003 empirical upper bound to pure starformation) can also be occupied by star-forming galaxies with asignificant fraction of LINER-like emission (Kewley et al. 2006)e.g. due to shock excitation or ionization by post asymptotic giantbranch (pAGB) stars (e.g. Singh et al. 2013).

The minimum ‘distance’ (in [N II]/Hα versus [O III]/Hβ space) ofa galaxy (or spectrum) from the enriched end of the star-formingsequence can be quantified using the star-forming distance (dSF;Kewley et al. 2006). The dSF metric and other variations on ithave been used as relative indicators of the contribution of starformation and AGN activity to the line emission of AGN hostgalaxies. Wu et al. (2007) defined a quantity dAGN which measuresthe distance of a galaxy from the Kewley et al. (2001) theoreticalupper bound to pure star formation, along lines parallel to the AGNsequence. Another common approach for calculating relative AGNfractions is to populate the composite region of the [N II]/Hα versus[O III]/Hβ diagnostic diagram by summing observed spectra of purestar-forming and AGN-dominated galaxies with different relativeweightings. The AGN fractions of observed composite spectra canthen be determined by position-matching their line ratios with theline ratios of the ‘synthetic’ composite spectra (e.g. Heckman et al.2004; Kauffmann & Heckman 2009; Allen et al. 2013; Richardsonet al. 2014).

Unfortunately, dSF cannot provide an accurate estimate of thecontribution of the AGN to the total luminosity of the host galaxy,especially on the basis of a single spectrum. The metallicity andionization parameter of the H II region and AGN narrow line region(NLR) gas and the hardness of the AGN ionizing radiation field allimpact the slope and shape of the mixing curve between pure starformation and AGN activity. Variations in the gas conditions andthe nature of the radiation field between galaxies result in signif-icant uncertainty in the absolute AGN contribution. Integral fieldspectroscopy resolves these issues by allowing the star-forming andAGN-dominated regions to be separated spatially and spectrally.

In Davies et al. (2014; hereafter Paper I), we presented an opticalIFU study of the starburst–AGN composite galaxy NGC 7130. Wefound that (1) spaxels are distributed along curved mixing sequencesbetween the pure star-forming and AGN regions on standard opticaldiagnostics, and (2) the dominant ionizing source is strongly depen-dent on distance from the centre of the galaxy. This phenomenon isknown as starburst–AGN mixing. We showed that the smooth de-crease in the contribution from the AGN with increasing radius canbe used to calculate the relative contribution of the star formationand AGN activity to the line emission of each spaxel as well as thesize of the AGN NLR.

In this paper, we extend our study of starburst–AGN mixing toactive galaxies identified in the first data release of the CALIFAsurvey. The activity types (i.e. starburst versus AGN) of all galax-ies are determined by placing emission-line ratios extracted frommock single-fibre spectra (designed to mimic the Sloan Digital SkySurvey (SDSS) 3 arcsec fibre) on the [N II]/Hα and [S II]/Hα versus[O III]/Hβ diagnostic diagrams (described in Section 2). We populatethe same standard optical diagnostic diagrams with emission-lineratios derived from the spectrum of each spaxel in the integral fielddata cubes to demonstrate that the galaxies in our sample showstrong evidence of starburst–AGN mixing. We calculate the frac-tion of line emission due to star formation and AGN activity in eachspaxel, and use these fractions to determine the relative contribu-tions of the star formation and the AGN activity to the global Hα,[O II] and [O III] luminosities of the galaxies. We also calculate thesize of the AGN NLR for each galaxy (Section 3).

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We construct theoretical starburst–AGN mixing curves using acombination of stellar and AGN photoionization models, and in-vestigate their correspondence with observed mixing sequences.We also present a new starburst–AGN mixing diagnostic which re-quires only the [O II], [O III] and Hβ emission lines, and discuss thepotential of using this diagnostic to probe starburst–AGN mixingat high redshifts (Section 5). We summarize the conclusions of ourpaper in Section 6.

Throughout this paper, we adopt cosmological parametersH0 = 70.5 kms−1 Mpc−1, �� = 0.73, and �M = 0.27 based onthe 5-year Wilkinson Microwave Anisotropy Probe (WMAP) resultsby Hinshaw et al. (2009) and consistent with flat � cold dark mattercosmology.

2 SAMPLE SELECTION AND EMISSION-L I NEFL UXES

The CALIFA survey is a representative IFU survey of 600 galaxiesin the local Universe (0.005 < z < 0.03), covering a wide range ofluminosities (−23 � Mz � −16), colours (0.5 � u − z � 4) andmorphologies (as probed by the concentration index C, in three cate-gories: C < 2.3, 2.3 < C < 2.8, C > 2.8). The first data release (DR1)of the survey contains reduced blue (V1200, 3650 Å < λ < 4840 Å,R ∼ 1650) and red (V500, 3745 Å < λ < 7400 Å, R ∼ 850) datacubes for 100 galaxies. The data cubes, processed by an automaticdata reduction pipeline, have a spatial size of 74 arcsec × 64 arcsecon a rectangular 1 arcsec grid. The point spread function (PSF) ismeasured from stars in the field and has a median full width athalf-maximum (FWHM) of 3.7 arcsec (Husemann et al. 2013b).

Emission-line maps for the CALIFA galaxies are produced us-ing the emission-line fitting toolkit LZIFU written in IDL (Ho et al.in preparation). LZIFU uses the penalized pixel-fitting routine (Cap-pellari & Emsellem 2004) to model the stellar continuum, and theLevenberg-Marquardt least-squares method to model the emissionlines as Gaussians (MPFIT; Markwardt 2009). We adopt MIUS-CAT stellar models constructed by Vazdekis et al. (2012); covering4 metallicities ([M/H] = −0.71, −0.41, 0.0, +0.22) and 50 ages(0.06 < t < 18 Gyr). We perform simple stellar population fittingwith the primary aim of correcting for Balmer absorption due to oldstellar populations. We note that the results of the stellar populationfitting are not used to derive stellar ages or metallicities, and thus

the exact choice of stellar models will have a minimal effect on ourresults.

We use mock 4 kpc (physical size) aperture single-fibre spectrato place all galaxies from CALIFA DR1 on the [N II]/Hα versus[O III]/Hβ and [S II]/Hα versus [O III]/Hβ optical diagnostic dia-grams (see Fig. 1). Kewley, Jansen & Geller (2005) showed thatactivity-type classifications (i.e. starburst versus AGN) for galaxiesobserved as part of the SDSS are most robust in the redshift range0.04 ≤ z ≤ 0.1. The lower redshift limit ensures that the aperturecovers �20 per cent of the majority of galaxies and the upper red-shift limit ensures that the [S II] doublet (λλ 6717, 6731) is notredshifted out of the spectral range of the instrument. At the mid-point of this ideal redshift range (z = 0.07), 3 arcsec correspondsto ∼4 kpc.

Each galaxy is classified as either (a) pure star-forming, (b) com-posite, (c) Seyfert, (d) LINER, (e) Seyfert–LINER intermediateobject or (f) ambiguous based on the diagnostic lines of Kewleyet al. (2001), Kauffmann et al. (2003) and Kewley et al. (2006).A full description of the combined classification scheme can befound in Kewley et al. (2006). We note that our classifications mayvary slightly from those of Husemann et al. (2013b) due to differ-ences in the size of the line-ratio extraction aperture and the choiceof classification scheme. For this study, we select a subsample ofAGN-dominated objects (from categories c, d and e) satisfying thefollowing conditions:

(i) Hα, Hβ, [N II] and [O III] must all be detected at the 3σ levelin at least 100 spaxels. This condition aims to remove objects whichhave very weak emission lines and are therefore likely to be domi-nated by evolved stellar populations.

(ii) The [N II]/Hα and [O III]/Hβ maps must not show a strongnucleus + ring morphology. A significant fraction of the LINERgalaxies in CALIFA DR1 have LINER-like emission which is spa-tially confined to a very small region around the nucleus, surroundedby a ring of material with very weak emission lines and then a star-forming ring at larger radii. Post-AGB stars are likely to accountfor the majority of the nuclear LINER-like emission (Singh et al.2013), and even if weak AGN are present in these galaxies, the sharpdiscontinuities in their radial emission-line profiles make them un-suitable for this study.

Figure 1. [N II]/Hα versus [O III]/Hβ (left) and [S II]/Hα versus [O III]/Hβ (right) diagnostic diagrams with line ratios extracted from 4 kpc aperture nuclearspectra for each of the galaxies in CALIFA DR1. The galaxies are classified as either star forming (black; 41), composite (pink; 16), Seyfert 2 (red; 4),Seyfert–LINER intermediate (purple; 3) LINER (green; 27) or ambiguous (orange; 3) according to the combined classification scheme of Kewley et al. (2001),Kauffmann et al. (2003) and Kewley et al. (2006).

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Table 1. Recessional velocity, redshift, spatial scale per arcsecond (based on Hubble distance) and activity-type information for the four CALIFA galaxiesin our sample. We have selected AGN-dominated galaxies, rejecting LINERs because there is a high probability that they are powered by non-AGN sources(Singh et al. 2013).

Galaxy Recessional velocity (km s−1) (source: NED) Redshift pc arcsec−1 Previous classification Mock-SDSS classification

NGC 6394 8486 0.028 600 Sy2 Veron-Cetty & Veron (2006) Sy2NGC 2410 4861 0.016 340 Sy2 de Vaucouleurs et al. (1991) Sy2IC 0540 2035 0.007 150 – – Seyfert–LINERNGC 6762 2923 0.009 190 – – Seyfert–LINER

Our final sample consists of four galaxies: NGC 2410 (Seyfert2), NGC 6394 (Seyfert 2), IC 0540 (Seyfert–LINER intermediate)and NGC 6762 (LINER). The recessional velocity, redshift, spatialscale per arcsecond (derived directly from the Hubble distance),previous activity-type classifications, and mock-SDSS activity-typeclassifications for each of the four selected galaxies are listed inTable 1.

3 R ESULTS

3.1 Starburst–AGN mixing

We follow the analysis presented in Paper I. We populate the[N II]/Hα versus [O III]/Hβ and [S II]/Hα versus [O III]/Hβ diagnos-tic diagrams with emission-line ratios derived from the spectrum ofeach spaxel in the integral field data cube. We reject spaxels whereany of the four diagnostic strong lines (Hα, Hβ, [O III] and either[N II] or [S II] depending on the diagnostic) are detected at less thanthe 3σ level. The spaxels form mixing curves which lie along theSDSS AGN sequence. We split the mixing sequences into 10 sec-tions according to projected distance between the spaxels with themaximum and minimum [O III]/Hβ ratios. Row 1 of Fig. 2 showsthe [N II]/Hα versus [O III]/Hβ diagnostic diagrams for NGC 6394,NGC 2410, IC 0540 and NGC 6762, with spaxels colour-coded bysection along the mixing sequence. We use the assigned colour-coding to construct maps indicating where spaxels in each sectionalong the mixing sequence are located (Row 2). Row 3 shows the[S II]/Hα versus [O III]/Hβ diagnostic diagrams for the same galaxieswith spaxels colour-coded by section along the mixing sequence,and the corresponding maps are shown in Row 4. Digitized SkySurvey (DSS) images of the galaxies are shown in the bottom panel(Row 5), indicating the optical extent of the galaxy discs.

In all galaxies, there is a strong relationship between the positionof spaxels on the diagnostic diagram mixing sequences and theirdistance from the centre of the galaxy. The distinct rings seen in themaps reflect the fact that the contribution of the AGN Extreme Ul-traviolet (EUV) radiation field is greatest in the centre of the galaxyand decreases smoothly with radius. The stellar ionizing radiationfield becomes increasingly dominant until the line emission in theextended regions of the galaxy is consistent with ionization due topure star formation. The maps produced from the [N II]/Hα versus[O III]/Hβ and [S II]/Hα versus [O III]/Hβ diagnostic diagrams arequalitatively very similar; indicating that the two diagnostics areconsistent with one another. All four galaxies in our sample appearto be prototypical examples of starburst–AGN mixing.

3.2 Hα equivalent widths

Our analysis thus far has assumed that spaxels lying in the purestar-forming region of the [N II]/Hα versus [O III]/Hβ diagnosticdiagram are dominated by H II regions, and that spaxels lying in

the AGN region are dominated by black hole accretion activity.Although this may appear to be a reasonable assumption, integralfield spectroscopic studies have revealed that spaxels dominatedby pAGB stars and/or diffuse ionized gas (DIG) can have lineratios which mimic pure star formation or LINER-like AGN activity(e.g. Cid Fernandes et al. 2010; Kehrig et al. 2012; Singh et al.2013). The Hα equivalent width (EWHα) can be used to breakthe degeneracy between the SF/AGN and pAGB/DIG scenarios.Hα is produced in the photospheres of O-B stars and can alsobe collisionally excited in the presence of a hard ionizing radiationfield. As a result, EWHα should be considerably higher in H II regionsand AGN NLRs (EWHα � 6) than in regions dominated by DIGor pAGB stars (0.1 < EWHα < 2.4; Cid Fernandes et al. 2010;Papaderos et al. 2013; Sanchez et al. 2014).

Fig. 3 (top) shows EWHα maps for each of the four galaxies;covering all spaxels where Hα is detected at the 3σ level. (Notethat we use positive EWHα values to indicate Hα in emission). Weshow [N II]/Hα versus [O III]/Hβ diagnostic diagrams with spaxelscolour-coded by EWHα in the bottom row. The colour bars arescaled to span the range of EWHα values measured for spaxels inwhich all BPT strong lines are detected at the 3σ level (mixingsequence spaxels). 100 per cent of the mixing sequence spaxelsin NGC 2410 and NGC 6394 have EWHα > 3; confirming thatthe emission from these galaxies is dominated by a combinationof star formation and Seyfert 2 AGN activity. The EWHα mapsreveal complex, clumpy structures of H II regions in both objects.The spaxels with the highest EWHα also appear to have the lowestAGN fractions; indicating that the H II regions dominate the globalproduction of Hα. These findings confirm that NGC 6394 and NGC2410 are prototypical examples of starburst–AGN mixing.

In IC 0540, more than 90 per cent of the spaxels have EWHα > 3;indicating that the possible rate of contamination from DIG/pAGBemission is low. The Hα emission is very centrally concentrated andthe EWHα decreases from the centre outwards. The spaxels with thehighest EWHα also lie strongly in the AGN region of the diagnosticdiagram; suggesting that a central AGN may be responsible for themajority of the Hα emission in this galaxy. Low-level emission froman underlying stellar population is likely to contribute to the opticalline emission; causing the AGN spectrum to become increasinglydiluted with radius.

In contrast, 90 per cent of the spaxels in NGC 6762 haveEWHα < 3; indicating that pAGB stars are likely to be responsiblefor a significant fraction of its line emission. Kehrig et al. (2012)compare the spatially resolved emission-line ratios of NGC 6762with AGN, pAGB and fast shock models, and conclude that thepAGB scenario is most consistent with the observations. However,they note that they are unable to match the largest observed [N II]/Hα

ratios without increasing the N/O ratio in the models. It is possiblethat mixing between a LINER AGN and pAGB stars would providea better overall fit to the data for this galaxy, as the AGN modelscan easily fit the high [N II]/Hα ratios (see Section 4.3), whilst the

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Figure 2. Row 1: [N II]/Hα versus [O III]/Hβ diagnostic diagrams with spaxels colour-coded by distance along the mixing sequences. Row 2: maps showingthe locations of spaxels for which all of the BPT strong lines are detected at least the 3σ level, using the colour-coding assigned from the mixing sequences.Rows 3 and 4 are the same as Rows 1 and 2 but using the [S II]/Hα versus [O III]/Hβ diagnostic diagram. Bottom row: DSS (broad-band) images of the galaxiesindicating the optical extents of their discs. Solid lines on the diagnostic diagrams trace the theoretical upper bound to pure star formation (Kewley et al.2001). Dashed lines on the [S II]/Hα versus [O III]/Hβ diagnostic diagrams indicate the empirical division between Seyfert and LINER-like emission (Kewleyet al. 2006). White bars on the maps show the physical scale of 10 pixels. Beige contours trace the integrated continuum emission over the wavelength range3750 Å < λ < 7500 Å. Left to right: NGC 6394, NGC 2410, IC 0540, NGC 6762. In all galaxies there is a clear relationship between the position of spaxelson the BPT diagram mixing sequences and their distance from the centre of the galaxy.

pAGB stars provide the underlying ionization source required todilute the AGN spectrum and produce the mixing sequence we ob-serve. Further diagnostics and modelling are required to distinguishbetween these scenarios.

3.3 Starburst–AGN fractions

We calculate the fraction of emission due to star formation and AGNactivity for each individual spaxel in NGC 6394 and NGC 2410. Wecannot numerically calibrate the mixing sequences of NGC 6762and IC 0540 to calculate AGN fractions because these galaxies do

not have any spaxels which can be conclusively identified as havingno contamination from AGN activity. Empirical mixing sequencesare created for NGC 6394 and NGC 2410 by assigning the spaxelswith the minimum and maximum [O III]/Hβ ratios as 0 per cent and100 per cent AGN fraction, respectively. The AGN fractions of allother spaxels are calculated according to their projected distancebetween these two extreme points. The relative error on the AGNfraction (fAGN/fAGN) of each spaxel is assumed to be 6.3 per cent(see discussion in Section 4.4).

We derive the AGN-fraction-weighted Hα ([O III]) luminosityof each spaxel in NGC 6394 and NGC 2410 by multiplying the

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Figure 3. Top: Hα equivalent width (EWHα) maps covering all spaxels in which Hα is detected at the 3σ level, and bottom: [N II]/Hα versus [O III]/Hβ

diagnostic diagrams with spaxels colour-coded by EWHα for (left to right) NGC 6394, NGC 2410, IC 0540 and NGC 6762. More than 90 per cent of spaxelsin NGC 6394, NGC 2410 and IC 0540 have EWHα > 3; confirming that their emission is dominated by a combination of star formation and AGN activity. Incontrast, 90 per cent of the spaxels in NGC 6762 have EWHα < 3; indicating that there is likely to be a significant contribution from post-AGB stars.

Hα ([O III]) luminosity of the spaxel (Hαn, [O III]n) with the cor-responding (empirically calculated) AGN fraction (fn). The globalHα ([O III]) luminosity due to the AGN (HαAGN, [O III]AGN) is givenby summing the AGN-fraction-weighted Hα ([O III]) luminositiesacross all spaxels in each galaxy. It is then trivial to calculate theglobal fraction of the Hα ([O III]) luminosity due to the AGN bytaking the ratio of HαAGN ([O III]AGN) to the total Hα ([O III]) lumi-nosity of the galaxy (see Paper I for a more detailed explanation ofthe calculations). The results are listed in Table 2.

In both galaxies, stellar photoionization dominates the global pro-duction of Hα, whereas ionization by the hard EUV radiation fieldof the AGN is the dominant source of [O III] emission, as expected.However, the AGN is responsible for exciting at least 25 per cent ofthe Hα emission; indicating the degree to which SFRs calculatedfrom Hα are overestimated in AGN host galaxies. More importantly,this fraction allows us to explore the possible contribution of AGNactivity to the Hα flux of intermediate to high redshift ‘star-forming’galaxies. Traditionally, galaxies are classified using [N II]/Hα and[O III]/Hβ ratios extracted from spectra integrated within fibres offixed angular size (e.g. the 3 arcsec SDSS fibre). However, the phys-ical covering size of such fibres increases strongly as a function ofredshift. The activity-type classifications of high-redshift galaxiestherefore reflect their globally averaged spectra rather than theirnuclear spectra, which can cause actively star-forming AGN hostgalaxies to be classified as pure star-forming.

To illustrate this, we have extracted [N II]/Hα and [O III]/Hβ ra-tios from spectra integrated across the entire field of view of theCALIFA data cubes for NGC 6394 and NGC 2410. This corre-sponds to a physical coverage of ∼21 × 25 and ∼38 × 44 kpcat the redshifts of NGC 2410 and NGC 6394, respectively. Fig. 4compares the globally integrated line ratios of these galaxies (black)

Figure 4. Left: [N II]/Hα versus [O III]/Hβ, and right: [S II]/Hα versus[O III]/Hβ with line ratios extracted from (black) globally integrated spectraand (red) 4 kpc aperture nuclear spectra of (diamonds) NGC 6394 and (stars)NGC 2410. Although NGC 6394 and NGC 2410 are Seyfert 2 hosts, theywould both be classified as star-forming galaxies if they were observed witha single fibre at intermediate to high redshift.

with line ratios extracted from 4 kpc aperture nuclear spectra (red).Points corresponding to NGC 2410 and NGC 6394 have been plot-ted as stars and diamonds, respectively. Although both NGC 6394and NGC 2410 are clearly classified as Seyfert 2 hosts within a4 kpc nuclear aperture, their globally integrated spectra place thembeneath the Kewley et al. (2001) theoretical upper bound to purestar formation in both the [N II]/Hα and [S II]/Hα versus [O III]/Hβ

diagnostic diagrams. These galaxies would be classified as purestar-forming if they were observed at high redshift, but we haveshown that the AGN is responsible for at least 25 per cent of the Hα

emission in both of these objects. This highlights the need to takecare when calculating SFRs from single-fibre spectra; especially atz � 1, where the fraction of galaxies hosting AGN is much largerthan in the local Universe (see e.g. Bundy et al. 2008; Aird et al.2012).

Table 2. Relative contribution of stellar and AGN photoionization to the global Hα and [O III]luminosities, AGN NLR radii, and NLR [O III] luminosities for NGC 6394 and NGC 2410.

Galaxy Star formation (per cent) AGN activity (per cent) NLR radius LNLR,[O III]Hα [O III] Hα [O III] (kpc)

NGC 6394 74 ± 4 25 ± 1 26 ± 1 75 ± 4 6.2 ± 2.2 6.86e+40NGC 2410 63 ± 3 24 ± 1 37 ± 2 76 ± 4 6.4 ± 1.2 4.04e+40

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3.4 AGN NLR radii

We define the radius of the AGN NLR in each galaxy to be theaverage radius at which the AGN fraction transitions from ≥20to <20 per cent. The errors on the NLR radii take into account boththe dispersion in transition radii between radial vectors in eachgalaxy, and the smoothing of light across several pixels due to thelarge FWHM of the PSFs.

The AGN NLRs of NGC 6394 and NGC 2410 have radiiof ∼6.3 kpc (see Table 2). These radii are consistent (within thequoted errors) with the majority of Seyfert 2 NLRs which are1–5 kpc in radius (Bennert et al. 2006), but smaller than the ex-tended NLRs of quasi-stellar objects which can reach out to tensof kpc from the nucleus (e.g. Greene et al. 2011; Husemann et al.2013a). Statistical studies of AGN NLRs have shown that their sizeis correlated with their total [O III] luminosity over three orders ofmagnitude in [O III] luminosity (e.g. Bennert et al. 2002; Schmittet al. 2003). The [O III] luminosities of the AGN NLRs of NGC6394 and NGC 2410 (listed in Table 2) are more than two orders ofmagnitude lower than the average [O III] luminosities of the quasarsin the Husemann et al. (2013a) sample; consistent with the signifi-cantly smaller AGN NLR radii of our objects.

We can use the largest radius at which we observe [N II], Hα,[O III] and Hβ as a lower limit on the size of the NLR for IC 0540,which we find to be 0.47 kpc. This is small compared to the NLRradii for the Seyfert galaxies in our sample, but large comparedto the average extent of Hα emission in LINER galaxies (whichranges from a few tens to hundreds of parsecs; Masegosa et al.2011); consistent with our classification of this galaxy as a Seyfert–LINER intermediate object. The inclination of NGC 6762 to theline of sight is too large to allow for distance measurements to beaccurately deprojected, preventing even a lower limit on the NLRsize from being calculated.

It is important to consider the potential impact of peculiar ve-locities (which can routinely be as large as a few hundred to1000 km s−1; e.g. Lauer & Postman 1994; Karachentsev et al. 2006;Watkins, Feldman & Hudson 2009) on the calculated distances ofthe galaxies and therefore the conversion between angular and phys-ical scales. NGC 6394 and NGC 2410 have recessional velocitiesof ∼8500 and ∼4900 km s−1, respectively; corresponding to pos-sible distance errors of up to ∼10 and ∼20 per cent. These errorsare quite small, indicating that any deviations between the true andcalculated NLR radii will also be minimal. IC 0540 has a reces-sional velocity of ∼2000 km s−1, corresponding to a much largerpotential distance error of up to 50 per cent. However, increasingor decreasing the upper limit on the NLR radius of IC 0540 by50 per cent does not change our conclusions.

4 STA R BU R S T– AG N M I X I N G M O D E L S

The identification of starburst–AGN mixing in all four AGN-dominated galaxies in CALIFA DR1 suggests that starburst–AGNmixing may be a common phenomenon. For this reason, we explorethe possibility of using theoretical mixing curves to investigate theproperties of the interstellar medium (ISM) and the stellar and AGNionizing radiation fields. If theoretical mixing sequences are able toreproduce the shape of observed mixing sequences, then they couldbe used to constrain the metallicity (Z) and ionization parameter(q) of the H II region and AGN NLR gas, the electron density inthe AGN NLR (ne) and the hardness of the AGN ionizing radiationfield ().

Theoretical mixing lines are constructed by linearly adding pureH II region and AGN NLR spectra with different relative weight-ings (AGN fractions). For effective comparison with our data, weconstruct mixing lines with AGN fractions between 0–100 per centin 10 per cent increments. We extract H II region and AGN NLRnebular emission spectra from the grids calculated by Dopita et al.(2013) and Groves, Dopita & Sutherland (2004), respectively.

The shapes of the stellar and AGN ionizing radiation fields havebeen characterized using the STARBURST99 stellar evolutionary syn-thesis models of Leitherer et al. (1999) and the Dusty AGN modelsof Groves et al. (2004), respectively. These radiation fields form theinput for the shock and photoionization code MAPPINGS (Binette,Dopita & Tuohy 1985; Sutherland & Dopita 1993; Allen et al. 2008;Dopita et al. 2013), which models the ISM and produces a simu-lated emission-line spectrum from the nebular gas surrounding theionizing radiation field.

4.1 MAPPINGS photoionization code

4.1.1 STARBURST99 stellar evolutionary synthesis models

The STARBURST99 stellar evolutionary synthesis models we use aredescribed in detail in Levesque, Kewley & Larson (2010) andNicholls, Dopita & Sutherland (2012). These models are based onthe stellar atmosphere models of Pauldrach, Hoffmann & Lennon(2001) and Hillier & Miller (1998), which consider the impact ofmetal opacities on the ionizing radiation field seen by the ISM. Thestellar populations are evolved along the ‘high’ mass-loss evolu-tionary tracks of Meynet et al. (1994), using a Salpeter initial massfunction (Salpeter 1955) and zero-age instantaneous burst modelswhich provide the best match to the SDSS H II region sequence atz ∼ 0 (Levesque et al. 2010).

4.1.2 Dusty AGN models

The dusty, radiation-pressure-dominated AGN models we use aredescribed in detail in Groves et al. (2004). One-dimensional equilib-rium photoionization models with plane–parallel geometry describethe photoionization of the AGN NLR by the ionizing radiation fieldfrom the central engine. The combination of power-law AGN spec-tra and low electron densities (102–104 cm−3) in the NLR cloudsproduces a large number of characteristic forbidden emission lines.

The Dusty AGN models are unique in their treatment of dust andimplementation of radiation pressure physics. The models considerthe absorption, scattering and polarization of light in the presenceof dust. Radiation pressure from two sources is considered – theforce exerted by photoionization processes, and absorption by dust.The relative significance of these two components varies with wave-length, but the latter is most significant in the far-ultraviolet wherethe hydrogen opacity is effectively zero and the dust opacity is verylarge. By including radiation pressure physics and the impact ofdust on photoionization, these models are able to account for thewide range of ionization states observed in individual NLRs, as wellas the fast, radiatively driven outflows observed in Seyfert galaxies(see Groves et al. 2004, for a more in-depth discussion).

The AGN models are calculated for a variety of spectral indicesbetween 1.2 < < 2. The spectral index quantifies the slope of theionizing radiation field as a function of frequency, such that a larger corresponds to a softer ionizing radiation field and a lower to aharder ionizing radiation field.

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4.1.3 Nebular emission

The MAPPINGS shock & photoionization code takes an input ion-izing radiation field and calculates photoionization, excitation andrecombination throughout the nebula, stopping when the hydrogengas is fully recombined. The main parameters influencing the shapeof the resulting spectrum are the shape of the input ionizing ra-diation field and the nebular metallicity and ionization parameter.The ionization parameter q is interpreted as the maximum velocityionization front an ionizing radiation field is able to drive througha nebula. It has dimensions of cm s−1, and is related to the dimen-sionless ionization parameter U by U = q/c.

MAPPINGS IV incorporates new atomic data and Maxwell col-lision strengths as well as a non-thermal (κ) electron temperaturedistribution (described in detail in Nicholls et al. 2012, 2013). Thedefining feature of this distribution is that the fraction of hot elec-trons can be varied using the κ value. Setting κ = ∞ yields theMaxwell–Boltzmann distribution, and the fraction of hot electronsincreases as the κ value is decreased. Selecting κ = 20 producesmodel spectra which are consistent with observations for the vastmajority of local H II regions, and the resulting distribution deviatesonly minimally from the standard Maxwell–Boltzmann distribution(Nicholls et al. 2012).

The κ electron temperature distribution was first introduced byVasyliunas (1968) to explain the excess of hot electrons in theEarth’s magnetosphere. Since then, κ distributions have also beenidentified in the magnetospheres of all the gas giant planets as well asMercury, Titan and Io (see references in Pierrard & Lazar 2010) andat the interface between the solar heliosheath and the surroundingISM (Livadiotis et al. 2011). These κ distributions arise due toexternal energy input, which prevents the system from relaxingto a classical Maxwell–Boltzmann distribution (see discussion inNicholls et al. 2012). Applying the κ distribution to extragalacticH II regions resolves the long standing discrepancy between electrontemperatures calculated using direct, recombination line and strongline ratio methods (Nicholls et al. 2012).

The grid of H II region nebular emission spectra from Dopita et al.(2013) is three-dimensional, and covers a range of hot electronfractions (κ = 10, 20, 50, ∞), metallicities (0.2 Z� < Z < 5Z�; 7.99 < 12 + log(O/H) < 9.39) and dimensionless ionizationparameters (−4 < log U < −2). The grid of AGN NLR nebularemission spectra from Groves et al. (2004) is four-dimensional, andcovers a range of electron densities (100 cm−3 < ne < 10 000 cm−3),AGN radiation field shapes (1.2 < < 2.0), metallicities (0.25Z� < Z < 4 Z�; 8.09 < 12 + log(O/H) < 9.29) and dimensionlessionization parameters (−4 < log U < 0).

4.2 Constraints on model parameters

Each theoretical mixing line, produced by combining one H II re-gion spectrum with one AGN NLR spectrum, is uniquely definedby seven parameters. It is impossible to independently constrain allof these parameters using only one diagnostic diagram with fouremission lines. We adopt κ = 20 (see discussion in Section 4.2),ne = 1000 cm−3 (see e.g. Stauffer 1982; Keel 1983; Phillips et al.1986) and = 1.7 (see e.g. Ho, Shields & Filippenko 1993a;Groves, Dopita & Sutherland 2004), and then select the metallicityand ionization parameter values which produce the best correspon-dence between the theoretical and observed mixing sequence foreach galaxy. It is important to note that the metallicity and ioniza-tion parameter are degenerate quantities, such that a more enriched,higher ionization model can produce the same line ratios as a more

pristine, lower ionization model (Kewley et al. 2001, 2013b). De-tailed diagnostics employing a larger range of emission lines arerequired in order to discriminate between these degenerate scenar-ios. At present we are only concerned with the ability of the modelsto fit the data and not the exact parameters defining the models, andtherefore discussion of the chosen model parameters is beyond thescope of this paper.

The star formation activity of individual H II regions induces smallvariations in the metallicity and ionization parameter of the ISM. Inorder to account for such variations, it is possible to mix betweenseveral H II region and AGN NLR spectra with similar ionizationparameter values and/or metallicities. For each galaxy, we extractpure H II region and AGN NLR spectra at three adjacent ionizationparameter values (U = 0.3), and mix all possible combinationsof these spectra to obtain nine values for the flux in each emissionline at each AGN fraction. Unfortunately, the grids are not sampledfinely enough in metallicity to allow for similar treatment.

4.3 Results

The [N II]/Hα versus [O III]/Hβ diagnostic diagrams for the fourCALIFA galaxies and NGC 7130 are shown in Fig. 5, with thechosen mixing models overplotted as black crosses. We includeNGC 7130 as a known example of starburst–AGN mixing whoseobserved mixing sequence has not yet been compared to theoreticalmixing curves (see Paper I). The chosen mixing models are con-sistent with observations for an average of 85 per cent of spaxelsacross all five galaxies, and it is clear that the models are able toreproduce the shapes of the observed mixing sequences. Mixingbetween different ionization parameters accounts for the spread inthe observed mixing sequences in the direction perpendicular tothe AGN fraction vector, although the true spread appears to besmaller than possible with the models. It is interesting to note thatthe Seyfert–LINER intermediate objects have much less spread intheir mixing sequences than the Seyfert 2 hosts. This may reflecta lack of active star formation to induce local ionization parametervariations.

4.4 Intrinsic scatter in AGN fractions

The empirical AGN fraction calculations presented in Section 3.3are based on the assumption that all points along the starburst–AGN mixing sequence of a given galaxy are consistent with mixingbetween one star-forming spectrum and one AGN NLR spectrum.This is equivalent to assuming that all gas ionized by star forma-tion must have approximately the same metallicity and ionizationparameter, with the same requirement for the AGN NLR gas. How-ever, our analysis from Section 4.3 indicates that there are small butsignificant variations in the physical conditions of the ISM withingalaxies. We apply our analysis from Section 3.3 to theoreticalmixing curves with a spread in ionization parameter, and comparethe known AGN fractions of models along these curves with theAGN fractions calculated using our empirical method. This allowsus to quantify the intrinsic errors on the AGN fractions calculatedin Section 3.3.

We show an example of a theoretical mixing sequence in Fig. 6,with points colour-coded by AGN fraction in 10 per cent incre-ments up the sequence. Our empirical method will only recover thetrue AGN fractions of all model spectra when their distances alongthe mixing sequence are purely dependent on their AGN fractions(colour in Fig. 6). In the pure star-forming region of the diagnosticdiagram, model spectra at a given AGN fraction lie at very similar

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Figure 5. [N II]/Hα versus [O III]/Hβ diagnostic diagrams for NGC 7130, NGC 6394, NGC 2410, IC 0540 and NGC 6762, with starburst–AGN mixing modelsoverplotted as black crosses. The colour-coding of spaxels is the same as in Fig. 1. Mixing models are constructed by linearly adding H II region and AGNNLR spectra with different relative weightings (AGN fractions). Solid lines connect models of constant AGN fraction (indicated by the percentages), spacedin 10 per cent increments. We adopt models with κ = 20 (hot electron fraction), = 1.7 (hardness of the AGN ionizing radiation field) and ne = 1000 cm−3

(density of the AGN NLR clouds). The metallicity and ionization parameter values for each galaxy are selected to provide the best correspondence betweenthe theoretical and observed mixing sequences.

Figure 6. Theoretical starburst–AGN mixing curves produced by mixingthree stellar photoionization models with three AGN photoionization mod-els. The individual H II region and AGN NLR models differ only in their ion-ization parameter values, which are adjacent in the model grids (U = 0.3).Each colour represents a single AGN fraction between 0 per cent (black) and100 per cent (pink), with a 10 per cent increment in AGN fraction betweencolours.

distances along the mixing sequence. However, as the contributionof the AGN increases, model spectra at a given AGN fraction be-come increasingly scattered along the mixing sequence, such thatthe relative error (fAGN/fAGN) on empirically calculated AGN frac-tions is ∼6.3 per cent. This is a conservative estimate of the error

given that our simulated ionization parameter variations producemixing sequences with larger spread than observed.

Unfortunately, the models grids are too coarsely sampled inmetallicity to allow for a similar investigation. Given the degen-eracy between ionization parameter and metallicity in the mix-ing models, we expect metallicity variations to mimic ionizationparameter variations – thus having minimal, if any, impact on theintrinsic errors for the calculated AGN fractions.

It is also important to consider the impact of metallicity gra-dients on our AGN fraction calculations. It is well establishedthat gas-phase metallicity gradients are present in the majority ofmassive spiral galaxies in the local Universe (e.g. McCall 1982;Zaritsky, Kennicutt & Huchra 1994; van Zee et al. 1998), and re-cent results from the CALIFA survey have confirmed and extendedthese findings by mapping gas-phase and stellar abundances acrosslarge numbers of local galaxies (e.g. Sanchez et al. 2012b, 2014;Sanchez-Blazquez et al. 2014). As mentioned in the introduction,the AGN sequence on the [N II]/Hα versus [O III]/Hβ BPT dia-gram traces variations in both the metallicity and the ionizationparameter of the line-emitting gas. Therefore, metallicity gradi-ents may impact the shapes of derived AGN fraction profiles. Byconstructing theoretical starburst–AGN mixing curves with differ-ent relative abundances between the starburst and AGN models(whilst holding all other parameters constant), we have determinedthat the presence of a smooth metallicity gradient (decreasing lin-early and monotonically with radius) does not increase the dis-persion in the mixing sequences. The resulting AGN fractions areconsistent with those calculated from models with no metallicitygradient.

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5 STA R BU R S T– AG N M I X I N G AT H I G HRE DSHIFT

5.1 Motivation

We have shown that integral field spectroscopic observations ofstarburst–AGN mixing signatures on the [N II]/Hα versus [O III]/Hβ

diagnostic diagram provide a method for probing (a) the relativecontribution of star formation and AGN activity, both spatially andas a fraction of global emission-line luminosities and fluxes, (b) thephysical conditions of the ISM and (c) the hardness of the ionizingradiation field in AGN host galaxies. Theoretical and observationalstudies have indicated that the physical conditions of the ISM vary asa function of redshift and that the slope and shape of starburst–AGNmixing sequences should evolve over cosmic time (e.g. Kewley et al.2013a,b). Observations of starburst–AGN mixing at high redshiftcould provide further constraints on the evolution of the ionizationparameter and the hardness of AGN ionizing radiation fields, andtherefore potentially provide insight into whether (and how) thephysics of AGN accretion has evolved over the last 10 billion years.

Analysis of the radial variations in the rest-frame optical line ra-tios of high-redshift galaxies requires high resolution observationstaken using NIR IFUs. Advanced adaptive optics (AO) systemshave made it possible to attain PSFs with an FWHM of a few kpcfor galaxies at z ∼ 2. Newman et al. (2014) utilize the variationsin diagnostic line ratios as a function of radius to probe the im-portance of star formation, AGN activity and shock excitation in10 star-forming galaxies at z ∼ 2 from the Spectroscopic Imag-ing in the Near-infrared with SINFONI (Spectrograph for IntegralField Observation in the Near Infrared) survey. Yuan et al. (2011)measure the gradient in the gas-phase metal abundance of a lensedgalaxy at z = 1.49 using laser guide star AO observations from theOH-Suppressing Infrared Integral Field Spectrograph (OSIRIS) onKeck II. Jorgenson & Wolfe (2014) also use OSIRIS data to con-struct maps of the Hα and [O III] lines for a Lyα-emitter at z ∼ 2.2,and Nesvadba, Lehnert & Genzel (2007) present an argument forthe existence of a starburst-driven wind in a sub-millimetre galaxyat z ∼ 2.56 using deep NIR IFU data from the SPectrometer forInfrared Faint Field Imaging (SPIFFI) instrument on the Very LargeTelescope (VLT). These works highlight the growing potential touse the spatial variation of emission-line fluxes and ratios as diag-nostics for the principle ionization sources of high-redshift galaxies.

Unfortunately, the redshift range over which the [N II]/Hα ver-sus [O III]/Hβ diagnostic diagram can be applied is fundamentallyrestricted by the wavelength coverage of optical and NIR IFUs. Op-tical IFUs such as the Gemini Multi-Object Spectrograph (GMOS)and Multi Unit Spectroscopic Explorer (MUSE) can observe to amaximum wavelength of λ ∼ 900 nm, and can therefore detect [N II]and Hα to z ∼ 0.4 (lookback time of ∼4.2 Gyr), whilst the [O III]and Hβ lines will not be shifted out of the visible spectrum until z

� 0.85 (∼6.6 Gyr). In the NIR, IFUs such as NIFS, OSIRIS andSINFONI can observe to a maximum wavelength of λ ∼ 2.5 µm,and thus can detect [N II] and Hα to redshifts as high as z ∼ 2.4(∼10.9 Gyr), whilst the [O III] and Hβ lines will not be shifted outof the NIR until z � 3.4 (∼11.8 Gyr).

The utility of the [N II]/Hα versus [O III]/Hβ diagnostic diagramas a probe of starburst–AGN mixing over cosmic time is also limitedby the metallicity sensitivity of the [N II] emission line. Cosmologi-cal hydrodynamical simulations have indicated that galaxies shouldbecome more enriched over cosmic time (e.g. Kobayashi, Springel& White 2007; Dave, Finlator & Oppenheimer 2011), and obser-vations have confirmed that the mass–metallicity relation evolves

towards larger metallicities as lookback time decreases (e.g. Erbet al. 2006; Mannucci et al. 2009; Zahid, Kewley & Bresolin 2011;Yabe et al. 2012; Zahid et al. 2012, 2013a,b). The exposure timerequired for robust detection of [N II] emission in H II regions there-fore increases strongly as a function of redshift. Low-metallicityH II regions also have weak [S II] emission, and the [O I] emissionline is much weaker than both [N II] and [S II] (see e.g. Kewleyet al. 2006); ruling out the [S II]/Hα and [O I]/Hα versus [O III]/Hβ

diagnostic diagrams.Starburst–AGN mixing diagnostics requiring only emission lines

which lie bluewards of [O III] λ 5007 and are strong at low metal-licity would significantly increase the redshift range over whichstarburst–AGN mixing can be probed. The strong, low ionization[O II] λλ 3727,3729 doublet is often used as an SFR indicator in theabsence of Hα measurements (e.g. Gallagher, Hunter & Bushouse1989; Lilly et al. 1996; Kennicutt 1998; Rosa-Gonzalez, Terlevich& Terlevich 2002; Kewley, Geller & Jansen 2004). The [O II] emis-sion lines are excited by hot electrons and therefore are strongestin low-metallicity H II regions which do not have significant metalcooling (Kewley & Dopita 2002). Here, we investigate whether the[O III]/[O II] line ratio can be used in conjunction with the [O III]/Hβ

ratio to probe starburst–AGN mixing.

5.2 Extinction correction

The combination of the [O III]/[O II] and [O III]/Hβ line ratios wasfirst proposed as a diagnostic for the power sources of galax-ies by Baldwin et al. (1981). However, the wavelength separa-tion of the [O III] λ 5007 and [O II] λλ 3727,3729 lines makesthe [O III]/[O II] ratio very sensitive to interstellar extinction, andtherefore the reddening-insensitive [N II]/Hα, [S II]/Hα and [O I]/Hα

versus [O III]/Hβ diagrams have become the ‘universal’ diagnosticsfor the power sources of galaxies. We correct the [O III], [O II] andHβ emission-line fluxes for interstellar extinction by comparing theintrinsic Hα/Hβ ratio (Balmer decrement) with its measured valuein each individual spaxel (assuming the Cardelli, Clayton & Mathis1989 extinction law). The Hα and Hβ emission lines originate fromrecombination to the n = 2 level of hydrogen, and therefore the in-trinsic Hα/Hβ ratio can be accurately calculated using the relativelifetimes of the Hα (3 → 2) and Hβ (4 → 2) transitions. Assum-ing Case B recombination, the intrinsic Balmer decrement is ∼2.86(Osterbrock 1989). Collisional excitation enhances the strength ofHα relative to Hβ; causing the Balmer decrement to rise to ∼3.1 inthe presence of an AGN.

We assume that the intrinsic Balmer decrement is 2.86 in allspaxels. The validity of this assumption varies with AGN fraction;but in the worst case scenario (for spaxels with 100 per cent AGNfraction in the nuclear regions of galaxies), the corrected Hα fluxeswill be overestimated by a factor of 1.08. Deviations in the localelectron temperature and density can also introduce up to 5 per centuncertainty on the intrinsic Balmer decrement (Osterbrock 1989).Taking both effects into account, there will be a maximum of 0.06dex difference between the corrected and intrinsic log (Hα/Hβ) ra-tios. We expect similar errors on the derived log ([O III]corr/[O II]corr)ratios, given that [O III] and [O II] lie only 1000 Å bluewards ofHβ and Hα and have a smaller wavelength separation (1280 Åcompared to 1722 Å). Errors of this size are considerably smallerthan the intrinsic spread in line ratios at a single AGN fraction (seeSection 4.4) and are therefore negligible.

If the Balmer decrement is used to correct for interstellar extinc-tion, the suite of lines required for our proposed starburst–AGN

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mixing diagnostic consists of Hα, Hβ, [O III] and [O II]. This re-moves the need to observe lines which are weak at low metal-licity, but the wavelength of the Hα line still strongly restrictsthe maximum redshift to which the diagnostic can be applied.In order to alleviate this issue, the EW[O III]/EW[O II] equivalentwidth ratio may be used as a partially reddening-insensitive proxyfor the [O III]/[O II] line flux ratio. The dependence of equivalentwidth on stellar continuum strength automatically corrects the ra-tio for any reddening affecting the stars, making the equivalentwidth ratio superior over the line flux ratio when reddening cor-rections are not available (Kobulnicky & Phillips 2003; Kobul-nicky & Kewley 2004). The equivalent width ratio is related to thereddening-corrected line flux ratio by some normalization constantα; i.e. [O III]corr/[O II]corr = α(EW[O III]/EW[O II]). The size of α isdetermined by both the ratio between the reddened and intrinsic lineflux ratios (which depends on the underlying stellar population) aswell as the difference in the amount of attenuation experienced bythe ionized gas and the stars. Kobulnicky & Phillips (2003) showthat, assuming an average galaxy stellar spectrum dominated byA-type stars and G & K giants, α ∼ 0.84 ± 0.3. The average valueof log(α) therefore falls short of unity by less than 0.1 dex. Useof the equivalent width ratio also alleviates the need for flux cal-ibration, which is notoriously difficult for NIR observations. Anycalibration affects the strength of the emission lines and the stel-lar continuum equally; leaving the equivalent width measurementsunchanged (Kobulnicky & Phillips 2003).

The extinction along the line of sight can also be calculated usingalternate techniques, including higher order Balmer line ratios (e.g.Hγ λ 4341/Hβ), photometric colours or the ratio of the total infraredto UV luminosity (e.g. Buat 1992; Meurer, Heckman & Calzetti1999).

5.3 AGN fractions using [O III]/[O II] and [O III]/Hβ

We show the [O III]corr/[O II]corr ratio compared to the [O III]/Hβ ra-tio for the five galaxies in our sample (again including NGC 7130)in the top row of Fig. 7. We observe a mixing sequence for the

[O III]corr/[O II]corr versus [O III]/Hβ diagram, similar to the [N II]/Hα

versus [O III]/Hβ diagnostic diagram. We colour-code spaxels ac-cording to projected distance along the line between the spaxelswith the minimum and maximum [O III]/Hβ ratios, and use thesame colour-coding to construct maps indicating where spaxels ineach section of the mixing sequence are located (as in Fig. 2). Theposition of spaxels on the [O III]corr/[O II]corr versus [O III]/Hβ mix-ing sequence is directly related to their distance from the centre ofthe galaxy.

It is interesting to note that NGC 6762 appears to have distinctlydifferent properties from the rest of the galaxies in our sample. Nomixing sequence is visible, and there is no clear correlation betweenthe [O III]/[O II] and [O III]/Hβ ratios. Baldwin et al. (1981) showedthat H II regions fall along a tight sequence on the [O III]/[O II] ver-sus [O III]/Hβ diagram, with a strong positive correlation betweenthe two ratios. However, objects ionized by harder ionizing radi-ation fields, such as planetary nebulae, AGN activity or shocks,do not lie along this correlation. The absence of a correlation be-tween the [N II]/Hα and [O III]/Hβ ratios in NGC 6762 suggests thatyoung stars are not a significant source of ionization; consistentwith the low EWHα values observed in this object. This findinghighlights the possibility to use the [O III]/[O II] versus [O III]/Hβ

diagram as an additional tool to distinguish between galaxieswhich are ionized by a combination of active star formation andAGN activity and interlopers which are dominated by older stellarpopulations.

We apply the technique described in Section 3.3 to the[O III]corr/[O II]corr versus [O III]/Hβ mixing sequences and therebyderive a second estimate for the AGN fraction of each spaxel inNGC 7130, NGC 6394 and NGC 2410. We quantify the level ofconsistency between the [O III]/[O II] versus [O III]/Hβ and [N II]/Hα

versus [O III]/Hβ diagnostics by comparing the AGN fraction esti-mates for each spaxel individually. The distribution of the differencein AGN fractions between the two diagnostics is shown in Fig. 8.The diagnostics agree to within 0.5 per cent in 80 per cent of spax-els, 1 per cent in 91 per cent of spaxels and 2 per cent in 96 per centof spaxels, indicating remarkably good correspondence. This

Figure 7. Top: [O III]corr/[O II]corr versus [O III]/Hβ diagnostic diagrams with spaxels colour-coded by distance along the mixing sequence, and (bottom) mapsindicating where spaxels in each section of the mixing sequence are located, using the colour-coding assigned from the mixing sequences. Beige contours tracethe integrated continuum emission over the wavelength range 3750 Å < λ < 7500 Å. Left to right: NGC 7130, NGC 6394, NGC 2410, IC 0540, NGC 6762.Bars indicate the physical scale of 10 pixels on the maps. In all galaxies there is a clear relationship between the position of spaxels on the mixing sequenceand their distance from the centre of the galaxy – similar to what is found for the [N II]/Hα and [S II]/Hα versus [O III]/Hβ diagnostic diagrams.

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Figure 8. Difference in AGN fractions derived from the [N II]/Hα versus[O III]/Hβ and [O III]/[O II] versus [O III]/Hβ diagnostic diagrams, taking intoaccount all spaxels with calculated AGN fractions from NGC 7130, NGC6394 and NGC 2410. The difference is less than 2 per cent for 96 per centof spaxels, indicating very good quantitative correspondence between thediagnostics.

Table 3. Relative contribution of star formation and AGNactivity to the global [O II] luminosities of NGC 7130, NGC6394 and NGC 2410.

Galaxy Star formation (per cent) AGN (per cent)

NGC 7130 60 ± 3 40 ± 2NGC 6394 56 ± 3 44 ± 2NGC 2410 56 ± 3 44 ± 2

confirms that the [O III]/[O II] versus [O III]/Hβ diagnostic can beused as a tracer of starburst–AGN mixing at high redshifts, provideddust attenuation has been accounted for (e.g. using the techniquesdescribed in the previous section).

5.4 Enhancement of [O II] emission due to AGN activity

The [O II] emission line is commonly used as an SFR indicatorin AGN host galaxies, under the assumption that this line is onlyweakly enhanced in the presence of an AGN (Ferland & Oster-brock 1986; Ho et al. 1993a; Ho, Filippenko & Sargent 1993b; Ho2005; Kim, Ho & Im 2006; Silverman et al. 2009). In order to testthis assumption, we calculate the relative contribution of the starformation and the AGN activity to the global [O II] luminosities ofNGC 7130, NGC 6394 and NGC 2410, using the technique out-lined in Section 3.3. The results can be found in Table 3. We haveassumed the relative error on AGN fractions calculated from the[O III]/[O II] versus [O III]/Hβ diagnostic to be the same as the erroron those calculated from the [N II]/Hα versus [O III]/Hβ diagnostic.

The AGN is responsible for exciting approximately 40 per cent ofthe global [O II] emission in all three galaxies, which is 10 per centhigher than the average contribution of the AGN to the Hα emissionin the same galaxies. We therefore do not recommend the use of un-corrected global [O II] luminosities to estimate the SFR of a galaxy.Instead, we recommend the use of integral field spectroscopy toremove the AGN contribution before the SFR is calculated.

6 C O N C L U S I O N S

We have analysed the relationship between star formation and AGNactivity as a function of radius in four AGN host galaxies usingoptical IFU data from the CALIFA survey. We construct maps ofthe spaxels in each galaxy for which all of the BPT strong lines aredetected at the 3σ level, colour-coded by distance of the spaxelsalong the starburst–AGN mixing sequence on the [N II]/Hα versus[O III]/Hβ diagnostic diagram. We observe clear rings of gas ionizedwith decreasing contributions from the AGN as radius increases.

We have numerically calibrated the starburst–AGN mixing se-quences to calculate the fractional contribution of the star formationand the AGN activity to the line emission of each spaxel in eachgalaxy. We find that the star formation and the AGN are each re-sponsible for at least 25 per cent of the global Hα, [O II] and [O III]luminosities in all galaxies – highlighting the need to correct forany AGN contribution when calculating SFRs using Hα or [O II].

We have constructed theoretical starburst–AGN mixing lines us-ing weighted combinations of HII region and AGN NLR nebularemission spectra. We have shown that these models are consistentwith observations for an average of 85 per cent of spaxels across allgalaxies, and are able to reproduce the slope and shape of observedmixing sequences. This agreement highlights the potential to usestarburst–AGN mixing models to constrain the ionization parame-ter, metallicity and hardness of the AGN ionizing radiation field inAGN host galaxies.

We have shown that the [O III]/[O II] versus [O III]/Hβ diagramprovides an alternate diagnostic to the [N II]/Hα versus [O III]/Hβ

diagram for calculating AGN fractions. We anticipate that the[O III]/[O II] versus [O III]/Hβ diagram will be useful for separat-ing starburst and AGN activity to high redshifts (z � 2.5).

Many IFU surveys are currently underway (including SAMI,CALIFA, S7, MaNGA and HETDEX) and many more integralfield spectrographs will be coming online in the near future (includ-ing the Multi Unit Spectroscopic Explorer (MUSE) for the VLT(Bacon et al. 2010), the Keck Cosmic Web Imager (KCWI; Mar-tin et al. 2010) and the Giant Magellan Telescope Integral FieldSpectrograph (GMTIFS; McGregor et al. 2012) to survey galaxiesboth locally and at high redshift. These instruments will providestatistically significant samples of IFU data to investigate the rela-tionship between star formation and AGN activity across cosmictime. The techniques demonstrated in this paper provide just one ofthe first stepping stones towards using these unique data sets to gaina greater understanding of how black holes and their host galaxieshave evolved over the history of the Universe.

AC K N OW L E D G E M E N T S

We would like to thank the anonymous referee whose commentsand suggestions facilitated significant improvement of this paper.LJK and MAD acknowledge the support of the Australian Re-search Council (ARC) through Discovery project DP130103925.MAD acknowledges financial support received under the KAUHiCi programme. This research has made use of the data providedby the Calar Alto Legacy Integral Field Area (CALIFA) survey(http://califa.caha.es/). Based on observations collected at the Cen-tro Astronomico Hispano Aleman (CAHA) at Calar Alto, operatedjointly by the Max-Planck-Institut fur Astronomie and the Institutode Astrofisica de Andalucia (CSIC). This research has made useof the NASA/IPAC Extragalactic Database (NED) which is oper-ated by the Jet Propulsion Laboratory, California Institute of Tech-nology, under contract with the National Aeronautics and Space

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Administration. We also acknowledge the usage of the HyperLedaDatabase (http://leda.univ-lyon1.fr; Paturel et al. 2003) and AladinSky Atlas (Bonnarel et al. 2000).

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