# CLEAR: Spatially Resolved Emission Lines and Active Galactic Nuclei at
$0.6<z<1.3$

Bren E. Backhaus Department of Physics, 196 Auditorium Road, Unit 3046,
University of Connecticut, Storrs, CT 06269  Joanna S. Bridge Department of
Physics and Astronomy, 102 Natural Science Building, University of Louisville,
Louisville, KY 40292  Jonathan R. Trump Department of Physics, 196 Auditorium
Road, Unit 3046, University of Connecticut, Storrs, CT 06269  Nikko J. Cleri
Department of Physics and Astronomy, Texas A&M University, College Station, TX
77843-4242  George P. and Cynthia Woods Mitchell Institute for Fundamental
Physics and Astronomy, Texas A&M University, College Station, TX 77843-4242
Department of Physics, 196 Auditorium Road, Unit 3046, University of
Connecticut, Storrs, CT 06269  Casey Papovich Department of Physics and
Astronomy, Texas A&M University, College Station, TX 77843-4242  George P. and
Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, Texas
A&M University, College Station, TX 77843-4242  Raymond C. Simons Space
Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD, 21218 USA
Ivelina Momcheva Space Telescope Science Institute, 3700 San Martin Drive,
Baltimore, MD, 21218 USA  Max-Planck-Institut für Astronomie, Königstuhl 17,
D-69117 Heidelberg, Germany  Benne W. Holwerda Department of Physics and
Astronomy, 102 Natural Science Building, University of Louisville, Louisville,
KY 40292  Zhiyuan Ji University of Massachusetts Amherst, 710 North Pleasant
Street, Amherst, MA 01003-9305, USA  Intae Jung Astrophysics Science Division,
Goddard Space Flight Center, Greenbelt, MD 20771  Jasleen Matharu Department
of Physics and Astronomy, Texas A&M University, College Station, TX 77843-4242
George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and
Astronomy, Texas A&M University, College Station, TX 77843-4242

###### Abstract

We investigate spatially-resolved emission-line ratios in a sample of 219
galaxies ($0.6<z<1.3$) detected using the G102 grism on the _Hubble Space
Telescope_ Wide Field Camera 3, taken as part of the CANDELS Ly$\alpha$
Emission at Reionization (CLEAR) survey, to measure ionization profiles and
search for low-luminosity active galactic nuclei (AGN). We analyze [Oiii] and
H$\beta$ emission-line maps, enabling us to spatially resolve the
$\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ emission-
line ratio across the galaxies in the sample. We compare the [Oiii]/H$\beta$
ratio in galaxy centers and outer annular regions to measure ionization
gradients and investigate the potential of sources with nuclear ionization to
host AGN. We investigate some of the individual galaxies that are candidates
to host strong nuclear ionization and find that they often have low stellar
mass and are undetected in X-rays, as expected for low-luminosity AGN in low-
mass galaxies. We do not find evidence for a significant population of off-
nuclear AGN or other clumps of off-nuclear ionization. We model the observed
distribution of [Oiii]/H$\beta$ gradients and find that most galaxies are
consistent with small or zero gradients, but 6-16% of galaxies in the sample
are likely to host nuclear [Oiii]/H$\beta$ that is $\sim$0.5 dex higher than
in their outer regions. This study is limited by large uncertainties in most
of the measured [Oiii]/H$\beta$ spatial profiles, therefore deeper data, e.g,
from deeper HST/WFC3 programs or from JWST/NIRISS, are needed to more reliably
measure the spatially resolved emission-line conditions of individual high-
redshift galaxies.

Active galaxies – emission line galaxies – Galaxies

††facilities: HST (WFC3)††software: AstroPy (Astropy Collaboration et al.,
2013), Matplotlib (Hunter, 2007), NumPy (van der Walt et al., 2011), SciPy
(Jones et al., 2001), grizli (Brammer, 2022), eazy-py (Brammer et al., 2008;
Brammer, 2021), FSPS (Conroy & Gunn, 2010)

##  1 Introduction

The rest-frame optical spectra of galaxies can be used to infer a wide variety
of physical properties via their nebular and recombination lines to determine,
for example, star formation rate (SFR; e.g., Kennicutt, 1998; Kennicutt &
Evans, 2012), metallicity (e.g., Pagel & Edmunds, 1981; Zahid et al., 2013;
Maiolino & Mannucci, 2019), interstellar medium (ISM) density (Kewley et al.,
2019), temperature (e.g., Peimbert et al., 2017), and dust attenuation (e.g.,
Cardelli et al., 1989; Calzetti, 2001). Additionally, emission-line ratios
have been used to identify active galactic nuclei (AGN), such as the
$\hbox{{\rm[N}\kern 1.00006pt{\sc ii}{\rm]}}/\hbox{{\rm H}$\alpha$}$ and
$\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ ratios
used in “BPT”111Baldwin, Phillips, and Terlevich diagram (Baldwin et al.,
1981; Veilleux & Osterbrock, 1987; Kewley et al., 2001; Kauffmann et al.,
2003), Mass-Excitation (MEx) diagram (Juneau et al., 2011), and the OIII/Hb vs
NeIII/OII (OHNO) “OHNO” diagram (Backhaus et al., 2022). Narrow-line AGN
selection methods are particularly important because they are complementary to
multi-wavelength AGN selections: different methods have different biases as a
function of host galaxy properties and/or AGN Eddington ratio (Hickox et al.,
2009; Buchner et al., 2015; Aird et al., 2012; Jones et al., 2016; Cann et
al., 2019; Trump et al., 2013; Ji et al., 2022; Lambrides et al., 2020; Trump
et al., 2015).

Determining the physical conditions of galaxies around the peak of cosmic star
formation ($z\sim 2$) is complicated. At these redshifts, optical diagnostic
lines such as [Oiii]$\lambda$5007+$\lambda$4959 and H$\alpha$ are redshifted
into the infrared, where atmospheric opacity and high background make ground-
based observations challenging. Additionally, interpreting BPT diagrams at
higher redshifts is complicated by higher star formation rates (Madau &
Dickinson, 2014) and harder ionizing radiation (Kewley et al., 2015; Steidel
et al., 2014), making it difficult to distinguish ionization from an AGN and
from high-redshift star formation processes (Moran et al., 2002; Trump et al.,
2015; Coil et al., 2015). This is especially true in low-mass galaxies where
X-ray detection of AGN is unlikely (Xue et al., 2010; Aird et al., 2012).

Spatially resolved lines can be used to gather further information on galaxy
evolution and formation. Spatially resolving H$\alpha$ gives the profile of
star formation within a galaxy. This gives us information whether a galaxy is
formed inside-out or outside-in by comparing to the galaxy’s stellar continuum
(Nelson et al., 2012, 2016a, 2021; Matharu et al., 2022). Spatially resolving
the Balmer decrement (H$\alpha$/H$\beta$) measures the profile of dust
attenuation within a galaxy. In low-mass galaxies at the redshifts $z\sim 1.4$
the dust attenuation gradients have been measured to be relatively flat on
average (Nelson et al., 2016b). As mass increases, dust attenuation increases
toward the center of the galaxy (Nelson et al., 2016b).

Spatially resolving the [Oiii]/H$\beta$ line ratio has shown promise for
decomposing nuclear AGN and extended star formation activity. Trump et al.
(2011); Wright et al. (2010) examined stacked WFC3/G141 grism spectra and
found that elevated central [Oiii]/H$\beta$ ratios may indicate the presence
of obscured or dim AGN. Using simulations of 2-orbit WFC3/G141 grism
observations, Bridge et al. (2016) showed that it is possible to detect low-
luminosity AGN in individual galaxies, particularly in low-mass galaxies, by
spatially resolving the [Oiii]/H$\beta$ line ratio in the inner and outer
regions of the galaxy using the G141 spectrum. That study made use of the
Mass-Excitation (MEx) diagnostic diagram (Juneau et al., 2011, 2014) in order
to distinguish between AGN and star formation activity. The MEx diagram
replaces the [NII]/H$\alpha$ axis of the traditional BPT diagram with stellar
mass. The mass-metallicity relation has shown that there is a correlation
between mass and [NII]/H$\alpha$ (e.g., Tremonti et al., 2004), facilitating
the use of this diagnostic even when the [NII] and H$\alpha$ lines are not
available.

In order to address the challenges of understanding high-redshift emission-
line galaxies, the Wide Field Camera 3 (WFC3; Kimble et al., 2008) G102
($0.8<\lambda<1.15~{}\mu$m, $R\sim 210$) and G141 ($1.1<\lambda<1.7~{}\mu$m,
$R\sim 130$) slitless grisms on the _Hubble Space Telescope_ (_HST_) have been
used to conduct large surveys of thousands of galaxies in the near infrared
regime. These surveys have expanded our understanding of physical conditions
of galaxies since cosmic noon [e.g., the 3D-HST (Momcheva et al., 2016) and
Faint Infrared Grism Survey (FIGS; Pirzkal et al. 2017) surveys]

In this work we investigate the spatially resolved [Oiii]/H$\beta$ emission-
line profiles of 219 galaxies at redshift $z\sim 0.9$ observed by the CLEAR
survey. We use the spatially resolved emission-line ratios to infer the
ionization profiles of the galaxies and particularly search for nuclear
ionization in low-mass galaxies in order to identify low-luminosity AGN that
are typically missed by X-ray detection. We also compare galaxy ionization
profiles to other galaxy properties such as stellar mass, star formation rate,
effective radius, and redshift.

In Section 2, we describe the data observations and reduction. In Section 3,
we explain our sample selection, and in Section 4 we discuss our method for
spatially resolving the [Oiii]/H$\beta$ line ratio. Section 5 describes how
the spatially resolved [Oiii]/H$\beta$ emission-line relates to different
galaxy properties. We discuss the spatially resolved [Oiii]/H$\beta$ś ability
to detect low luminosity AGN and regions of higher ionization in Section 6. We
present our conclusions in Section 7. Throughout this paper, we assume a
$\Lambda$CDM cosmology with $H_{0}=70$ km s-1 Mpc-1, $\Omega_{m}=0.3$, and
$\Omega_{\Lambda}=0.7$ (Planck Collaboration et al., 2016) .

##  2 Observations and Data Reduction

The data used in this work is comprised of _HST_ /WFC3 G102 grism
$(0.8<\lambda<1.15~{}\mu$m) observations from various surveys, the majority of
which was taken as part of the CANDELS Ly$\alpha$ Emission at Reionization
(CLEAR; Estrada-Carpenter et al., 2019) G102 grism survey. The G102
observations come from programs GO-14227 (PI: C. Papovich), GO-13420 (PI: G.
Barro), and GO/DD-11359 (‘ERS’, PI: R. O’Connell). The _HST_ /WFC3 also has
G141 observations which come from programs GO-11600 (‘AGHAST’; PI: B. Weiner),
GO-12461 (‘SN Colfax’, PI: A. Reiss), GO-13871 (PI: P. Oesch), GO/DD-11359
(‘ERS’, PI: R. O’Connell), GO12099 (‘George, Primo’, PI: A. Reiss), and
GO-12177 (‘3D-HST’, PI: van Dokkum). CLEAR includes six pointings in the
CANDELS (Koekemoer et al., 2011) Great Observatories Origin Deep survey
(GOODS)-North (GN) field with 10 orbit depth and six pointings in the GOODS-
South (GS) field with 12 orbit depth. These datasets provide low-resolution
grism spectroscopy over observed-frame $0.8<\lambda<1.65$ µm for every source
in the field of view, with $R\sim 210$ in G102. The CLEAR pointings overlap
with the 3D-HST survey (Momcheva et al., 2016), which gives G141 slitless
grism spectra covering $1.1-1.65$ µm with a 2-orbit depth which were used in
the data reduction to aid in redshift determination. In contrast to the low
spectral resolution, the two-dimensional spectra have high spatial resolution
of $0\farcs 06$ per pixel.

The CLEAR survey is augmented by G102 observations from the Faint Infrared
Grism Survey (FIGS; HST-GO 13776, PI Malhotra). The FIGS campaign is comprised
of four pointings of 40-orbit observations in the GOODS fields (see Tilvi et
al., 2016), one of which overlaps with a CLEAR pointing in GOODS-S. This
pointing was therefore also ingested into the CLEAR data. The FIGS data were
reduced and processed in the same fashion as the CLEAR data (Section 2.2).

The CLEAR spectra have been used to study the metallicities, ages, and
formation histories of massive high-redshift galaxies (Estrada-Carpenter et
al. 2019, 2020; Simons et al. 2021), and to appraise Paschen-$\beta$ as a
star-formation rate indicator in low-redshift galaxies (Cleri et al., 2022).
Matharu et al. (2022) used spatially resolved H-alpha emission line maps of
star-forming galaxies to study the evolution of gradients in galaxy assembly.
Jung et al. (2021) used CLEAR to study the evolution of the strength of Lyman
Alpha emission at 6.5<z<8.2. Backhaus et al. (2022) and Papovich et al. (2022)
used CLEAR spectra to study the physical conditions of galaxies and their
(spatially integrated) gas conditions.

###  2.1 CLEAR Observing Strategy

The CLEAR observations were taken over the course of two years (November 2015
to February 2017). Direct imaging observations were done using the WFC3 F105W
filter. Each field was observed with three different orients, four orbits for
each orient in GS and GN has two four orbit orients with a single two orbit
orient, separated by $\sim 10-20$ degrees in roll angle to facilitate the
separation of overlapping spectra.

The Earth’s atmosphere produces a time-variable background caused by Hei
emission at $10830$ Å that affects both the F105W filter and the G102 grism.
The observations were scheduled to reduce this background by placing the G102
grism observations during times of low background and the F105W observations
when the background is predicted to be higher in order to minimize the
background in the spectra (see Brammer et al. 2014; Tilvi et al. 2016; Lotz et
al. 2017 for further information.)

###  2.2 Spectroscopic Data Reduction

The G102 grism data from all the surveys were reduced together using the grism
redshift & line analysis software grizli (Brammer, 2022). The complete
reductions are described in detail in (Simons et al., 2021), but we describe
the process briefly here. CLEAR F105W reference images and dispersed G102
grism were aligned to the same world coordinate system (WCS) as 3DHST
photometric catalog (Skelton et al., 2014). Cosmic ray cleaning, flat-
fielding, and sky subtraction (using WFC3/IR master sky images, Brammer et
al., 2015) was then performed.

Contamination from overlapping spectra is a known issue in grism spectroscopy.
It is more significant for faint sources contaminated by bright ones because
subtracting bright sources from faint spectra introduces errors and
contributes residual flux to the spectra of faint sources. The continuum model
of these overlapping sources are subtracted from object spectra. The
contamination of the 2D spectra was modeled in two steps. First, a flat
continuum model was used for objects down to $m_{\textrm{F105W}}<25$.
Subsequently, a polynomial continuum was used for objects with
$m_{\textrm{F105W}}<24$. All objects with $m_{\textrm{F105W}}<25$ were then
extracted from the CLEAR imaging, with 2D spectral extractions for each grism
observation, for about 6000 extracted objects.

Figure 1: Left: The distribution of stellar mass and H$\beta$ SFR from our
selected sample of CLEAR galaxies between $0.6<z<1.3$, color-coded by
redshift, compared to the complete CLEAR data set between $0.6<z<1.3$ (grey
points). Our sample contains about 31% of the CLEAR galaxies at this redshift.
The red line is the star formation mass sequence from Whitaker et al. (2012)
shown in Equation 1. Right: The distribution of redshifts from our selected
sample of CLEAR galaxies between $0.6<z<1.3$ (blue points) compared to the
complete CLEAR data set between $0.6<z<1.3$ (grey points).

Fits to the spectra were carried out with grizli using the CLEAR F105W images
as well as the photometry available from 3D-HST (Skelton et al., 2014). In
order to determine the redshift of each object, Flexible Stellar Population
Synthesis (FSPS) stellar population models (Conroy & Gunn, 2010) were used
with fixed emission line sets and ratios. Line fluxes were then determined
using the best-fit redshift.

The grizli software creates spatially resolved emission-line maps by fitting a
model to the 2D spectrum of the object of interest, and subtracting the
continuum. The line maps for each emission line present in the spectrum are
then created by drizzling the best-fit galaxy model at the wavelength of each
emission line in the spectrum. This results in a 2D map with a pixel scale of
$0.1\times 0.1$ arcsec of the flux that is in excess of the continuum at each
line wavelength.

##  3 Sample selection

The final CLEAR catalog (Simons et al. in prep) contains the 1D and 2D
spectra, total (integrated) line fluxes, and emission-line maps of more than
6000 objects. We implemented a cut in the grism redshift fits to require
$(z_{97}-z_{02})/2<0.005$ to ensure robust line identification, where $z_{97}$
and $z_{02}$ are the 97 and 2 percentiles of the redshift probability
distribution produced by grizli for each object.

We focus on the [Oiii]/H$\beta$ ratio (with air wavelengths of 5007 and 4861
Å, respectively) that is ideal for detection with the G102 grism. This ratio
has been identified as a tracer of AGN activity (e.g., Baldwin et al., 1981;
Juneau et al., 2014; Bridge et al., 2016) because a high [Oiii]/H$\beta$ ratio
indicates the presence of the harder ionizing radiation necessary to produce
[Oiii] oxygen (Kewley et al., 2015). Additionally, the fact that the [Oiii]
doublet and H$\beta$ are close in wavelength makes their ratio nearly
independent of extinction. Requiring multiple line pairs (such as
[NeIII]/[OII] or [SII]/$H\alpha$) would significantly reduce the redshift
range and sample size.

Figure 2: The upper and lower panels show examples of a large and small galaxy
and their outer-aperture regions. _Top:_ A small galaxies with $R_{50}<2\farcs
5$ with an outer-aperture region of 20 pixels shown as boxes. _Bottom:_ A
large galaxy with $R_{50}>2\farcs 5$ with an outer-aperture region of 28
pixels shown as boxes. _Left_ : The F105W direct images. _Center_ : The [Oiii]
emission-line maps. _Right_ : The $H\beta$ emission-line maps. The pixel scale
is $0\farcs 1$ in all panels, corresponding to $\sim$1 kpc at the redshift of
these galaxies. The center of these galaxies is the F105W centroid.

We then use the integrated [Oiii] and H$\beta$ line fluxes (total fluxes
integrated across a whole galaxy) to impose a signal-to-noise cut on the
[Oiii]/H$\beta$ emission line ratio of
S/N${}_{\textrm{[O~{}III]/H}\beta}>3/\sqrt{2}$, the low end of which is
equivalent to both lines being measured at exactly $3\sigma$. Implementing a
signal-to-noise cut on the ratio ensures that either [Oiii] _or_ H$\beta$ are
measured by at least 3$\sigma$, but allows for the inclusion of objects where
one line may be less well-measured than the other. The resulting sample is
almost 30% larger than that generated by a traditional ${\rm S/N}>3$ cut on
the [Oiii] line flux measurement.

Finally, we examine both the 1D spectra and 2D emission-line maps by eye to
ensure a robust sample of galaxies with well-determined [Oiii]/H$\beta$
ratios. In some cases, errors in the continuum model leave unphysical
artifacts in the emission-line maps. We remove these objects from the sample
to include only those with well-fit continua. This removes $\sim 28\%$ of our
sample leaving our final sample to contain 219 emission-line objects. The
H$\beta$ SFR and stellar mass distribution of our sample compared to the
entire CLEAR sample at $0.6<z<1.3$ is shown in Figure 1. This SFR is corrected
for dust attenuation using the $\hbox{{\rm H}$\alpha$}/\hbox{{\rm H}$\beta$}$
ratio.

The star formation mass sequence line is from Whitaker et al. (2012) using the
sample’s average redshift of $z=1.0$:

$\begin{split}\log({\rm
SFR})[M_{\odot}/\mathrm{yr}]=\alpha(z)(\log(M_{*})-10.5)+\beta(z)\\\
\alpha(z)=(0.7-0.13z)\\\ \beta(z)=0.38+1.14z-0.19z^{2}\end{split}$ (1)

###  3.1 Stellar Masses

Following the method of Estrada-Carpenter et al. (2019), the stellar masses
were determined using eazy-py (Brammer, 2021), a spectral energy distribution
(SED) fitting package based on the photometric redshift fitting code EAZY
(Brammer et al., 2008). The algorithm uses 12 FSPS templates, each with their
own unique star formation history. The templates all use a Chabrier initial
mass function (Chabrier, 2003).

###  3.2 X-ray Counterparts

We matched objects in our sample with known X-ray-emitting counterparts in the
Chandra Deep Fields using the the 2-Ms CDF-N (Xue et al., 2016) and 7-Ms CDF-S
(Luo et al., 2017) point-source catalogs. Any galaxy from the CLEAR sample
that corresponds to an optical counterpart in the X-ray source catalogs within
0$\farcs$5 is considered an X-ray object. Two counterparts were classified as
X-ray galaxies (i.e., X-ray emission consistent with X-ray binaries and other
processes associated with star formation) and 11 objects were classified as
X-ray AGN. These classifications were made based on the strength and hardness
of the galaxies’ X-ray flux (see Xue et al. 2016 and Luo et al. 2017 for
details).

Table 1: Sample  ID | Global Ratio | Inner Ratio | Outer Ratio | $\log(M_{\star}/M_{\odot})$ | $z$ | log(SFR) | $R_{50}$
---|---|---|---|---|---|---|---
$GN1\\_36795$ | $4.42\pm 1.14$ | $1.74\pm 1.45$ | $1.99\pm 0.93$ | 9.87 | 1.22 | 1.58 | 0.39
$GN1\\_38027$ | $2.50\pm 0.69$ | $1.00\pm 0.50$ | $2.06\pm 2.14$ | 9.39 | 0.98 | 0.18 | 0.27
$GN1\\_37494$ | $2.31\pm 0.55$ | $0.69\pm 0.51$ | $1.08\pm 0.29$ | 9.54 | 1.02 | 0.59 | 0.52
$GN1\\_37031$ | $0.84\pm 0.15$ | $0.32\pm 0.24$ | $0.28\pm 0.31$ | 9.76 | 1.06 | 1.08 | 0.58
$GN1\\_37567$ | $2.88\pm 0.40$ | $3.05\pm 1.21$ | $7.80\pm 7.55$ | 9.63 | 1.18 | 0.96 | 0.29
$GN1\\_37812$ | $2.08\pm 0.84$ | $0.70\pm 0.74$ | $0.72\pm 0.50$ | 9.72 | 0.78 | 1.20 | 0.55
$GN1\\_37691$ | $4.46\pm 1.15$ | $0.84\pm 0.59$ | $3.12\pm 1.93$ | 9.49 | 1.15 | 0.47 | 0.40
$GN1\\_37700$ | $1.65\pm 0.40$ | $1.37\pm 0.47$ | $1.09\pm 0.67$ | 9.88 | 1.04 | 0.84 | 0.15
$GN1\\_37053$ | $1.44\pm 0.23$ | $2.74\pm 2.89$ | $1.17\pm 0.42$ | 8.87 | 1.04 | 0.74 | 0.32
$GN1\\_37750$ | $12.21\pm 4.00$ | $6.03\pm 1.56$ | $3.55\pm 1.56$ | 8.43 | 1.23 | 0.66 | 0.05
Table 1: The [Oiii]/H$\beta$ ratios for the galaxies in the sample, measured from the global profile (e.g., integrated over the whole galaxy), in the inner central pixel, and in the outer aperture. Other columns indicate the stellar mass, redshift, SFR and effective radius of the galaxies. Only a portion of this table is shown here to demonstrate its form and content. A machine-readable version of the full table is available. Table 3: Binned Data  $\log(M_{\star}/M_{\odot})$ | $\log(M_{\star}/M_{\odot})_{Med}$ | $\log(SFR)_{Med}$ | $N_{gal}$ | Global Ratio | Inner Ratio | Outer Ratio | Gradient
---|---|---|---|---|---|---|---
8.34-8.99 | 8.79 | -0.01 | 21 | 0.60$\pm$0.01 | 0.51 $\pm$0.02 | 0.33$\pm$0.05 | 0.18$\pm$0.06
8.86 | 0.59 | 22 | 0.67$\pm$0.01 | 0.64 $\pm$0.04 | 0.39$\pm$0.05 | 0.25 $\pm$0.07
9.00-9.34 | 9.18 | 0.28 | 21 | 0.64$\pm$0.02 | 0.56$\pm$0.05 | 0.46 $\pm$0.07 | 0.09 $\pm$0.08
9.20 | 0.77 | 22 | 0.62 $\pm$0.01 | 0.40 $\pm$0.05 | 0.48 $\pm$0.07 | -0.08 $\pm$0.08
9.36-9.58 | 9.42 | 0.33 | 22 | 00.54$\pm$0.02 | 0.26$\pm$0.03 | 0.36$\pm$0.04 | -0.10$\pm$0.05
9.49 | 0.86 | 23 | 0.55$\pm$0.01 | 0.28 $\pm$0.05 | 0.32$\pm$0.05 | -0.05$\pm$0.07
9.59-9.79 | 9.69 | 0.59 | 22 | 0.34 $\pm$0.02 | 0.15$\pm$0.07 | 0.20$\pm$0.06 | -0.04$\pm$0.09
9.66 | 1.21 | 22 | 0.49 $\pm$0.01 | 0.33$\pm$0.02 | 0.29$\pm$0.04 | 0.03$\pm$0.05
9.82-10.99 | 9.96 | 0.94 | 22 | 0.29$\pm$0.02 | -0.00 $\pm$0.03 | 0.19 $\pm$0.04 | -0.19 $\pm$0.05
10.33 | 1.95 | 22 | 0.31$\pm$0.02 | 0.16 $\pm$0.03 | 0.18 $\pm$0.04 | -0.02$\pm$0.05
Table 2: Median [Oiii]/H$\beta$ emission-line ratios for galaxies in bins of
stellar mass and SFR. We first break our data into five stellar mass bins, and
we use the median SFR of the mass bin to create two sub-bins representing high
and low SFRs. The uncertainty of the median is given for the ratio and
gradient measurements. The low (high) SFR bins are depicted as stars
(hexagons) in Figures 5, 6, and 10.

##  4 Spatially Resolved Line Ratios

Figure 3: Distribution of the inner minus the outer [Oiii]/H$\beta$ ratio. The
solid histogram represents the distribution of galaxies that have well-
measured [Oiii] and H$\beta$ fluxes in both their central pixel and outer
aperture. The open histogram represents the distribution of the entire sample
including galaxies that have an upper limit in one or more of the central or
outer [Oiii] or H$\beta$ fluxes. The median gradient is 0.0147 and standard
deviation is 0.3428, and most galaxies have a gradient that is consistent with
zero. Figure 4: Distribution of the uncertainty in the inner minus the outer
[Oiii]/H$\beta$ ratio. The solid histogram represents the distribution of
galaxies that have well-measured [Oiii] and H$\beta$ fluxes in both their
central pixel and outer aperture. The open histogram represents the
distribution of the entire sample including galaxies using a limit of [Oiii]
or H$\beta$. As expected,galaxies with well-measured fluxes have smaller
uncertainties. In general most of the line-ratios have large uncertainties
compared to the measurement.

We use the 2D line maps to measure the spatially-resolved emission lines from
each galaxy. We are specifically interested in the [Oiii]/H$\beta$ line ratio,
and we use the line maps (examples of which are shown in Figure 2) to measure
differences in the ratios across the spatial profile of each galaxy. We begin
by defining the “center” of the galaxies, i.e., where we expect to find a
central AGN, to be the middle of the pixel of the photometric centroid of the
F105W image. The pixel scale of both the images and the 2D grism spectra is
0$\farcs$1/pixel, which for the redshift range of this sample corresponds to
approximately 1 kpc/pixel. This resolution is sufficient such that the
ionization from a central AGN can be spatially distinguished from the more
extended emission associated with distributed star formation.

In order to characterize the emission lines from the extended star-forming
region of the galaxy, we define an outer aperture region outside of the
central pixel. The number of pixels chosen depends on the size of the galaxy
as determined from the half-light radii ($R_{50}$) from the F125W CANDELS
images (van der Wel et al., 2014). For galaxies with $R_{50}>$ 2$\farcs$5, we
selected a set of 28 pixels symmetrically around the center pixel from the
extended regions of the galaxy. Smaller galaxies use a similar shape but
slightly smaller and with only 20 pixels. In both cases we leave a gap of at
least one pixel between the central pixel and the extended region in order to
minimize blending between the regions of emission and avoid correlated fluxes
from neighboring pixels in the drizzled WFC3 data. The geometry of the
extended region pixel selection from larger and compact objects is
demonstrated in Figure 2.

The extended [Oiii]/H$\beta$ ratio is calculated as the median [Oiii]/H$\beta$
ratios in the outer aperture. We choose the median as a statistically robust
measure of the extended emission-line flux, since many galaxies contain pixels
with lower signal-to-noise measurements and/or outlier flux caused by
contamination. Use of the median allows the outlier pixels to be ignored in
the aperture measurement for the galaxy. We also calculated the outer-aperture
emission-line flux using the mean, weighted mean, weighted mean with outlier
rejection, and weighted median. These other methods generally resulted in
similar flux values but tended to be more affected by outliers or had larger
uncertainties than using the simple median.

Our samples integrated, inner aperture, and outer aperture ratio measurements
are shown in Table 1 along with the galaxies stellar mass, redshift, SFR, and
effective radius.

###  4.1 Binned Line Ratio Profiles

Of our sample of 219 galaxies, 113 of them have at least one limit in a flux
measurement from the inner or outer regions, usually from the H$\beta$
emission line, resulting in a limit in the [Oiii]/H$\beta$gradient. We
mitigate the large uncertainties and limits of individual galaxies by putting
our sample, including galaxies with limits in their emission lines, into five
bins based on their stellar mass, with each bin containing about 43-45
galaxies. We then split each mass bin into two sub-bins of high and low
H$\beta$ star formation rates using the median H$\beta$ SFR of each bin,
giving us a total of 10 bins with $22\pm 1$ galaxies in each.

We then calculate the median stellar mass and SFR of each bin. The
$\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ gradient
for each bin is created by taking the median emission-line fluxes from both
apertures to create the ratios. The median mass, SFR, emission-line ratios,
and gradient for each bin is shown in Table 2.

##  5 Results

We define the “$\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$}$ gradient” as the difference between the $\log(\hbox{{\rm[O}\kern
1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$})$ ratio in the inner pixel
minus the ratio in the outer region. Figures 3 and 4 show the distributions of
the $\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$
gradient and $\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$}$ gradient uncertainty, respectively. In these diagrams the solid
blue histogram is the distribution of galaxies with well-measured emission-
line fluxes in both the inner and outer apertures. The open blue histogram is
the distribution of the entire sample, including galaxies with limits in at
least one emission-line flux.

Figure 3 shows most of the objects have measured [Oiii]/H$\beta$ gradients
close to zero, although there is large scatter. Much of this scatter is likely
due to the large gradient uncertainties seen in Figure 4: only 29 galaxies,
$13\%$ of the sample, have a gradient uncertainty less than 0.3 dex. The
median uncertainty for the entire sample is 0.5 dex (open histogram), with a
median gradient uncertainty of 0.38 dex for the well-measured sample of
galaxies with no limits in inner/outer emission-line fluxes (solid blue
histogram).

###  5.1 General Emission-Line Ratio Properties

Figure 5: The MEx diagram of the galaxies in our sample. The integrated
[Oiii]/H$\beta$ ratios are given on the vertical axis, and the points are
shaded by the inner minus the outer [Oiii]/H$\beta$ ratio. Left: Galaxies with
well-measured gradient in both inner and outer apertures. Right: Galaxies with
limits in an emission-line flux in the inner and/or outer regions. The arrows
indicate an upper or lower limit in the _ratio gradient_. The black circles
are galaxies that have limits in both the inner and outer regions and are
statistically unconstrained. The stars and hexagons in both panels are the
ratios of the galaxies binned by mass and SFR described in Table 2, each pair
of low and high SFR for a certain mass is connected by a black arrow. The
objects identified via X-rays are shown with open squares (AGN) and diamonds
(galaxies). The black dashed line represents the empirical division between
star-forming galaxies (below the line) and galaxies with AGN (above the line)
for galaxies at this redshift (Juneau et al., 2014). Galaxies with lower
stellar mass tend to have higher integrated $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ ratio and also tend to have a higher inner
$\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ ratio.

We place the final sample of galaxies on a Mass-Excitation (MEx) diagram using
the Juneau et al. (2014) AGN/SF line shown in Figure 5, with all the well-
measured galaxies in the left panel and the galaxies with limits in their
inner minus outer $\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$}$ in the right panel. The median uncertainty in the integrated
emission-line ratio is also shown in the lower left corner. Also shown are the
objects in the sample that are X-ray sources and with X-ray emission
classified as coming from AGN or star-forming galaxies (Luo et al., 2017; Xue
et al., 2016). The triangles in the right panel represent upper or lower
limits for the [Oiii]/H$\beta$  _gradient_ as shown by the color bar. The
black filled circles in the right hand panel are galaxies that have the same
type of limit in both the inner and outer regions making the gradient
unconstrained. The stars and hexagons are the ratios of the galaxies binned by
mass and SFR described in Table 2.

Figure 5 shows that low-mass galaxies prefer higher $\hbox{{\rm[O}\kern
1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ in their nucleus. This will
be further investigated in Section 5.2. The binned medians show no significant
difference in the gradient between the high and low SFRs. The bins, similar to
individual galaxies, indicate that low stellar mass galaxies marginally prefer
nuclear ionization, while high stellar mass galaxies have neutral or slightly
off-nuclear ionization.

X-ray AGN are identified in massive galaxies, due to the well-known stellar
mass bias for X-ray detection (Aird et al., 2012). The most luminous known
X-ray AGN do not have large [Oiii]/H$\beta$ gradients, as the AGN in these
galaxies are likely so bright that the emission from the AGN narrow line
region overwhelms the entire host galaxy’s star formation emission lines.
These X-ray AGN are generally identified in traditional BPT diagrams because
they have high integrated [Oiii]/H$\beta$ ratios. This effect was also seen in
the simulations of Bridge et al. (2016).

Figure 6 further investigates the relationship between [Oiii]/H$\beta$
gradient and galaxy stellar mass. There is no strong trend between the
resolved [Oiii]/H$\beta$ and stellar mass, as there is a large range of
[Oiii]/H$\beta$ gradients across the sample. There is a marginal preference
for low mass galaxies to have nuclear ionization. In sections 6.2 and 6.3 we
further investigate the galaxies which deviate from zero gradient.

Figure 6: Inner [Oiii]/H$\beta$ vs outer [Oiii]/H$\beta$ color-coded by
stellar mass. The arrows represent limits in the measured line ratios, with
diagonal arrows representing limits in both axes. The median uncertainty for
the inner and outer ratios is shown in the lower right of the panel. The black
line is the 1:1 ratio between the inner and outer regions. The stars and
hexagons are from the bins described in Table 2. All the bins are within
1$\sigma$ of having a zero gradient.

We now investigate how the spatially resolved emission-line gradient is
affected by a galaxy’s classification as a star-forming or AGN galaxy, as well
as how the [Oiii]/H$\beta$ gradient correlates to galaxy stellar mass, SFR,
size, and redshift.

Figure 7 investigates the relationship between the line-ratio gradient and
galaxy properties, with X-ray AGN and X-ray galaxies shown as red stars and
blue diamonds respectively. We carry out a linear regression fit to the sample
excluding the X-ray AGN and plotted the best-fit line in yellow with its slope
and uncertainty reported in each panel. In all of the panels, X-ray AGN have a
preference for higher $\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$}$ in the nucleus, which we would expect for an AGN ionizing the
central gas. The average [Oiii]/H$\beta$ gradient of X-ray AGN is 0.12 dex,
where the rest of the galaxy population has a [Oiii]/H$\beta$ gradient of
-0.01 dex. X-ray galaxies, on the other hand, have similar [Oiii]/H$\beta$
gradients to other galaxies of the same stellar mass.

In Figure 7, we find that the gradient does not have a relationship with
H$\beta$ SFR or with redshift, as shown in the first and third panels. There
is a marginal (1.55$\sigma$) anti-correlation between gradient and stellar
mass, which was also observed in Figure 5. There is also a marginal
(2.5$\sigma$) relationship between line-ratio gradient and galaxy size, with
higher nuclear ionization in smaller galaxies. The relationships of line-ratio
gradient with stellar mass and size are likely related due to the known
correlation between galaxy mass and radius (van der Wel et al., 2014; Yang et
al., 2021; Mowla et al., 2019).

Figure 7: The relationships of $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ gradient with galaxy SFR, stellar mass,
redshift, and effective radius. X-ray AGN and X-ray galaxies are shown as red
stars and blue diamonds, respectively. Each panel has a yellow linear
regression best-fit line, fit to the galaxies excluding X-ray AGN, with its
slope showing the strength of the relationship. The $\hbox{{\rm[O}\kern
1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ gradient has marginal anti-
correlations with stellar mass and effective radius.

##  6 Discussion

###  6.1 An Intrinsic Population of Galaxies with Higher Nuclear Ionization

Figure 3 shows a broad distribution of measured [Oiii]/H$\beta$ gradients, and
Figure 7 shows that nuclear ionization is marginally preferred in X-ray AGN,
low-mass galaxies, and small galaxies. But it is unclear how much of the
distribution of measured gradients is due to noise or due to the intrinsic
galaxy population. To further investigate this, we compare our measurements
with different models for the underlying distribution.

Figure 8 shows galaxies with well-measured line-ratio gradients as the blue
histogram, and compares its distribution to different models shown as a red
line in each panel. In the left panel our model depicts a distribution of
galaxies with zero intrinsic gradient and with noise drawn from the observed
uncertainties. An Anderson-Darling test returned a p-value of $>$0.25,
indicating that the model is consistent with being drawn from the same parent
distribution as the observed galaxies. In the middle and right panels we start
adding galaxies with higher nuclear or off-nuclear [Oiii]/H$\beta$ ratios (a
gradient of +0.5 dex and -0.5 dex, respectively), until an Anderson-Darling
test finds $p<0.05$ such that the distributions are no longer consistent with
the same parent distribution. We choose $\pm 0.5$ dex because, as shown in
Figure 4, our well-measured gradient sample (the solid blue histogram)
uncertainty extends to 0.5 dex. The middle panel indicates that up to $16\%$
of the galaxies can have nuclear [Oiii]/H$\beta$ that is 0.5 dex higher than
the outer region before the model has a different parent distribution from the
sub-sample. In the right panel, the model distributions indicate that up to
10% of the galaxies can have off-nuclear ionization before it has a different
distribution from the sub-sample. This shows that even though our sub-sample
distribution is consistent with noise there is still room for a significant
fraction of the galaxies to have large nuclear or off-nuclear ionization
profiles.

We repeat this analysis again but this time with a subsample of galaxies that
have the lowest $\delta\Delta\log_{10}(\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$})$, shown in Figure 9. This leaves us with 30
galaxies in our blue histograms with a gradient uncertainty less than 0.3 dex.
The left panel shows a model with zero intrinsic gradient and the same
uncertainties as the observations. In this case, an Anderson-Darling test
indicates that model is not a good description of the data, with $p=0.01$.
This indicates that, at least among galaxies with the smallest uncertainties
in the line-ratio profiles, there is a significant population of galaxies with
intrinsically higher nuclear [Oiii]/H$\beta$ that cannot be simply explained
by noise. The right panel shows that our sample is best modeled by at least
$6\%$ of the galaxies having nuclear $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ that is 0.5 dex higher than the outer
region. The best-measured galaxies are statistically inconsistent with all
galaxies having a flat [Oiii]/H$\beta$ profile, and $6\%$ of galaxies with 0.5
dex higher nuclear [Oiii] need to be added to reproduce the observations.
Meanwhile, in the larger population we find we can fit strong [Oiii]/H$\beta$
nuclear ionization (0.5 dex) in up to $16\%$ of galaxies. There appears to be
a genuine intrinsic population of galaxies with higher ionization in their
central regions as $6-16\%$ of galaxies have nuclear ionization that is 0.5
dex higher than their outer regions. As we used a p-value of 0.05 this 6-16%
fraction of galaxies with higher nuclear ionization roughly corresponds to a
$95\%$ confidence interval.

Figure 8:  In each panel we compare the distribution of emission-line ratio
gradients in our well-measured galaxies (blue histogram in each panel) to
simulated datasets (red line). In the left panel we show a simulated
distribution with zero emission line gradients with noise. An AD test returns
$p>0.25$, showing the distributions are consistent. In the middle panel we
increase the fraction of galaxies with higher nuclear emission-line gradients
(+0.5 dex) until the AD-test is $p<0.05$: this occurs where 16% of the
galaxies have gradient (with 0.5 dex higher [Oiii]/H$\beta$ in the nucleus).
The right panel repeats the test but using -0.5 dex gradients, where we find
that the AD-test is $p<0.05$ when 10% of the galaxies show off-nuclear
gradients (where the [Oiii]/H$\beta$ ratio is 0.5 dex higher in the outskirts
of the galaxies). Figure 9:  In each panel we compare the distribution of
emission-line ratio gradients in our galaxies with a
$\delta\Delta\log_{10}(\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$})$ under 0.3 dex (blue histograms in each panel) to simulated
datasets (red line). In the left panel we show a simulated distribution with
zero emission line gradients with noise. An AD test returns p=.01, showing the
distributions are inconsistent. In the right panel we increase the fraction of
galaxies with strong emission-line gradients (+0.5 dex) until the AD-test is p
> 0.05: this occurs where 5.5% of the galaxies have gradient (with stronger
OIII/H-beta in the nucleus). This tells us the the off-nuclear ionization
galaxies are more likely to just be caused by noise.

###  6.2 Nuclear Ionization and Low-Luminosity AGN

Figure 10: _Left_ : The inner and outer [Oiii]/H$\beta$ ratios for galaxies
binned by stellar mass and SFR as described by Table 2. In all bins the inner
and outer [Oiii]/H$\beta$ ratios are consistent within $1\sigma$, suggesting
that galaxies on average have relatively flat [Oiii]/H$\beta$ gradients.
_Middle_ : The six galaxies with nuclear [Oiii]/H$\beta$ ratios that are at
least 1.5$\sigma$ higher than their outer [Oiii]/H$\beta$ ratios, suggesting
higher nuclear ionization. All six of these galaxies are not X-ray detected in
the deep CDF-S and CDF-N catalogs (Luo et al., 2017; Xue et al., 2016).
_Right_ : 19 objects that have ($\sim$ 0.5 dex) higher [Oiii]/H$\beta$ ratios
in their outer regions compared to their inner ratio.

In the previous subsection we find evidence that 6-16% of the galaxies in our
sample have higher nuclear [Oiii]/H$\beta$. In this subsection we investigate
individual galaxies that are candidates for having high nuclear ionization.
The middle panel of Figure 10 shows the line-ratio profiles of the 6 galaxies
with positive [Oiii]/H$\beta$ gradients detected with more than 1.5$\sigma$
significance. Two of these galaxies have a lower limit in their inner
[Oiii]/H$\beta$ ratio, as shown by the triangles in Figure 10. The galaxies
shown in the middle panel of Figure 10 have an average gradients of 0.6 dex,
which is larger than the average X-ray AGN [Oiii]/H$\beta$ gradient of 0.12
dex shown in Figure 7 and the AGN identification threshold of
$\Delta\log(\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$})=0.1$ dex used in Bridge et al. (2016). This makes the six galaxies
prime candidates to host low-luminosity AGN.

Figure 11: Two of the galaxies from the right panel of Figure 10 which have
gradients with SNR>1.5 and indicate nuclear ionization. The left three panels
show the F105W image, the [Oiii] emission-line map, and the H$\beta$ emission-
line map for each galaxy. _Right_ : The SFR and stellar mass of the parent
sample with the galaxy of interest highlighted as a red star. Both galaxies
appear to have [Oiii] emission that is more compact than the continuum image
and than the Hb emission.

Figure 11 shows continuum (F105W), [Oiii], and H$\beta$ images for two of the
galaxies identified in the right panel of Figure 10. The right panel marks the
galaxy of interest in the distribution of SFR and stellar mass of the parent
sample. Figure 11 gives an example of a low-mass and a high-mass galaxy, where
both are extended in their continuum and H$\beta$ images but have more compact
[Oiii] emission. The detection of higher nuclear [Oiii]/H$\beta$ emission-line
ratios could indicate a low-luminosity and/or obscured AGN that is undetected
by the deep X-ray observations (Xue et al., 2016; Luo et al., 2017).

Gradients in [Oiii]/H$\beta$ can also be caused by non-flat metallicity
gradients resulting in varying [Oiii]/H$\beta$ ratios across the disks. Simons
et al. (2021) showed that high stellar mass galaxies at redshifts $z\sim 1.5$
generally have flat metallicity profiles while low stellar mass galaxies have
lower metallicity in the center (higher [OIII]/Hb in the center at the 0.1
dex/kpc scale). This would cause higher $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ in the center, however the gradients we
measure are $\sim$0.5 dex over $\sim$2 kpc while Simons et al. (2021) have
gradients $\sim$0.1 dex/kpc, so metallicity alone is unlikely to fully account
for the elevated central $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$.

Using a similar analysis with stacked data from both CANDELS WFC3 and Chandra,
Trump et al. (2011) found that it was likely that at least some of the
galaxies in their sample of 28 objects contained weak AGN. Single-object
studies have also been done: Wright et al. (2010) used the OSIRIS integral
field spectrograph on the Keck Observatory to show that the nuclear region
($\sim 0$$\farcs$2) of a $z\sim 1.5$ galaxy exhibits elevated [Oiii]/H$\beta$
and [N II]/H$\alpha$ ratios, which they posit is an indication of an embedded
AGN. Our analysis finds 6 galaxies at $z\sim 1$ which show promise for hosting
low-luminosity AGN.

###  6.3 Off-Nuclear Ionization

Figure 5 and 6 show a wide range of line-ratio profiles, including galaxies
with higher $\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$}$ in their outer regions. Section 6.1 indicates that the observed
high off-nuclear [Oiii]/H$\beta$ ratios are consistent with flat
[Oiii]/H$\beta$ profiles and observational uncertainties. But the
uncertainties are sufficiently large that the same analysis indicates that up
to 10% of the galaxies might have off-nuclear ionization profiles with
[Oiii]/H$\beta$ that is 0.5 dex higher in galaxy outskirts than in galaxy
centers. Such systems could be off-nuclear AGN. Evidence of off-nuclear
massive black holes has been observed near the center of the Milky Way (Oka et
al., 2017), and the discovery of extragalactic off-nuclear X-ray sources
(e.g., Farrell et al., 2009; Jonker et al., 2010; Barrows et al., 2016) has
lent credence to the idea that massive black holes exist at significant, 1 kpc
or greater, distances from the centers of galaxies.

Figure 12: Left: The gradient of inner minus outer $\hbox{{\rm[O}\kern
1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ versus dust attenuation.
Right: The gradient of $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ versus the galaxy axis ratio. X-ray AGN and
X-ray galaxies are red stars and blue triangles, respectively. The off-nuclear
ionization galaxies (negative $\Delta\log(\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$})$) do not have more dust attenuation that
the rest of the sample, and also are not preferentially edge-on galaxies. An
Anderson-Darling test between the off-nuclear sources and the full sample
returns a p-value $>0.25$, indicating the high off nuclear ionization galaxies
are consistent with the same parent distribution as the rest of the sample.
Figure 13: Two galaxies with higher off-nuclear [Oiii]/H$\beta$ in the
outskirts than in their centers. The left panels show the direct F105W image.
The center panels show the [Oiii]/H$\beta$ of the outer-region pixels as a
function of the angle shown in the left panel, with the inner-pixel ratio and
median outer-pixel ratio shown as horizontal lines. The right panels show the
outer-pixel [Oiii] and H$\beta$ fluxes color-coded by angle, with limits in
line fluxes and ratios shown by triangles. The inner-pixel ratio and median
outer-pixel ratio are shown as red and blue stars, respectively. Both galaxies
have an apparent preference for high [Oiii]/H$\beta$ ratios at particular
angles, shown by dashed vertical lines in the middle panel, that do not
coincide with the continuum light in the direct image, indicated by white
arrows in the left panel.

We investigate the possibility of off-nuclear AGN by investigating the line-
ratio maps of a sample of 19 objects that have ($\sim$0.5 dex) higher
[Oiii]/H$\beta$ ratios in their outer regions compared to their inner ratio as
shown in the right panel of Figure 10. Of the 19 galaxies, five of them cross
the AGN/SF line with an outer region indicating an AGN while the central ratio
stays in the SF region. Three of these five points also have a lower limit in
their outer ratio measurement.

We first investigate if dust and/or orientation plays a role in causing higher
off-nuclear [Oiii]/H$\beta$ ($\Delta\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$<0), using measurements of $A_{V}$
attenuation and axis ratio from the compilation of Barro et al. (2019).
Matching catalogs results in 196 galaxies from our sample, for which we show
AV and axis ratio measurements in Figure 12. From the left panel we can see
that the off-nuclear ionized galaxies do not have more dust attenuation that
the rest of the sample. The right panel shows that the off-nuclear ionized
galaxies are not preferentially viewed edge-on. An Anderson-Darling test
between the off-nuclear sources and the full sample returns a p-value $>0.25$
for both dust attenuation and axis ratio, showing the high off-nuclear
ionization galaxies have the same distribution as the rest of the sample. This
shows that high [Oiii]/H$\beta$ ratios in galaxy outskirts are not
preferentially produced by dust attenuation.

We investigate the possibility of these galaxies hosting off-nuclear AGN by
looking for clumping of off-nuclear [Oiii]/H$\beta$ and/or continuum light at
particular angles, as shown in Figure 13. The left panel shows the F105W
continuum image, the middle panel shows the emission-line ratio of each pixel
in the outer region verses the angle, and the right panel shows the emission-
line flux of each outer-region pixel color-coded by the angle. The middle and
right panel show the median for the inner (outer) regions as a red (magenta)
line or star, respectively, and limits are shown by triangles. Off-nuclear AGN
might lead to a clump of high [Oiii]/H$\beta$ ratio and high [Oiii] flux at a
narrow range of angle. This is shown by simulations done by Bellovary et al.
(2010) and Seepaul et al. (2022) which indicate that off-nuclear AGN can be
detected if they retain a bound clump of both gas and stars.

These are the only 2 of the 19 galaxies with high off-nuclear
$\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ that have
a preferred angle for higher [Oiii]/H$\beta$ emission. If we also see more
continuum light at that angle, this would give further indication of an off-
nuclear AGN. However, we did not see this for either galaxy. The two galaxies
shown in Figure 13 do show a peak $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ ratio at a particular angle in the middle
figure, at $\sim 60\deg$ for the top panel and $\sim 260\deg$ in the bottom
panels. But the continuum light in these galaxies does not have the same
distribution, and is instead concentrated at different angles (330 deg in the
top galaxy, and 150 deg in the bottom). The other 17 galaxies with high outer-
region [Oiii]/H$\beta$ do not show this kind of clumpiness, but instead the
[Oiii]/H$\beta$ is distributed over a wide range of angles.

The two galaxies examined in Figure 13 do not seem to be well-described as
off-nuclear AGN. These example galaxies could instead be ionized outflows, as
there is not a concentration of continuum light in the areas that are marked
with high ionization. High outer-region [Oiii]/H$\beta$ could indicate a
metal-rich nucleus and metal-poor disk (commonly referred to as a "negative
metallicity gradient"), as observed in some massive high-redshift galaxies
(Wuyts et al., 2016). The number of galaxies with off-nuclear ionization is
also fully consistent with the large uncertainty in the measured gradients, as
indicated from our models of the intrinsic distribution of line-ratio
gradients.

##  7 Conclusions

We report measurements of resolved [Oiii]/H$\beta$ line-ratio profiles via
_HST_ /WFC3 G102 grism observations taken as part of the CLEAR survey. We
measured [Oiii]/H$\beta$ gradients by taking the center of the galaxy, defined
by the photometric center of the F105W image, and subtracting the median of
the [Oiii]/H$\beta$ ratio in an annular extended region. We investigate the
spatially-resolved nature of this line ratio, and we summarize our results as
follows:

  * •

The data binned by stellar mass and SFR in Figures 5 and 6 show that low
stellar mass galaxies tend to have marginally higher nuclear
$\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ whereas
high stellar mass galaxies have flat gradients. The SFR of the galaxy is not
correlated with the $\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$}$ gradient. A slight anti-correlation ($\sim 1.6\sigma$) between
stellar mass and $\hbox{{\rm[O}\kern 1.00006pt{\sc iii}{\rm]}}/\hbox{{\rm
H}$\beta$}$ gradient is shown in Figure 7. This also shows a $\sim 2\sigma$
anti-correlation of effective radius with $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ gradient.

  * •

X-ray AGN have a 0.1 dex higher nuclear $\hbox{{\rm[O}\kern 1.00006pt{\sc
iii}{\rm]}}/\hbox{{\rm H}$\beta$}$ than the rest of the sample, as seen in
Figure 7.

  * •

We compare toy models to the distribution of galaxies with well-measured
gradients and galaxies with the lowest gradient uncertainty from our data set.
From these toy models, Figures 8 and 9, we found that 6-16% of the sample is
likely to include galaxies with higher nuclear [Oiii]/H$\beta$. The lower
limit comes from the number of galaxies needed for the model to have a similar
distribution to galaxies with the smallest gradient uncertainty, while the
upper limit is from the number of galaxies before the model has a different
distribution from galaxies with no limit in its gradient measurement.

  * •

The toy models show that galaxies with higher nuclear ionization are likely to
exist, but the individual detections are marginal (only $\sim$1.5$\sigma$) as
shown in Figure 10. These galaxies potentially host low-luminosity AGN in its
nucleus that are not detectable by X-rays or BPT diagrams.

  * •

We investigate the galaxies with the largest measured off-nuclear
[Oiii]/H$\beta$ ratios and find that they are mostly consistent with
observational noise. Two galaxies shown in Figure 13 have "clumpy" off-nuclear
[Oiii] emission that is roughly orthogonal to the morphology of the continuum
image, and so is probably better described by an ionized gas cone than by off-
nuclear AGN.

This work sheds light on the ensemble properties of 1<z<2 galaxies, especially
the conclusion that 6-16% of galaxies have considerable ($\sim$0.5 dex)
central [Oiii]/H$\beta$ gradients indicative of nuclear AGN that are missed by
other methods. But the measurements of individual galaxies are limited by
large uncertainties in the CLEAR data. A better understanding of individual
galaxies, including searches for off-nuclear AGN or more nuanced ionization
profiles, requires deeper data. This is available from HST/WFC3 grism data in
FIGS and MUDF, and will soon be available from JWST/NIRISS surveys like
NGDEEP.

##  8 Acknowledgments

This work is based on data obtained from the Hubble Space Telescope through
program number GO-14227. Support for program GO-14227 was provided by NASA
through a grant from the Space Telescope Science Institute, which is operated
by the Association of Universities for Research in Astronomy, Incorporated,
under NASA contract NAS5-26555. B.E.B. and J.R.T. acknowledge support from NSF
grant CAREER-1945546 and NASA grant JWST-ERS-01345. J.S.B. acknowledges
support from NASA/STScI grant HST-AR-15008.

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