# Emission-line galaxies at $z\sim 1$ from near-IR HST Slitless Spectroscopy:
metallicities, star formation rates and redshift confirmations from VLT/FORS2
spectroscopy

K. Boyett,1,2 A. J. Bunker,3 J. Chevallard,3 A. Battisti,2,4 A. L. Henry,5 S.
Wilkins,6,7 M. A. Malkan,8 J. Caruana,7,9 H. Atek,10 I. Baronchelli,11,12 J.
Colbert,13 Jonathan P. Gardner,14 M. Rafelski,5,15 C. Scarlata,16 H. I.
Teplitz,13 X. Wang,17,18,19
1School of Physics, University of Melbourne, Parkville 3010, VIC, Australia
2ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D),
Australia
3Department of Physics, University of Oxford, Oxford OX1 3PU, UK
4Research School of Astronomy and Astrophysics, Australian National
University, Cotter Road, Weston Creek, ACT 2611, Australia
5Space Telescope Science Institute, 3700 San Martin Dr., Baltimore, MD 21218,
USA
6Astronomy Centre,University of Sussex, Falmer, Brighton BN1 9QH, UK
7Institute of Space Sciences and Astronomy, University of Malta, Msida
MSD2080, Malta
8Department of Physics and Astronomy, University of California, Los Angeles,
430 Portola Plaza, Los Angeles, CA 90095, USA
9Department of Physics, University of Malta, Msida MSD2080, Malta
10Institut d’Astrophysique de Paris, CNRS, Sorbonne Université, 98bis
Boulevard Arago, 75014, Paris, France
11INAF - Istituto di Radioastronomia, via Gobetti 101, 40129 Bologna, Italy
12Italian ALMA Regional Centre, via Gobetti 101, 40129 Bologna, Italy
13IPAC, Mail Code 314-6, California Institute of Technology, 1200 E.
California Blvd., Pasadena CA, 91125, USA
14Astrophysics Science Division, NASA Goddard Space Flight Center, 8800
Greenbelt Rd, Greenbelt, MD 20771, USA
15Department of Physics and Astronomy, Johns Hopkins University, Baltimore, MD
21218, USA
16Minnesota Institute for Astrophysics, University of Minnesota, 116 Church St
SE, Minneapolis, MN 55455, USA
17School of Astronomy and Space Science, University of Chinese Academy of
Sciences (UCAS), Beijing 100049, China
18National Astronomical Observatories, Chinese Academy of Sciences, Beijing
100101, China
19Institute for Frontiers in Astronomy and Astrophysics, Beijing Normal
University, Beijing 102206, China E-mail<EMAIL_ADDRESS>
(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

We follow up emission line galaxies identified through the near-infrared
slitless HST/WFC3 WISP survey with VLT/FORS2 optical spectroscopy. Over 4 WISP
fields, we targetted 85 of 138 line emission objects at $0.4<z<2$ identified
in WFC3 spectroscopy. Half the galaxies are fainter than $H_{AB}=24$ mag, and
would not have been included in many well-known surveys based on broad-band
magnitude selection. We confirm 95% of the initial WFC3 grism redshifts in the
38 cases where we detect lines in FORS2 spectroscopy. However, for targets
which exhibited a single emission line in WFC3, up to 65% at $z<1.28$ did not
have expected emission lines detected in FORS2 and hence may be spurious
(although this false-detection rate improves to 33% using the latest public
WISP emission line catalogue). From the Balmer decrement the extinction of the
WISP galaxies is consistent with $A($H$\alpha)=1$ mag. From SED fits to multi-
band photometry including Spitzer $3.6\,\mu$m, we find a median stellar mass
of $\log_{10}(M/M_{\odot})=8.94$. Our emission-line-selected galaxies tend to
lie above the star-forming main sequence (i.e. higher specific star formation
rates). Using [Oiii], [Oii] and H$\beta$ lines to derive gas-phase
metallicities, we find typically sub-solar metallicities, decreasing with
redshift. Our WISP galaxies lie below the $z=0$ mass-metallicity relation, and
galaxies with higher star formation rates tend to have lower metallicity.
Finally, we find a strong evolution with redshift of the H$\alpha$ rest-frame
equivalent width, $EW_{0}($H$\alpha)\propto(1+z)^{1.85\pm 0.24}$ with higher
$EW_{0}$ galaxies having larger [Oiii]/H$\beta$ and O32 ratios on average,
suggesting lower metallicity or higher ionisation parameter in these extreme
emission line galaxies.

###### keywords:

galaxies: star formation – evolution – ISM

††pubyear: 2024††pagerange: Emission-line galaxies at $z\sim 1$ from near-IR
HST Slitless Spectroscopy: metallicities, star formation rates and redshift
confirmations from VLT/FORS2 spectroscopy–C

##  1 Introduction

In this paper we study galaxies seen in H$\alpha$ emission across “cosmic
noon" ($z\sim 0.5-2$), the era when the star formation rate (SFR) comoving
density peaks (Madau & Dickinson, 2014). In recent years there has been
significant effort in slitless spectroscopic surveys from HST, such as the
WFC3 Infrared Spectroscopic Parallel (WISP) Survey in the near-IR (Atek et al.
2010; Battisti et al. 2024), and currently this is being greatly expanded with
ongoing space-based Wide Field Slitless Spectroscopy (hereafter, WFSS) such as
JWST-NIRISS (e.g. Boyett et al., 2022) and NIRCam (e.g., Oesch et al., 2023;
Kashino et al., 2023), and Euclid (Laureijs et al., 2011). WFSS selects
directly on emission line strength (which is often a good proxy for the star
formation rate), and is sensitive to high equivalent width sources. These
extreme emission line objects, with potentially high specific star formation
rates, may well be missed in traditional multi-object spectroscopic surveys
which are based on broad-band photometric selections.

However, many WISP spectra contain only single emission lines (some with low
signal-to-noise) where line designation may be in error. To address this
concern, we analyse VLT/FORS2 spectroscopic optical follow-up on selected WISP
galaxies. A key goal is redshift confirmation, affirming WISP line
identifications and improving redshift measurements with higher spectral
resolution. The optical spectroscopy also enables the study of line ratio
diagnostics, to measure the gas-phase metallicity of the WISP galaxies and to
identify potential Active Galactic Nuclei (AGN).

In this work we describe the reduction and analysis of the VLT/FORS2
spectroscopy, and combine this with the WFC3 spectra and photometry across a
wide wavelength range (including Spitzer 3.6 $\mu$m imaging) to study the
nature and evolution of emission line galaxies at high redshift.

The outline of this paper is as follows. We discuss the HST/WFC3 and VLT/FORS2
spectroscopic observations, along with the target selection, data reduction
and ancillary photometry in Section 2. We identify the FORS2 detected
emissions lines and from these determine redshifts in Sections 3.1 and 3.2. We
use the measured line emission and photometry to investigate AGN contamination
(S3.4), star formation rates and stellar masses (S3.5), metallicity (S3.6),
and a sub-sample of galaxies with extreme equivalent widths (EWs, S3.7). Where
applicable, we use a standard $\Lambda$CDM cosmology with parameters
H${}_{0}=70$ km/s/Mpc, $\Omega_{m}=$0.3, and $\Omega_{\wedge}=$0.7. All
magnitudes are in the AB system (Oke & Gunn, 1983). When quoted, all EWs are
in the rest-frame.

##  2 Observations

The initial results of the WFC3 Infrared Spectroscopic Parallel survey (see
Section 2.1) are reported in Atek et al. (2010) with subsequent data releases
being made available through MAST111The latest data release (v1.00) is
available on the Milukski archive for space telescopes page
https://archive.stsci.edu/prepds/wisp/ as the survey expanded (Battisti et
al., 2024). In this Section we report the optical spectroscopy follow-up
performed at the VLT on 4 selected WISP fields (Par:309, 64, 62 and 236),
providing complementary 0.5 to 0.9 $\mu$m wavelength coverage, ideal for rest-
optical emission lines (e.g., [Oii]$\lambda\lambda 3727,29$, H$\beta$ and
[Oiii]$\lambda\lambda 4959,5007$) in our anticipated redshift range, and
offering up to an order of magnitude greater spectral resolution relative to
the WFC3 grisms. First we will briefly describe the WISP HST/WFC3 WFSS, then
we will detail follow-up target selection, observing strategy, and
spectroscopic data reduction. Finally we will discuss the complementary
broadband photometry.

###  2.1 HST/WFC3 wide field slitless spectroscopy

The WISP survey (Atek et al. 2010; Battisti et al. 2024) is a pure parallel
program on the Hubble Space Telescope, using the WFC3 G102 and G141 infrared
grisms to detect emission line galaxies through WFSS from 0.7 to 1.8$\mu m$
over $\sim 1600$ arcmin2 of blank fields. Sensitive to H$\alpha$ emission
across a broad redshift range, $0.5<z<1.6$, the WISP survey detects emission
line galaxies whose continuum may otherwise be too faint to appear in standard
broadband wide field photometric surveys. Selecting on emission line strength
rather than broadband luminosity is ideal for targetting low mass systems
exhibiting high specific star formation rates (sSFR) which are expected to be
abundant above $z>1$ (e.g., van der Wel et al., 2011) but are below the
broadband photometric threshold for selection in typical spectroscopic surveys
(see Section 3.7). WFSS offers the advantage over broad-band pre-selection for
spectroscopic follow-up in that we are selecting directly on the quantity of
interest (the star formation rate, indicated by the H$\alpha$ flux), hence
reducing any observational biases in a survey of star forming galaxies (SFGs).
Atek et al. (2010) and Battisti et al. (2024) provide the data reduction
method and detail the identification and flux measurements of the observed
emission lines ([Oii]$\lambda\lambda 3727,29$, H$\beta$, [Oiii]$\lambda\lambda
4959,5007$, H$\alpha$, [Sii]$\lambda\lambda 6716,30$) from the WISP HST/WFC3
slitless spectra, with accompanying redshift estimates.

####  2.1.1 WFSS emission line catalogues

A publicly available WISPS emission line catalogue (v1.00)1 is presented in
Battisti et al. (2024). The slitmasks for the VLT/FORS2 observations (see
Section 2.2) were based on an earlier version of the catalogue which had a
lower emission line S/N threshold and less thorough visual inspection of
emission line candidates, and hence had a larger number of potential targets.
We note that the v1.00 catalogue does not cover one of our four target fields
with FORS2 (Par62) where 13 galaxies were assigned slits. For the 72 galaxies
we targetted in the other three fields, many are not included in the later
v1.00 catalogue (53/72) due to its higher S/N cut, although as we discuss in
Section 3.1 some of these galaxies were subsequently spectroscopically
confirmed in our FORS2 observations. In column v1.00_par_obj of Table 4 we
show the matching ID in the v1.00 catalogue for the 19 galaxies which we
targetted with FORS2 which are included in the v1.00 catalogue in Battisti et
al. (2024).

We note that when we match the original emission line catalogue, from which
the slitmask design was based, to the v1.00 catalogue; only 34 of the 114
original candidates are included in v1.00 (we exclude Par62 from the matching
as we know that this field was not included in v1.00). From these 34
candidates, the reported redshift is consistent between both catalogues for 24
candidates but has changed significantly in 11 cases due to the identification
of the detected emission lines in the WFSS being updated (see Appendix A).

###  2.2 VLT/FORS2 Observation and Target Selection

Between July and August 2014, follow-up optical spectroscopic observations
were conducted for a sub-sample of WISP galaxies using the FOcal Reducer/low
dispersion Spectrograph 2 (FORS2, Appenzeller et al. 1998), a multi-object
spectrometer on the Very Large Telescope UT1 (Antu), as part of programme
093.A-0893 (P.I A. Bunker). FORS2 uses two red-sensitive MIT/LL $2k\times 4k$
CCDs, with a native pixel scale of $0.125^{\prime\prime}$ pixel-1. To reduce
the readnoise we binned the pixels $2\times 2$ (hereafter we refer to the
binned pixels, 0.25′′), which still Nyquist-sampled the seeing and spectral
resolution. The observations are detailed in Table 1, and were taken at low
airmass (1.0–1.35) and in good seeing ($\sim 0.6^{\prime\prime}$ FWHM). We
used a slit width of 1′′ across all of the masks. The 600RI grism (with a
central wavelength of 6800 Å) was used in combination with the GG435 order-
blocking filter. Each slit mask was observed twice, each with a 1400 s
exposure. The mask was nodded by 3′′ between the two exposures to place the
targets first in the upper half of their slit and then in the lower ($\pm
1.5^{\prime\prime}$ from the centre of the slit), in order to perform local
background subtraction (discussed in Section 2.3). Acquisition images of the
field were taken in the $R$-band before the slitmask was moved into the focal
plane. The field-of-view of FORS2 is $6.8\times 6.8$ arcmin2. Since our WISP
fields were smaller (the HST/WFC 3 detector is only 2.2 arcmin across) we
placed all our targets in just one of the two FORS2 detectors.

We chose 4 WISP survey fields to observe which were equatorial or in the
Southern hemisphere with RAs appropriate to the observing season. Two of the
WISP fields (Par309 and Par236) were observed twice with different slitmask
designs to accommodate the larger number of WISP emission line targets in
these fields, and as part of these masks designs three targets appeared on
both masks (and these are indicated in our Tables 2 \- 8 as “double-galaxy").
The emission line catalogue from the WISP HST/WFC3 spectroscopy (Section 2.1)
has between 24 and 48 candidate galaxies per field, based on the early
catalogues used to select the targets for FORS2 spectroscopy (not all of which
are included in the latest v1.00 public catalogue). We could not accommodate
all these candidates in each field on a single FORS2 slitmask, since we wanted
a minimum slitlet length of 8′′ to facilitate sky subtraction by nodding at
two positions along the slit. Over the 2.2′ HST/WFC3 field we could allocate
at most $\sim 15$ targets, and we gave each galaxy a score based on the WISP
line emission, considering the observed H$\alpha$222If H$\alpha$ was not
detected within the wavelength coverage (e.g., at too high a redshift,
$z>1.6$) the [Oiii] doublet was used instead. emission line equivalent width,
signal-to-noise (S/N) and the determined redshift. Specifically, the scores
were to favour:

  * •

a high signal-to-noise ratio in the WISP WFC3 spectroscopy from our early
catalogues, with $S/N>10$ scoring 3, $5<S/N<10$ scoring 2, and $S/N<5$ scoring
1;

  * •

a high observed-frame equivalent width emission line sources, with H$\alpha$2
$\rm{EW}>300$ Å scoring 3, $100<$EW$<300$ Å scoring 2, and $\rm{EW}<100$ Å
scoring 1.

The scores for observed equivalent width and S/N were multiplied together to
obtain an overall score between 1 and 9, and if the redshift based on the WFC3
WFSS lay beyond $z=1.28$ we down-weight the overall score by a factor of 4,
since few bright emission lines would fall in our FORS2 wavelength range at
higher redshifts. In the early WISP survey catalogues used to for the FORS2
mask design about 20-30% of galaxies per field lie at these higher redshifts
(and 36% lie at $z>1.28$ in the subsequent v1.00 catalogue for the entire WISP
survey). Beyond this redshift, 15 galaxies are selected for follow-up to check
if conflicting emission lines appear (8 of which are in the v1.00 catalogue,
we note that the redshift of 2/8 has changed between the catalogues and these
2 are now in the redshift range where we expect to observe corresponding line
emission in FORS2.); this can provide confirmation on whether or not the
HST/WFC3 grism detected lines were identified correctly.

Based on these overall scores we used the UCSC-LRIS mask design
software333https://www.ucolick.org/~phillips/lris/, developed by D. Phillips
and collaborators for LRIS on the Keck telescope, to maximise the sum of the
overall scores of the objects placed on the slitmask, optimising the centre
and position angle for this. Of 138 galaxies in the initial WISP survey
emission line catalogue used in the slitmask design for these 4 fields, 85
have slits placed over them (a completeness of $62\%$). In Figure 1, we
present the distribution of H-band magnitudes for our FORS2 sample. In Figure
2 we show the distribution of the rest-frame $V$-band absolute magnitudes
($\sim 5500$ Å), MV, for the WISP galaxies within the sample that have
observed photometric coverage (observed-frame F110W-F160W), and we note the
wide range of galaxy luminosities in our emission line selected sample. We
determine MV using the best available spectroscopic redshift, adopting the
FORS2 spectroscopic redshift when available (see Section 3.2), otherwise using
the WFC3 spectroscopic redshift. We will discuss the redshift distribution in
Section 3.2 with the distribution of spectroscopic redshifts presented in
Figure 3.

Observation | RA | Dec | Date | Airmass | Seeing
---|---|---|---|---|---
mask | (Deg) | (Deg) |  |  |
309_1 | 324.79799 | -38.419686 | 2014-08-03 | 1.0655 | 0.55′′
309_2 | 324.79799 | -38.419686 | 2014-08-03 | 1.0615 | 0.6′′
64_2 | 219.36889 | -1.8316702 | 2014-07-18 | 1.2465 | 0.6′′
62_1 | 195.318858 | -0.03223 | 2014-07-18 | 1.374 | 0.575′′
236_1 | 231.20360 | 0.41788568 | 2014-07-01 | 1.129 | 0.675′′
236_2 | 231.20360 | 0.41788568 | 2014-07-29 | 1.3515 | 0.625′′
std_star | 28.710728 | -27.47780 | 2014-07-25 | 1.33 | 0.625′′
Table 1: Observation conditions for our 6 FORS2 masks and our standard star.

###  2.3 FORS2 data reduction

The European Southern Observatory (ESO) provide a reduction pipeline for the
FORS2 instrument - EsoReflex (Freudling et al., 2013). However, this pipeline
reduces individual exposures and does not combine the nodded observations at
different positions that we took. Hence we perform our own data reduction,
using standard techniques in the Image Reduction and Analysis Facility (IRAF).
We now briefly outline the process.

Each exposure first had the bias removed using the overscan regions using the
colbias package. For each slitmask we averaged several spectroscopic flat
fields taken during the day with the same instrumental configuration. Then we
normalized the flat field for each slitlet by dividing by the spectral shape
of the flat field lamp (obtained by collapsing the 2D spectrum spatially,
along the long axis of the slit), leaving the pixel-to-pixel sensitivity
variations. We then flat fielded our science integrations for each 2D slitlet
through division by the appropriate flat field.

We performed cosmic ray rejection through two methods. We first used LACOSMIC
(van Dokkum, 2001) on the individual 2D science spectra for each slitlet. We
also used crreject within the IRAF imcombine package, rejecting outliers at
the $4\sigma$ level when the two spatially-offset spectra were aligned (we
used the CCD gain of 1.43e/DN and detector read noise of 2.9 electrons so that
the Poisson noise was correctly calculated). The cosmic rays found were added
to a mask, which also included bad pixels and regions not illuminated by the
slitlet.

Finally, we subtracted one nod position from the other, and this “$A-B$”
spectrum had the sky emission subtracted out although residuals due to time
variation were still present. We combined the 2D “$A-B$” spectrum with the
inverted “$B-A$” applying a spatial offset to reverse the effect of the nod
along the slit, so that the spectrum of the target galaxy added at the same
location. Bad pixels, unilluminated areas and cosmic rays were excluded in
this combination.

The resulting 2D combined spectra for each slitlet (i.e. targetted galaxy) had
not yet been corrected for spatial curvature, or wavelength and flux
calibrated. However, at this point each pixel was independent (no
interpolation had yet been applied), so the noise could be measured directly
and was found to agree well with the expected Poisson noise (with the readout
noise added in quadrature) derived from the spectrum of the sky emission.

The spectra of each object is then extracted using the apextract.apall package
in IRAF. For the brighter objects, where the spectral continuum was easily
seen, we traced how the position of the spectrum varied with wavelength across
the detector. For fainter objects, where no continuum or just individual
emission lines were visible, we used the edge of the slit (which was readily
seen in the flat field exposures) to map the spatial distortion. We use a 1′′
extraction width, corresponding to 4 pixels centred on the target, in
combination with the 1′′-width slits this creates a
1${}^{\prime\prime}\times$1′′ extraction aperture. Some sources were spatially
extended, so we also performed a second extraction over a wider 10-pixel
(2.5′′) height along the slit. In both cases we applied background subtraction
using the IRAF.background package to remove any residual sky emission which
remained after the differencing of the offset exposures, by subtracting the
clipped average counts in pixels between 6 and 10 pixels from the object
position (which avoided self-subtracting the object flux, and also avoided the
ends of the slitlets). For each extraction width we also generated a 1D noise
spectrum from the Poisson noise model of the object and sky counts (taking
into account the gain of the detector).

Wavelength calibration for each slitmask was done using NeArHgHe arc lamps
observed during the day with the same instrument configuration. We extracted
the arc spectrum for each slitlet using the same trace as the object, but
without the background subtraction. We fit a cubic mapping of pixel to
wavelength using about 50 arc lines with a scatter of 0.3 Å, and calculated
the average scale to be 1.62 Å pix-1. The wavelength calibration was checked
against sky emission lines in our spectra to confirm there had been no shift
in the grism central wavelength. We then produced two versions of the
wavelength-calibrated spectrum, the first involving interpolation onto a
uniform wavelength scale of 1 Å pix-1, and the other preserving the original
pixels but allocating a wavelength to each pixel on a non-linear scale (so
that the pixels are independent). For slitlets close to the centre of the CCD,
the wavelength coverage was $5150-8470$ Å, although slits placed on targets
towards the edge of the field (offset along the wavelength axis) can have the
wavelength coverage shifted by up to $\pm$300 Å. We computed the spectral
resolution from the FWHM of arclines and unblended sky lines, and found this
to be 5.6 Å, equivalent to a resolving power of
$R=\lambda/\Delta\lambda_{FWHM}=1200$ at our central wavelength. However, we
note that for objects which do not fill the 1′′ slit the spectral resolution
will be better. This spectral resolution is far greater than the $R=210$ and
$R=130$ that the G102 and G141 HST/WFC3 grism achieve at 1.1 $\mu$m and 1.4
$\mu$m respectively.

As part of the FORS2 observing program four standard stars were obtained to
flux calibrate the science images, but these were not necessarily observed on
the same nights as their target masks. Only one of the standard stars
(LTT1020) was taken in similar seeing to our slitmask observations, so we used
this to determine our flux calibration. The extraction and wavelength
calibration were performed as described above. We determined the conversion of
counts to flux density by comparison with the reference values for our
standard star (Hamuy et al., 1992, 1994). For each slitmask we had added about
4 additional brighter compact/point sources as a check of the spectro-
photometry. These objects have photometry from the Sloan Digital Sky Survey
(SDSS DR12) (Fukugita et al., 1996) or the VLT Survey Telescope ATLAS (VHS-
ATLAS DR3) (Shanks et al., 2015). The literature flux in the $r$ and $i$ bands
(within our FORS2 wavelength coverage) was compared to the FORS2 spectrum
continuum flux (convolved with the $r$\- or $i$-band filter transmission
function) averaged across the same wavelength range. The FORS2 observed flux
consistently falls short of the anticipated flux based on the flux calibration
from the single standard star. The discrepancy is seen to be $30\%$ in the
$r$-band and $15\%$ in the $i$-band. The origin of this flux discrepancy may
be due to a number of factors: different seeing; some slight mis-alignment in
the mask acquisition; telescope tracking drift or changes in atmospheric
transparency. We applied the appropriate scaling factor (for the mask and
wavelength) to the emission line fluxes from our FORS2 spectroscopy.

The difference in correction factors between the $r$-band and the $i$-band
regions of the spectra does not have a large impact on the spectral
diagnostics we wish to explore. For example a difference of 15$\%$ in the
[Oii]/H$\beta$ emission line flux ratio would result in an offset of 0.06 dex
in the $x$-axis in Figure 12 (which shows the metallicity tracks in
[Oiii]/H$\beta$ vs. [Oii]/H$\beta$), which is comparable to the error bars and
also the bin size of the SDSS comparison dataset. The [Oiii]/H$\beta$ ratio is
unaffected by the correction factor since these lines are close in wavelength
to each other. A larger potential impact is on the H$\beta$ flux, and hence
the Balmer decrement – perturbing the Balmer decrement H$\alpha$/H$\beta$ by
$15\%$ changes the reddening of A(H$\alpha$) by 0.04 mag.

Finally, for the three galaxies that were each assigned to two masks, allowing
them to be observed twice, the 1D wavelength and flux calibrated spectrum from
each mask are averaged together to achieve greater S/N. We note that in these
3 cases, the measured continuum flux density and emission lines flux ([Oii]
was detected in 309_1_9:309_2_2444The FORS2 ID is constructed as the
combination of the WISP field, the slitmask and the slit the target was
assigned to. e.g., 309_1_9 was the galaxy assigned to slit 9 on the first
slitmask targetting WISP field 309. and 236_1_2:236_2_5, while no lines were
detected in 236_1_9:236_2_7) between the two observations are consistent,
supporting consistent flux calibration between the different masks.

###  2.4 Multi-band photometry

In addition to the HST WFC3 grism slitless and VLT/FORS2 spectroscopy, these
four WISP fields (62, 64, 236 $\&$ 309) have been observed with ground- and
space-based telescopes to provide complementary imaging (described below).
However, not all fields have coverage in all filters and the imaging available
to each WISP field is given in Table 2. We will briefly describe the imaging
and photometric analysis.

As part of the WISP survey (Atek et al. 2010; Battisti et al. 2024) HST/WFC3
WFSS was obtained in combination with direct imaging in typically two HST/WFC3
broadband filters, F110W and one of either F140W or F160W (apart from field
236 which only had F140W obtained). The near-infrared bands are observed to
provide reference images for wavelength calibration of the WFC3 WFSS. As part
of the WISP program, HST/UVIS direct imaging was observed for certain WISP
fields; this included F475X and F600LP for field 64, and F814W for field 309.
Here multiple exposures of the reduced imaging were drizzled into a final
science image that retains the HST/WFC3 native 0.128′′ pixel scale. Due to the
variable number of HST orbits that each WISP field was observed for, the
exposure times for each direct imaging observation vary and we measure
$5\sigma$ limit depth in a 0.4′′ radius aperture in the range 26.05 to 24.74;
full details are given in Table 2.

To complement the HST imaging, the WISP program obtained follow-up ground-
based Palomar/WIYN Sloan $u$, $g$, $r$, $i$ and Spitzer/IRAC 3.6$\,\mu$m
observations for WISP fields 62, 64 and 309. The IRAC imaging is drizzled to a
0.6′′ pixel scale (1.2′′ pixel native scale) and has $5\sigma$ 1.2′′ radius
aperture depths in the range 23.35 to 23.58. The AB magnitude distribution for
the F160W “H-band" (F140W “JH-band" for WISP field 236) is given in Figure 1.

From the available imaging, we determine the photometry with IRAF.phot using
apertures fixed at the location of the emission line galaxies for each WISP
target to provide complementary analysis to existing SExtractor Bertin &
Arnouts (1996) derived photometry from the WISP team (see Atek et al. 2010;
Battisti et al. 2024 for discussion of SExtractor parameter details). The
SExtractor photometry was measured by training on each filter image separately
(i.e., without a reference image), which meant galaxies would not have a flux
measurement in a particular band if they were too faint to be detected in that
image. In these cases our application of fixed-position apertures allows
targets with faint continuum emission to have photometric measurements
obtained even when they were undetected above the SExtractor specified
thresholds. Across the HST direct imaging, 0.4′′-radius apertures are laid on
the coordinates determined from the F160W or F140W reference image of each
WISP target. For our aperture photometry, we apply an aperture correction
determined from point sources to account for the flux falling outside of the
aperture and to return an approximate total magnitude (which is appropriate
for compact sources, but will underestimate the total flux if the source is
significantly extended). Due to the lower resolution of the Spitzer/IRAC
imaging we measure total fluxes using 1.2′′-radius apertures and apply a 0.7
magnitude aperture correction from Eyles et al. (2005) appropriate for a
compact source. The lower resolution of Spitzer/IRAC additionally means that
for a small number of WISP targets the measured flux within an aperture is
confused with the contribution of close neighbours. In each of these cases we
utilise the WISP team photometry from Battisti et al. (2024) which models the
contribution of multiple sources to reduce the confusion. For the majority of
objects, consistency is found between the photometry derived from both the
SExtractor and fixed-aperture photometric analysis methods. However, disparity
in the measured photometry is found in extended sources, when the target
extends beyond the fixed aperture. For extended sources, the variable radius
employed by SExtractor recovers a more reliable total flux estimate. For faint
sources, which were not necessarily detected above the required SExtractor
thresholds (see Atek et al. 2010 for details), fixed aperture photometry
provides reliable measurements using coordinates matched to the HST/WFC3
reference images. Therefore, upon inspection of each galaxy, the preferred
choice of photometric method is dependent on whether the galaxy is considered
to be extended in comparison to the PSF of the images and the size of the
fixed aperture.

Filter (∗) |  $\lambda_{\rm{central}}$ ($\mu$m) | Par-309 | Par-236 | Par-62 | Par-64
---|---|---|---|---|---
u (1) | 0.383 | $25.83$ | - | - | $25.97$
g (1) | 0.487 | $25.59$ | - | - | $25.97$
F475X (3) | 0.490 | - | - | - | 25.39
r (1) | 0.625 | $25.14$ | - | - | -
F600LP (3) | 0.719 | - | - | - | 24.88
i (2) | 0.768 | - | - | - | $25.18$
F814W (3) | 0.806 | 25.17 | - | - | -
F110W (3) | 1.152 | 26.05 | - | 25.38 | 25.95
F140W (3) | 1.392 | - | 25.29 | 24.74 | -
F160W (3) | 1.540 | 25.13 | - | - | 24.97
IRAC $3.6\mu$m (4) | 3.557 | 23.58 | - | 23.58 | 23.35
Table 2: HST UVIS, WFC3 and ground-based Sloan-like ancillary photometric data (taken by the WISP collaboration) available for each of the four WISPS fields observed. The $5\sigma$ 0.4′′-radius aperture depths are given for each, with the IRAC given for a larger 1.2′′-radius aperture due to the lower resolution. $*$ Imaging from: $1)$ Magellan-Megacam; $2)$ WIYN-Mini Mosaic; $3)$ HST; $4)$ Spitzer/IRAC ID_forsa | RA [deg] | DEC [deg] | orig_par_objb | v1.00_par_objc |  $z$_fors |  $z$_wisp_orig |  $z$_v1.00 | flagd
---|---|---|---|---|---|---|---|---
64_2_10 | 219.365463 | -1.828888 | 64_206 | – | 0.6588$\pm$0.0001 | 0.660$\pm$0.001 | – | 2
309_1_16 | 324.797699 | -38.433235 | 309_40 | 309_40 | 0.8123$\pm$0.0001 | 0.8109$\pm$0.0003 | 0.8156$\pm$0.0004 | 0
… |  |  |  |  |  |  |  |
Table 3: Identification of targets across various catalogues. ${}^{a})$ Throughout this work we refer to targets from the WISP field they were observed in (e.g. par 309) and the FORS2 mask and slit they were assigned to (e.g., 309_1_16). ${}^{b})$ Each target also has an original identification based on the early emission line catalogue in that field (e.g. par 309, object 40). ${}^{c})$ if a target appears in the v1.00 catalogue we also provide the identification from Battisti et al. (2024). ${}^{d})$ Finally, we provide a WFC3 single emission line flag ($2=$ single emission line reported, $1=$ multiple lines reported but only one $\geq 3\sigma$, $0=$ multiple $\geq 3\sigma$ lines). Available for the full sample as a machine readable table.  ID_fors | u | g | F475X | r | F600LP | i | F814W | F110W | F140W | F160W | IRAC
---|---|---|---|---|---|---|---|---|---|---|---
64_2_10 | 0.18$\pm$0.03 | 0.19$\pm$0.03 | 0.27$\pm$0.05 | - | 0.45$\pm$0.08 | - | - | 0.51$\pm$0.03 | - | 0.54$\pm$0.07 | 1.46$\pm$0.33
309_1_16 | 2.77$\pm$0.04 | 3.09$\pm$0.05 | - | 4.42$\pm$0.08 | - | - | 4.57$\pm$0.13 | 5.12$\pm$0.08 | - | 5.02$\pm$0.25 | 7.94$\pm$0.19
… |  |  |  |  |  |  |  |  |  |  |
Table 4: Ancillary photometry ($\mu$Jy), available for the full sample as a
machine readable table. Figure 1: The $H$-band (F160W, blue) and $JH$-band
(F140W, orange) AB magnitude distribution for the 85 objects in our sample.
$JH$-band is given instead of the $H$-band in WISP field 236 due to the
availability of imaging; see Table 2. 51$\%$ of galaxies have magnitude
fainter than AB=24 mag. Figure 2: The distribution of the rest-frame $V$-band
absolute magnitudes ($\sim$5500 Å) for the subset of targetted WISP galaxies
with observed photometric broad-band coverage (observed-frame F110W-F160W).
Absolute magnitudes are determined using the FORS2 spectroscopic redshift when
available, otherwise using the WISPS WFC3 spectroscopic redshift.

##  3 Results

The combination of HST/WFC3 slitless grism and VLT/FORS2 provides
spectroscopic coverage over a broad range from the observed-optical to near-
infrared, with complementary multi-band photometry constraining the broadband
continuum from the observed-optical into the mid-infrared. This breadth of
data provides coverage of key rest-optical emission lines over our redshift
range (e.g., [Oii]$\lambda\lambda 3727,29$, H$\beta$, [Oiii]$\lambda\lambda
4959,5007$ and H$\alpha$) which we will use to assess the validity of HST/WFC3
grism WISP line identifications and redshifts, correct WISP H$\alpha$ derived
SFR by estimating the dust extinction, and utilise line diagnostics and
photometry-derived stellar masses to assess the gas-phase metallicity and
interstellar medium (ISM) conditions for our galaxies.

###  3.1 Emission line identification and flux measurement

With the 2D and 1D FORS2 spectrum for each galaxy extracted, we visually
inspect each to identify all significant emission. Visual inspection
establishes 38 of 85 unique WISP targets display FORS2 emission lines (the
breakdown by field and mask is given in Table 6). We note that this FORS2
emission line detection rate is low and we emphasise that many of the single
line emitters followed-up were low S/N in the WISP grism spectrum and FORS2 is
being used to test the reality of these (see discussion in Section 3.2.1). As
a preliminary check before a more sophisticated redshift determination, a
simple overlay is created to mark the locations of expected [Oii], H$\beta$
and [Oiii] emission lines on the FORS2 2D spectra based on the WISP
spectroscopic redshift estimates for each galaxy. This provides immediate
visual confirmation that 36 galaxies have observed emission lines consistent
with the expected redshift, whereas 2 galaxies show emission lines
inconsistent with the WISP redshift (see Section 3.2 and Appendix B for
details). The FORS2 observed emission lines are typically the [Oii]λλ3727,29
doublet and often H$\beta+$ [Oiii]λλ4959,5007 . We will discuss redshift
validation further in Section 3.2.

The remaining 47 targets without obvious emission lines in the FORS2 spectrum
can be further separated into two categories. First, those where no emission
lines were predicted to lie in the FORS2 wavelength range (at $z>1.28$) based
on the WISP redshift estimates, which comprised 15 of the 85 galaxies
targetted, all 15 of which had no lines detected in our FORS2 spectroscopy.
Here, the lack of contradictory line detections in FORS2 supports the WISP
redshift estimate and line identification by ruling out alternative
redshift/line-identification solutions that would have placed emission in the
FORS2 wavelength coverage (although we caution this does not rule out the
possibility that a single-line detection in the HST/WFC3 WFSS is spurious).
Secondly, targets where we had expected emission lines to fall within the
FORS2 wavelength range (70 of our targetted sample, $z<1.28$) but no
detections were made (32/70), either due to the emission line flux being too
faint to be detected or due to misidentification of the WISP emission line (or
the WISP emission line being spurious), which we will discuss further in
Section 3.2.1.

The 1D science and noise spectra of the 38 targets with visually identified
FORS2 emission line detections are processed through the Penalized Pixel-
Fitting (PPXF) spectral fitting package (Cappellari, 2017) to fit a continuum
and emission line model to the spectra and to obtain emission line flux
measurements. Here the galaxy spectra are brought to the rest-frame using the
HST/WFC3 grism WISP redshift estimate. The galaxy continuum in these emission
line selected targets is usually non-dominant and a fourth order additive
polynomial is used to model the continuum; the individual emission lines are
modelled as either a single gaussian or a pair in the case of the
[Oii]$\lambda\lambda 3727,29$ doublet. The flux ratio between this pair is
tied to constraints set from atomic physics (Osterbrock & Ferland, 2006). Any
velocity offset exhibited by the emission lines allows the HST/WFC3 WFSS
redshift estimate to be refined by the FORS2 spectroscopy. The emission line
fluxes are given in Table 5.

###  3.2 Redshift validation

When a galaxy in a spectroscopic survey only has a single emission line
detected, determination of the line identification and redshift is ambiguous.
One goal of our optical spectroscopy follow-up is to validate the WISP
redshifts, especially for the 47/85 galaxies that only had a single emission
line detection in the HST/WFC3 WFSS.

Visual inspection of the 2D and 1D FORS2 spectra identified 38 of the 85
unique galaxies with significant line emission ($>3\sigma$). Of these 38, 36
galaxies had FORS2 emission line detections that supported their WISP
designated spectroscopic redshift, whilst 2 galaxies had FORS2 significant
line emission that was inconsistent with the expected redshift. Hence, in the
sub-set of cases where there was significant line detection in FORS2 (38/85,
45% of targetted objects) the tentative redshift from WFC3 was confirmed 95%
of the time (36/38). Where FORS2 was able to detect emission lines, there was
a very high success rate in confirming that the WISP redshifts are accurate,
although due to the lower WFC3 WFSS spectral resolution compared to the FORS2,
the FORS2 redshift is more precise.

Of the 38 galaxies with significant FORS2 line emission, 17 were cases when
the WISP redshift was based on only a single line detection (most commonly
attributed to H$\alpha$ and in one case [Oiii]). Here, the reliability of the
WISP spectroscopic redshift is less robust than cases when multiple emission
lines were detected, which could further constrain the redshift. The 2
galaxies with FORS2 detections inconsistent with the expected WISP
spectroscopic redshift both had only single line detections in WFC3, and
present catastrophic WISP misidentification. From the detection of multiple
FORS2 emission lines we determine new line identifications and redshifts for
these 2 galaxies. FORS2 ID 236_2_12 had an initial tentative WISP
spectroscopic redshift of $z\sim 0.36$ based on a single emission line assumed
to be H$\alpha$. However, FORS2 spectroscopy identified line emission of
H$\beta$, [Oiii] and H$\alpha$ consistent with $z=0.12$. With no standard
emission line expected at the WISP line wavelength (rest-frame 0.89$\mu$m
based on the FORS2 spectroscopic redshift), the WISP survey line detection
(S/N = 2.9) is determined to be spurious and may have been caused by a cosmic
ray or some detector artefact coincident with the dispersed slitless spectrum
of the galaxy. FORS2 ID 62_1_13 similarly had a single line detection
attributed to H$\alpha$ at $z\sim 0.62$ however, a clear FORS2 [Oii] doublet
is identified which determines a $z=1.13$ spectroscopic redshift. The WISP
detection (S/N = 6.1) lies coincident with a rest-frame wavelength of 4990 Å
based on the FORS2 redshift, which we identify as a being consistent with the
blended [Oiii]$\lambda\lambda 4959,5007$ doublet. This is a case of a single
detected WISP HST/WFC3 emission line being real, but mis-attributed to
H$\alpha$ rather than [Oiii]. Of the single-line emitters from WISP/WFC3 for
which we detect lines in FORS2, in 10% (2/17) of the cases the original
single-line in WFC3 must be [Oiii]$\lambda\lambda 4959,5007$, with 90% being
H$\alpha$.

In Figure 3 we first present the WISP spectroscopic redshift distribution
(left panel) for the complete WISP survey sample of galaxies in the four
target fields and the sub-sample that were followed up with our optical
spectroscopy. In the right panel of Figure 3, we present the updated redshift
distribution, considering the FORS2 spectroscopy, identifying how robustly
each sub-group has its redshift validated. In Appendix B we compare the
original catalogue redshift with the updated redshifts in Figure 23. In Figure
4, we present the Near-IR magnitude distribution, again identifying how
robustly each sub-group has its redshift validated.

####  3.2.1 Undetected emission lines

Given that a significant fraction of our sample did not display emission lines
in their FORS2 spectroscopy, despite the sufficient wavelength coverage (32/70
at $z<1.28$), we now consider whether this was expected. We note that of these
32, 26 were single line detections in the WFC3 spectroscopy and of the
remaining 6, only 3 had multiple lines detected at $>3\sigma$. In turn we now
examine whether the expected signal-to-noise of the three strongest rest-
optical emission lines ([Oii], H$\beta$ and [Oiii]) would be below the
$3\sigma$ detection threshold of FORS2. Hence, whether these non-detections
can be attributed to the line emission being too faint or to the HST/WFC3 WFSS
emission lines being misidentified or spurious.

To determine the expected observed flux for each undetected emission line, we
will utilise the line ratio between the average detected emission line flux of
H$\alpha$ and the average detected flux of the line in question, for the sub-
sample where both lines were detected. In this calculation we remove two
sources which were spatially extended compared to the FORS2 slit width, as
these would artificially increase the measured line ratio due to slit losses.
We require detections in both emission lines (H$\alpha$ and the line in
question) and a detection of at least one line in the FORS2 spectroscopy to
confirm the redshift. Within our sample there are 34 galaxies that meet this
criterion for detection of both H$\alpha$ and [Oii] lines. The H$\alpha$ and
[Oii] line flux ratio of the average observed line fluxes is $3.6\pm 0.7$. For
H$\beta$ there are 15 galaxies that meet these criteria with a measured
observed line flux ratio to H$\alpha$ of $6.0\pm 1.0$ (this is consistent with
the Balmer decrement presented in Section 3.3.2 where we also consider the
[Nii] contribution and stellar absorption). For [Oiii]$\lambda\lambda
4959,5007$, 24 galaxies meet these criteria with a measured observed line flux
ratio to H$\alpha$ of $1.5\pm 0.2$.

To calculate the expected signal-to-noise of each undetected line, the WISP
measured H$\alpha$ flux for each galaxy is divided by the appropriate line
flux ratio (see above) to estimate the corresponding observed flux. Then the
associated noise spectrum for each galaxy is used to estimate the noise over a
500 km s-1 aperture centred on the expected wavelength, determined from the
WISP grism spectroscopic redshift. Together these provide an estimate of the
expected S/N for each of the emission lines that were undetected in FORS2.

Out of the 32 galaxies without FORS2 detections but with WFC3 emission-line-
determined redshifts that predict emission lines to fall in the FORS2
coverage, 29 were expected to exhibit [Oii] with a S/N estimate ranging
between 4 and 43 (the remaining 3 galaxies were at redshifts or slit-mask
locations where [Oii] was not in the spectral coverage). The 17 galaxies
expected to exhibit [Oiii] had estimated S/N ranging between 5 and 57. Finally
for H$\beta$, the same 17 galaxies are estimated to exhibit a S/N in the range
of 2 to 21 for the observed line ratio, or up to a S/N between 5 to 44 for the
intrinsic line ratio of H$\alpha$/H$\beta$ (2.86 from Osterbrock 1989).
Therefore, we would have expected to observe significant line emission in the
FORS2 spectra for the majority of these objects, following the typical line
ratios of the FORS2 detected galaxies. We note that 26 of these 32 undetected
galaxies had WISP redshifts based on a single-emission line detection in WFC3.
Hence, for the majority of these galaxies we believe the WFC3 emission line
may have been spurious (e.g., a mistaken artefact within the grism imaging) or
have been mis-identified such that no lines should have been expected to fall
in the FORS2 coverage.

As a check, we stack the FORS2 spectra for the galaxies without FORS2 emission
line detections despite expectation. The stacking is performed by averaging
the linearised 1D FORS2 spectrum of each object. Due to the lower spectral
resolution of the WFC3 grism the redshift precision means the expected
location of the non-detected emission line may lie over a broad pixel range
($\sim 30$Å due to the precision of the redshift that could be constrained
from the WFC3 grism). We examine evidence for a flux excess over a $\pm 15$Å
wavelength range centred on the expected position, after subtracting a fit to
the continuum emission. We find no evidence at more than $2\sigma$ for a flux
excess in the stacked [Oii], [Oiii] or H$\beta$ spectra. We note that due to
the redshift uncertainty in WFC3 being much larger than that due to the FORS2
spectral resolution, the undetected emission line may fall over a large
wavelength (and pixel) range and this increases the noise in the stack and can
mask the benefits of improving the S/N of the individual spectra by stacking
the data. This stacking result supports that the WFC3 detected single-line
emission of these galaxies may not be genuine, or that the line identify is
incorrect, or the object in the direct-image associated with the spectrum
(required to set the wavelength zeropoint) was mis-identified.

Within our complete sample there are 43 single emission line galaxies in WFC3
where we expect lines to fall in our FORS2 coverage ($z<1.28$), with 15
(35$\%$) having their redshift confirmed. The inverse of this sets a maximum
potential false-detection rate of galaxies identified in the WFC3 WFSS with
only a single emission line to $<65$$\%$. This is a upper limit on the false
detection rate (i.e., spurious emission lines, false-positives) because it
includes cases when the WFSS line may be real but the emission line rest-
wavelength is mis-identified as well as cases when the WFSS line may be
spurious. We find that this upper limit to the single emission line false-
detection rate is roughly in line with that determined by Baronchelli et al.
(2020, 2021) of about $\sim 50\%$ using both supervised and unsupervised
machine learning models trained on the complete WISPS datasets. It is clear
that in WFSS surveys the factions of false detections among the single lines
is far from marginal.

####  3.2.2 Confirmation rates in the v1.00 public catalogue

Finally, when we restrict our sample to only those that appeared in the recent
v1.00 emission line catalogue, which had a higher S/N requirement, we find a
much higher success rate for redshift confirmation. Of 19 galaxies in v1.00
which we target, 13 have redshifts in the v1.00 emission line catalogue where
emission lines should be observable with FORS2. We confirm FORS2 line
detections in 11 out of 13, giving a confirmation rate of 85$\%$. The 6
galaxies at redshifts $z>1.28$, where no lines are anticipated to fall in
FORS2 wavelength coverage, show no emission lines in FORS2 as expected. Of the
19 galaxies targetted from the v1.00 catalogue, 5 had a single emission line
in WFC3. Of these, 2 have confirmed redshifts from FORS2, and 2 have WISP
redshifts beyond the range where we would expect to see line emission in the
FORS2 coverage ($z>1.28$), so of those single-emission line galaxies in the
v1.00 catalogue expected to have emission lines in FORS2 we have a 67% (2/3)
confirmation rate compared to 35% for the larger preliminary catalogue used
initially to choose targets (15 confirmed single emission line galaxies out of
43 at $z<1.28$). The remaining 1 single-emission-line galaxy out of 5 from the
v1.00 catalogue is likely to be spurious (a potential false-detection rate of
33%, compared with 65% for the original early catalogue, when we consider
galaxies at $z<1.28$). Here the detection rate is clearly shown to improve
with higher S/N thresholds in WFSS. However, we do note that there are 25
galaxies with FORS2 line detections which confirm the WISPS spectroscopic
redshift that do not appear in v1.00 (see Table 3), of which 12 were single
line emitters.

Figure 3: Left: The HST/WFC3 WFSS redshift distribution of the 85 galaxies
(red), out of the 138 WISP emission line detected sources (purple), that we
follow up with FORS2 spectroscopy. Right: The updated redshift distribution
based on the FORS2 follow-up (solid red, with updates shown in dashed). 38
galaxies (green) had FORS2 detected emission lines allowing their
spectroscopic redshifts to be validated or corrected. 32 galaxies (orange) are
predicted to exhibit emission lines within the FORS2 wavelength coverage but
none are detected in FORS2 at S/N$=3\sigma$ detection threshold. 15 galaxies
(blue) were not predicted to exhibit emission lines within the FORS2
wavelength coverage and the lack of contradictory lines help rule out lower
redshift solutions. Figure 4: Left: The Near-IR AB magnitude distribution of
the 85 galaxies in our sample (red), using either the $H$-band or the
$JH$-band depending on available imaging. Right: The near-IR AB magnitude
distribution coloured by the same redshift validation as in Figure 3. Galaxies
(green) that had FORS2-detected emission lines are typically brighter than
average, but still cover a broad magnitude range in F160W/F140W of 20$<AB<27$
mag.

###  3.3 Emission line flux corrections

In this sub-section we will consider the necessary corrections for the
observed emission line fluxes to recover line luminosities. The emission line
fluxes are presented in Table 5, and are available electronically555All the
tables presented in this work are available at
https://github.com/Kitboyett/Boyett_et_al_2024.

ID_fors | redshifta | [Oii]b | H$\beta^{\rm{b}}$ | [Oiii]b | H$\alpha^{\rm{b,c}}$ | [Sii]b | [Oii]b,d | H$\beta^{\rm{b,d,e}}$ | [Oiii]b,d | H$\alpha^{\rm{b,c,d,e}}$ | [Sii]b,d | $L_{\rm H\alpha}^{\rm b,c}$
---|---|---|---|---|---|---|---|---|---|---|---|---
64_2_10 | 0.6588$\pm$0.0001 | 2.9$\pm$0.2 | 1.7$\pm$0.1 | 9.1$\pm$0.3 | 7$\pm$1 | - | 15$\pm$1.2 | 7.1$\pm$0.3 | 31$\pm$1 | 18$\pm$4 | - | 12$\pm$2
309_1_16 | 0.8123$\pm$0.0001 | 43$\pm$7 | 15$\pm$3 | 92$\pm$4 | 56$\pm$2 | 5$\pm$1 | 220$\pm$37 | 61$\pm$14 | 320$\pm$13 | 160$\pm$5 | 13$\pm$3 | 180$\pm$6
… |  |  |  |  |  |  |  |  |  |  |  |
Table 5: Emission line measurements (fluxes: $10^{-17}$erg/s/cm2, Luminosity
$10^{40}$erg/s) for our full sample measured from FORS2 or taken from the
early WISP emission line catalogue. $a)$ Spectroscopic redshift from FORS2
detected line emission when available, otherwise set to the WFC3 redshift.
$b)$. Line measurement corrected for seeing. $c)$. H$\alpha$ measurements
corrected for [N ii] contribution. $d)$. Line measurements corrected for
reddening assuming $A_{\rm{H}\alpha}=1$ mag and the Calzetti et al. (2000)
extinction law. $e)$ H$\alpha$ and H$\beta$ corrected for Balmer absorption,
adopting 2 and 3Å EW corrections respectively from Domínguez et al. (2013).
Available as a machine readable table.

####  3.3.1 [NII] contribution correction for H$\alpha$ flux

The low spectral resolution of the WFC 3 WFSS means the H$\alpha$,
[Nii]$\lambda 6548$ and [Nii]$\lambda 6584$ emission lines are blended and the
WISP flux measurement therefore provides an upper limit to the H$\alpha$
emission. To obtain an estimate for the contribution from the two [Nii]
emission lines (which have a theoretical flux ratio of 3:1 between
[Nii]$\lambda 6584$ and [Nii]$\lambda 6548$, Osterbrock & Ferland 2006), the
[Nii]$\lambda 6584$ over H$\alpha$ ratio is estimated from the star-forming
abundance sequence in the redshift-dependent BPT diagnostic diagram from
Kewley et al. (2013b, equation 5). The star-forming abundance sequence
provides a [Nii]$\lambda 6584$/H$\alpha$ flux ratio as a function of the
[Oiii]$\lambda 5007$/H$\beta$ flux ratio under the assumption that our sample
consist of star forming galaxies. The mean value for the [Nii]$\lambda\lambda
6548,6584$ contribution to the total H$\alpha$ \+ [Nii]$\lambda\lambda
6548,6584$ flux is $0.18\pm 0.10$ for the sub-sample of 19 galaxies which had
[Oiii]$\lambda 5007$, H$\beta$ and H$\alpha$ detections, exhibiting a mean
redshift of $z=0.69\pm 0.34$. We also consider a plausible upper limit on the
[Nii]$\lambda$(6548 + 6584) (hereafter [Nii]) contribution to H$\alpha$ \+
[Nii] flux for this sub-sample, which we determine to be $0.26\pm 0.10$,
following the 0.1 dex upper boundary on the star forming abundance sequence
provided by Kewley et al. (2013a). For the remaining galaxies in the sample,
the H$\alpha$ flux is corrected for the [Nii] contribution using the mean from
this sub-sample (where [Nii] contributes a fraction 0.18 to the blended flux).
Our correction provides an updated estimate to the [Nii] contributions adopted
in previous WISP collaboration papers (Atek et al., 2010, 2011; Domínguez et
al., 2013; Colbert et al., 2013; Masters et al., 2014) which lie in the range
$4-20\%$, dependent on the H$\alpha$ equivalent width and stellar mass of the
galaxy. Our value for the [Nii] contribution is marginally larger than some
previous estimates, due to the availability of a redshift-dependent BPT star-
forming abundance sequence. Higher [Nii] contributions are found at higher
redshifts which may be due to a larger ionisation parameter, evolution of
metallicity or a different N/O abundance ratio (Faisst et al., 2018), whereas
the previous computations were all reliant on $z\sim 0$ galaxy diagnostics.

field $\&$ | Fors2 line | no FORS2 | no FORS2 | total
---|---|---|---|---
mask | detections | detections (high-$z$) | detections ($<S/N$) | targets
309_1 | 11 | 1 | 5 | 17
309_2 | 3 | 7 | 4 | 14
62_1 | 6 | 2 | 5 | 13
64_2 | 5 | 4 | 4 | 13
236_1 | 8 | 0 | 8 | 16
236_2 | 5 | 1 | 6 | 12
Totals | 38 | 15 | 32 | 85
Table 6: FORS2 follow-up detection rate split between each of the six observed
mask configurations.

####  3.3.2 Extinction correction and the Balmer Decrement

Figure 5: Balmer decrement relation with H$\alpha$ luminosity (left) and
stellar mass (right). Balmer lines corrected for seeing and [Nii]
contribution, we additionally correct the Balmer decrement for stellar
absorption. In both panels our detections are spilt into low (green, $z<0.7$),
medium (orange, $0.7<z<1.28$) and high (red, $z>1.28$) redshift bins, with
galaxies that have H$\beta$ detections below $2\sigma$ plotted as lower limits
on H$\alpha$/H$\beta$. Two galaxies are removed which had artefacts around the
H$\beta$ emission line in the spectroscopy. In purple diamonds, we present the
WISP sample from Domínguez et al. (2013) ($0.75\leq z\leq 1.5$). Left: Binned
data points (blue) show the luminosity ranges $\log_{10}(L_{\rm
H\alpha}/\rm{erg\,s}^{-1})$ of $41.0-41.5$, $41.5-42.0$ and $42.0-42.5$. Pink
dashed line shows the binned SDSS ($z\sim 0$) sample from Hopkins et al.
(2001). Right: Binned data points (blue) show the stellar mass ranges
$\log_{10}($M/M${}_{\odot})$ of $7.4-8.5$, $8.5-9.5$ and $9.5-10.5$. Pink
dashed line shows the binned SDSS ($z\sim 0$) sample from Garn & Best (2010).

Observation of the H$\alpha$ emission line in the WISP survey allows galaxy
properties including SFR to be measured. However, measurements of the SFR
based on H$\alpha$ luminosity alone may be underestimated due to dust
attenuation, which we wish to correct for. For the majority of our sample we
have wavelength coverage of the H$\alpha$ emission line in the HST/WFC3 WFSS
and also the H$\beta$ emission line, which falls in our FORS2 wavelength
coverage at $z\lesssim 0.7$, and in the G102 WFC3 grism at $0.7<z<1.4$. We
assume the intrinsic flux ratio between the H$\alpha$ and H$\beta$ emission
lines (the Balmer decrement) is $f($H$\alpha)/f($H$\beta)=2.86$, set by atomic
physics for Case B recombination for a temperature T$=10^{4}K$ and an electron
density $n_{e}=10^{2}$ cm-3 (Osterbrock & Ferland, 2006).

The flux ratio observed in galaxies is typically larger than this due to
wavelength dependent differential extinction, with the shorter-wavelength
H$\beta$ line typically more attenuated. In this section, we will use the
observed Balmer decrement from galaxies in our sample along with a Calzetti
extinction law (Calzetti et al., 2000) to determine and correct for the dust
extinction.

We note that since the H$\beta$ emission line flux is typically more than
three times weaker than H$\alpha$ it is frequently undetected (see Section
3.2.1). This happens even in the cases where we confirm the putative WISP
redshift from a single emission line in the slitless WFC3 WISP spectrum with
another line (typically [Oii] or [Oiii]) in the follow-up FORS2 spectroscopy.

To determine the Balmer decrement within our sample the measured H$\alpha$ and
H$\beta$ emission line fluxes must be corrected for the effects of [Nii]
contribution to the measured H$\alpha$ flux and the effect of stellar
absorption for both lines. First, the H$\alpha$ flux is corrected for
contamination from the [Nii] doublet, as described in Section 3.3.1. Secondly,
we correct for the intrinsic Balmer line absorption that occurs in the
photospheres of stars in these galaxies. The strength of this absorption
depends on the stellar population, and we follow Domínguez et al. (2013) who
study the dust properties of WISP galaxies and adopt their correction values
for the emission line rest-frame equivalent width of 3 Å for H$\beta$ and 2 Å
for H$\alpha$, which Domínguez et al. (2013) determine for their lowest
stellar mass sub-sample $M_{*}\approx 10^{8.5}\,M_{\odot}$ (which is
consistent with the mean stellar mass of our sample, described in Section
3.5.3). For this correction we assume a continuum slope flat in $f_{\nu}$
appropriate for ongoing star formation in the absence of significant reddening
(e.g., Wilkins et al., 2011).

The Balmer decrement is measured for the sub-sample of galaxies that have
detections $>2\sigma$ in both H$\alpha$ and H$\beta$ emission lines. For
galaxies with a robust redshift (i.e., confirmed through a FORS2 line
detection or multiple emission line detections in the WISP survey) but with a
H$\beta$ signal-to-noise below our detection threshold, a $2\sigma$ lower
limit to the Balmer decrement is derived using the 2$\sigma$ upper limit to
the H$\beta$ flux and we plot these limits for individual galaxies in Figure
5. We also stack the data in bins of H$\alpha$ luminosity by adding the
measured line fluxes from different galaxies (even if undetected in individual
cases) to get the average Balmer decrement for a sub-sample of galaxies. We do
not consider three galaxies that clearly have extended morphology beyond the
FORS2 1′′ slit-width, where the slit-losses would lead to an overestimate of
the Balmer decrement (these are noted in Table 5666FORS2 ID: 236_1_10, 62_1_16
and 309_1_5). Together the average Balmer decrement for the sub-sample of
galaxies with robust redshifts is $4.08\pm 0.45$. In Figure 5, the Balmer
decrement measurements and lower limits are plotted against their H$\alpha$
luminosity (corrected for [Nii] contribution). The individual galaxies are
colour coded by redshift and are also binned (closed blue circles) into three
H$\alpha$ luminosity regimes (log${}_{10}(L_{\rm H\alpha}/\rm{erg\,s}^{-1}$) =
41.0-41.5, 41.5-42.0 and 42.0-42.5). Two galaxies are removed from the
$42.0<log_{10}(L_{\rm H\alpha}/\rm{erg\,s}^{-1})<42.5$ bin, on account of
their WFC3 spectra exhibiting strong negative counts around H$\beta$ due to
data reduction artefacts777FORS2 ID: 64_2_15 and 236_2_16. The binned data lie
slightly below the local Balmer decrement - H$\alpha$ luminosity relation
(Hopkins et al., 2001) and are in broad agreement with the moderate redshift
($0.75<z<1.5$) observations made by Domínguez et al. (2013).

When splitting our stacks into bins of H$\alpha$ luminosity, we note a trend
that galaxies with higher H$\alpha$ emission line luminosity tend to have
higher Balmer ratios and hence more dust extinction. However, we note that our
lowest luminosity bin ($\log_{10}(L_{\rm
H\alpha}/\rm{erg\,s}^{-1})=41.0-41.5$) is almost exclusively comprised of
galaxies at $z<0.7$ with H$\beta$ falling in the FORS2 spectroscopy, but the
higher luminosity bins are mainly the higher redshift galaxies with H$\beta$
from the WFC3 WFSS. Hence the trend may either be due to line luminosity, or
instead a trend with redshift. Many models predict that dust should increase
with time (i.e. decrease with redshift), although how the dust extinction in
star forming regions evolves is less clear (e.g., Zavala et al. 2021 find the
contribution from dust obscured star formation to the total remains flat up to
$z\sim 2$). Our Balmer decrement results, binned in H$\alpha$ luminosity, are
slightly below the $z\approx 0$ work of Hopkins et al. (2001) from SDSS, who
also fit an extinction dependence on H$\alpha$ luminosity. However, to guard
against a possible selection effect with luminosity (in that it is easier to
detect the less-obscured emission lines), we also plot the observed Balmer
decrement as a function of stellar mass (right panel of Figure 5, see Section
3.5.3 for mass measurement). As also found by (Battisti et al., 2022) using a
larger WISP sample with WFC3 spectroscopy alone, our measured Balmer
decrements stacked in stellar mass bins are in approximate agreement with the
mass:reddening relation seen in low-redshift galaxies in SDSS Garn & Best
(2010), where we consider the SDSS fibre-region stellar mass (with $\log
M_{*}^{tot}\approx\log M_{*}^{fib}+0.5$) as used in Battisti et al. (2022).
Our results are consistent with the scenario where reddening increases with
stellar mass (as also found in WISP by Domínguez et al. 2013), although we
note that our small sample size and large error bars mean that the three bins
are also consistent with uniform reddening.

Although we find tentative evidence for a correlation between H$\alpha$
luminosity and extinction, we also note that each luminosity bin is consistent
within $1\sigma$ with an extinction $A(\rm H\alpha)=1$ mag, consistent with
the findings of Sobral et al. (2009), corresponding to an observed Balmer
decrement of 4.07. We note that the average Balmer decrement, stacking our
full sample of galaxies with robust redshifts, is $4.08\pm 0.45$. In order to
correct the emission line fluxes, later used in line diagnostic analysis
(Section 3.6), we assume a fixed extinction corresponding to this standard
value of $A($H$\alpha)=1$ mag. For a Calzetti et al. (2000) extinction law
this corresponds to $A$([Oii]) $\sim 1.77$ mag and
$A$(H$\beta),\,\,\,A$([Oiii]) $\sim 1.36$ mag for the other nebular emission
lines. We note that the continuum might be affected by a different level of
attenuation than the nebular lines (Calzetti et al., 2000), and we consider
this further in Section 3.5.2.

###  3.4 Identifying potential AGN

Emission line galaxies can be powered by star formation and/or AGN activity,
and although we do not have X-ray data by which to select AGN, we can still
address the relative contribution by looking at the line ratios of the
emission lines which relate to the hardness of the ionising spectrum. A BPT
diagram (Baldwin et al., 1981; Veilleux & Osterbrock, 1987) traditionally uses
[Nii] and [Oiii] forbidden lines in ratio with their counterpart (close in
wavelength) recombination lines H$\alpha$ and H$\beta$ to discriminate between
star formation and AGN as the source of photoionisation. However, for our
dataset, [Nii] is unusable in the low spectral resolution WFC 3 grism as it is
blended with H$\alpha$. Hence we use [Sii]$\lambda\lambda 6717,6731$
(hereafter [Sii]) as an alternative diagnostic to [Nii] (e.g., Kewley et al.,
2006). A soft ionising spectrum indicating a star forming radiation field
consists of low [Oiii]$\lambda 5007$/H$\beta$ and [Sii]$\lambda\lambda
6717,31$/(H$\alpha$+[Nii]) line flux ratios whilst Seyfert galaxies and LINERs
with harder ionising spectra occupy the high ratio region. Our galaxies are
plotted on the [Sii]-BPT diagnostic diagram in Figure 6, and we overlay the
$z\sim 0$ AGN/star-formation separation line diagnostic from Henry et al.
(2021) which is the theoretical maximum for SFG calculated using Cloudy (v17;
Ferland et al. 2017) models (see also Henry et al. 2018).

We have 35 galaxies where we cover all the lines in the [Sii]-BPT diagram.
This breaks down to 11 galaxies with ($>2\sigma$) detections in each of
H$\alpha$, [Oiii], [Sii], H$\beta$. There are 10 galaxies that have only [Sii]
undetected and 6 galaxies with only H$\beta$ undetected. The remaining 8 are
undetected in both [Sii] and H$\beta$. We plot 2$\sigma$ limits on the flux
ratios in the upper panel of Figure 6. In the lower panel of Figure 6 we
replace the limits on undetected H$\beta$ with an inferred flux based on the
H$\alpha$ flux, assuming a case B flux ratio and an assumed dust attenuation
of $A(H\alpha)=1$ magnitude with a Calzetti et al. (2000) extinction law
(Section 3.3.2), corresponding to $f($H$\alpha)/f($H$\beta)=4.07$ (where the
H$\alpha$ flux has had the estimated [Nii] removed, and both H$\alpha$ and
H$\beta$ have been corrected for stellar absorption, see Sections 3.3.1 and
3.3.2 respectively).

From this sub-sample, 29 of the 35 galaxies on our [Sii]-BPT diagram lie below
the SFG/AGN demarcation line at $z\sim 0$, although it should be noted that 10
of these 29 have lower limits on H$\beta$ that mean they are conceivably still
consistent with the AGN region (this falls to 3 if we use H$\beta$ fluxes
inferred from the measured H$\alpha$ emission line), whilst 19 (54%) are
confirmed as inconsistent with being AGN. The remaining 6 galaxies lie above
the diagnostic demarcation line in the region consistent with being dominated
by AGN, although 4 are consistent with the star forming region within the
uncertainties. We therefore determine that 33 of the 35 galaxies (94%) are
consistent with being star forming galaxies (either falling below the
demarcation line for $z\sim 0$ within the error bars, or with limits
consistent with the star forming region). Of the galaxies above the dividing
line, inspection of the F160W $H$-band WFC 3 images reveals that the two
inconsistent with being SFGs appear to be spatially unresolved (FORS2 ID:
309_1_2 & 309_1_6). We note that 309_1_6 also exhibited [Ne iii]$\lambda 3869$
emission, further evidence of a hard radiation field (although we note that 2
additional galaxies that are consistent with being SFGs also had [Ne iii]
detected).

In recent years it has been suggested that there is evolution with redshift in
the dividing line between SFG and AGN in the BPT diagram, in the sense that
the demarcation rises with increasing redshift, and this is particularly
prominent in the [Nii]-based BPT (e.g., Kewley et al., 2013b, who note that
this evolution may also be due to a larger electron density or a harder
ionising radiation field). However, Shapley et al. (2019) study the
[Sii]-based BPT diagram for a sample of galaxies from the MOSDEF survey at
$z\sim$1.5-2.3 (slightly higher redshift on average than in our sample), and
find that the evolution is less extreme for [Sii] than when using [Nii], which
they argue is attributable to two competing effects: a less significant
contribution from Diffuse Ionised Gas (DIG) leading to a lower [Sii]/H$\alpha$
ratio at higher-redshift, and an increased ionisation parameter which pushes
this line ratio in the opposite direction (higher [Sii]/H$\alpha$). Hence, the
net result is minimal overall evolution in the [Sii]-BPT diagram, and we adopt
the $z\sim 0$ dividing line as our AGN criterion.

The measurements of [Sii] from our WISP WFC3 spectroscopy are often low S/N,
and so we want another check on the presence of AGN. We also consider the
mass-excitation (MEx) diagnostic proposed by Juneau et al. (2011), where the
[Nii]/H$\alpha$ ratio of the original BPT diagram is replaced by the stellar
mass (on the grounds that the average stellar mass of a galaxy is related to
metallicity, from the mass-metallicity relation, see Section 3.6.4). This also
allows us to inspect the ionising conditions of the highest redshift galaxies
within our sample, where H$\alpha$ no longer fell within the HST/WFC3 WFSS
coverage. Plotting the stellar mass (which we describe in Section 3.5.3)
against [Oiii]$\lambda 5007$/H$\beta$ allows SFG to be separated from AGN, and
we present our MEx diagram in Figure 7, where we plot the low-redshift
dividing line, along with another division which may be more appropriate at
higher redshift (due to evolution in the mass-metallicity relation e.g.,
Newman et al. 2014; Coil et al. 2015; Kashino et al. 2019; Henry et al. 2021).
We adopt the AGN/star-formation separation in the MEx diagram from Coil et al.
(2015) who consider a sample of MOSDEF galaxies.

Within the MEx diagram, there are 6 galaxies with H$\beta$ detections
(diamonds in Figure 7) that lie in the $z\sim 0$ AGN region, although each of
these lies either inside or is consistent within their uncertainties of the
modified $z\sim 2$ SFG region. When undetected H$\beta$ flux limits are
replaced with the H$\alpha$ flux divided by 4.07 (that consistent with a
H$\alpha$ attenuation of 1 magnitude), 5 further galaxies lie above the $z\sim
0$ AGN/SFG separation line, although 4 are at least consistent with the SFG
region on the modified MEx diagram. Only one galaxy (FORS2 ID 309_1_2) is
clearly an AGN considering both MEx diagrams, this galaxy is also identified
as an AGN in the [Sii]-based BPT diagram.

In Table 7 we present the AGN candidates identified by the [Sii]-BPT and MEx
diagnostics, and report that only 2 galaxies are identified by both methods.
These 2 are also found to be unresolved in the F110W and F160W imaging,
suggesting that these are indeed AGN contaminants of our star forming sample.
We remove them from our sample for the remaining analysis. The remaining AGN
candidates are identified as being SFG in at least one of the methods with
many also being spatially resolved. We conclude that star formation is the
dominant ionising source in most of our emission-line-selected galaxies, with
only 2 out of 41 galaxies (which have sufficient data to be plotted on at
least one of the [Sii]-BPT or MEx diagrams) likely being AGN. For the
overwhelming majority of our sample, the H$\alpha$ emission is most likely
dominated by a SFG rather than an AGN.

FORS2 ID | Modified [Sii] BPT | MEx | Modified MEx | imaging/SED
---|---|---|---|---
309_1_2a | AGN | AGN | AGN | Compact
309_1_6a | AGN | AGN | AGN* | Compact
309_1_13 | AGN | SFG | SFG | Resolved
309_2_13 | AGN* | SFG | SFG | Resolved
309_2_1 | AGN* | SFG | SFG | Compact
64_2_10 | AGN* | SFG | SFG | Resolved
236_1_14 | AGN | - | - | Resolved
309_1_3 | SFG | AGN* | SFG | Resolved
309_2_4 | - | AGN | AGN* | Compact
309_2_5 | - | AGN | AGN* | Resolved
309_2_7 | - | AGN* | AGN* | Resolved
64_2_5 | SFG | AGN | SFG | Resolved
64_2_9 | - | AGN* | SFG | Compact
64_2_15 | SFG | AGN | SFG | Resolved
64_2_16 | - | AGN* | AGN* | Compact
62_1_14 | - | AGN | SFG | Resolved
Table 7: Potential AGN candidates meeting various selection criteria. We
consider the [Sii]-BPT diagram and the mass-excitation (MEx) diagram (where we
indicate if it meets the AGN threshold at $z\sim 0$ and also a modified
threshold which may be more appropriate at high redshifts). More marginal AGN
candidates marked with (∗) were consistent with the SFG region within their
uncertainties or had limits consistent with the SFG region due to non-
detections in the [Sii] emission line. Two galaxies, marked by (a), are
consistent with being AGN in both diagnostics and are removed from the sample
for the remaining analysis.

Figure 6: The [Sii]-modified BPT diagram to identify AGN candidates (which lie
in the region above the curve), using the Henry et al. (2021) separation curve
(red). In the two panels we treat non-detections ($\geq 2\sigma$) of H$\beta$
differently. Top: Galaxies without H$\beta$ detections are treated as
$2\sigma$ lower limits on the flux ratios. Bottom: Galaxies without H$\beta$
detections are plotted using $f$(H$\alpha$)/4.07 (that consistent with a
H$\alpha$ attenuation of 1 magnitude). Galaxies with H$\beta$ detections are
shown in diamonds (green, or orange when [Sii] is undetected), whilst galaxies
without detections in H$\beta$ are shown in circles (blue, or purple when
[Sii] is undetected). Galaxies without [Sii] detections are set to $2\sigma$
[Sii] upper limits for the flux ratios.

Figure 7: The mass excitation (MEx) diagnostic diagram shows that the ionising
radiation field in the majority of our sample is consistent with star
formation, rather than AGN activity. Top: galaxies without H$\beta$ detections
($\geq 2\sigma$, circles) are treated as $2\sigma$ lower limits on the line
flux ratios. Bottom: galaxies without H$\beta$ detections are plotted using
$f$(H$\alpha$)/4.07 (consistent with A(H$\alpha$)= 1 magnitude).

###  3.5 Star formation rates and stellar masses of the WISP galaxies

The star formation rate and stellar mass are two fundamental galaxy properties
that influence the observational characteristics of a galaxy, including the
luminosity, comparative broadband colour and nebular emission line strength.
Several indicators of the star formation rate have been used (see for example
the review by Kennicutt & Evans 2012) for a range of redshifts and galaxy
samples, and these have been combined to trace the evolution of the star
formation rate density in the Universe (e.g., Lilly et al., 1996; Madau et
al., 1996; Hopkins et al., 2003; Madau & Dickinson, 2014). The sample
selection from the HST/WFC3 WFSS favours galaxies with high luminosity
emission lines, and it is the expectation that these will exhibit high
specific star formation rates (sSFR). The reliance of the sample selection on
the detection of strong emission lines without the requirement for any
continuum detection is expected to allow a large range of stellar masses to be
observed, including low mass systems potentially missed in spectroscopic
surveys following up broad-band magnitude-limited samples. In this Section we
compare SFR estimates derived using three measurements: the H$\alpha$
luminosity; the rest-frame UV continuum luminosity; and through SED fitting to
the full broadband photometry. We also derived stellar mass estimates from the
SED fitting. The derived properties are shown in Table 8.

ID | SFR(UV) | SFR(H$\alpha^{\rm{a}}$) | SFR(SED) | M(SED) | Mv | H$\alpha^{\rm{a}}$ EW0 | metal(O32) | metal(R23)
---|---|---|---|---|---|---|---|---
64_2_10 | 1.70$\pm$0.33 | 1.49$\pm$0.27 | 1.01$\pm$0.29 | 8.03$\pm$0.23 | -16.85 | 300.0$\pm$58.0 | 8.33$\pm$0.02 | 7.88$\pm$0.25
309_1_16 | 24.54$\pm$0.76 | 27.99$\pm$1.34 | 29.27$\pm$2.65 | 9.07$\pm$0.11 | -19.69 | 306.2$\pm$9.4 | 8.41$\pm$0.04 | $<8.44$
… |  |  |  |  |  |  |  |
Table 8: Derived galaxy properties from emission line measurements and
photometric SED analysis, available for the full sample as a machine readable
table. Star formation rates are given in $M_{\odot}/yr$, BEAGLE SED derived
masses in log10(M/$M_{\odot}$) and rest-frame equivalent widths given in Å.
Metallicity is in $\log_{10}(O/H)$ where solar is 8.69 (Asplund et al., 2009).
a H$\alpha$ corrected for seeing, stellar absorption and [Nii] contribution

####  3.5.1 Spectroscopic star formation rate analysis

H$\alpha$ is one of many nebular emission lines whose luminosity is sensitive
to the star formation rate of a galaxy. H$\alpha$ is a recombination line of
atomic hydrogen which arises from the integrated stellar light from photons
below the Lyman-limit ($\lambda<912$ Å) which photo-ionise neutral hydrogen in
the ISM. The H$\alpha$ luminosity therefore provides a probe of the ionising
flux and is sensitive to the population of young massive stars, which have hot
photospheres and short lifetimes. Taken with a population synthesis model and
assumptions of the underlying initial mass function, a calibrated scaling
relation can be constructed between the luminosity of the emission line and
the star formation rate.

For our sample we derive the SFR using the H$\alpha$ fluxes corrected for
[Nii] contribution, stellar absorption and reddening (see Sections 3.3.1 and
3.3.2). The H$\alpha$ fluxes are converted to luminosities using the FORS2
emission line measured redshift or HST/grism emission line redshift when FORS2
had no line detections. To determine the SFR, we adopt the SFR - H$\alpha$
luminosity relation from Kennicutt & Evans (2012) (see also Murphy et al.
2011; Hao et al. 2011), which assumes a Kroupa (2001) IMF.

####  3.5.2 Star Formation Rates inferred from the rest-UV

The luminosity of the non-ionising UV continuum is sensitive to the stellar
population of a galaxy and towards shorter wavelengths it is increasingly
dominated by the emission from younger stellar populations. The rest-frame UV
continuum luminosity can be used as a probe of the underlying star formation
rate (e.g., Kennicutt & Evans 2012). We adopt the rest-frame 2800 Å UV
continuum luminosity ($L_{UV}$) as a probe of the star formation rate,
available across the majority of our redshift range. We utilise the Kennicutt
& Evans (2012) $L_{UV}$ \- SFR scaling relation (see also Murphy et al. 2011;
Hao et al. 2011), which assumes a constant star forming history (SFH) and a
Kroupa (2001) IMF. We note that the non-ionising rest-UV continuum is
sensitive to the star formation rate integrated over longer timescales
($\sim$100 Myr) than that probed by the H$\alpha$ (since the OB stars which
dominate the ionising flux have lifetimes of $<$10 Myr, e.g., Sullivan et al.
2001). Hence, scatter in the measured $L_{UV}$\- and H$\alpha$-derived SFR
(see Figure 8) could be attributable to different recent star formation
histories. UV wavelengths are also more sensitive to dust attenuation, which
could lead to scatter between the two SFR measurements.

Across our sample, the rest-frame 2800 Å has broadband filter coverage
spanning from the ground-based $r$-band for our lowest redshift galaxies to
the HST/WFC3 F110W band for our highest. To estimate the stellar continuum
luminosity ($L_{UV}$) from the broadband photometry, we first correct the flux
density for any contribution from emission lines (e.g., [Oii]$\lambda 3727$)
measured in either the HST/WFC3 WFSS or VLT/FORS2 spectroscopy. The flux from
any emission lines is subtracted from the filter flux density, weighted by the
filter transmission profile at the respective location of each line. For each
galaxy in our sample we determine $L_{UV}$ from the broadband magnitude of the
filter that contains the rest-frame 2800 Å based on the spectroscopic
redshift. We remove galaxies from this sub-sample if the rest-frame 2800 Å did
not fall within an observed filter or if it lies within 100 Å of the edge of
the filter where the filter response is minimal. The SFR is then computed
using the Kennicutt & Evans (2012) relation for these 41 remaining galaxies
out of the 85 observed with FORS2.

Our observed $L_{UV}$ measurements will underestimate the intrinsic luminosity
due to attenuation by dust. We correct the 2800 Å continuum for dust
extinction. In Section 3.3.2 we corrected the nebular emission line flux for
reddening by adopting a 1 magnitude attenuation ($A$(H$\alpha)$ = 1) along
with a Calzetti et al. (2000) extinction law. Like Wuyts et al. (2013), we
note the need for extra attenuation in nebular emission lines (e.g.,
H$\alpha$) compared to the continuum and we adopt the Calzetti et al. (2000)
parameterisation $E(B-V)_{star}=0.44E(B-V)_{gas}$. This parameterisation
accounts for the young O/B stars responsible for the UV continuum being within
their birth cloud and generates A${}_{2800}=1.29\rm{A}_{H\alpha}$ as given by
Equation 14 of Calzetti (2001)(we note that the attenuation at UV wavelengths
is much higher than optical wavelengths).

For 39 galaxies, both H$\alpha$-derived and $L_{UV}$-derived star formation
rates are available, and we present their comparison in Figure 8. We find good
agreement between the star formation rates derived from each method, with a
fitted slope of SFR($L_{UV}$) $\propto$ SFR(H$\alpha$) raised to the power of
$1.15\pm 0.10$, close to a linear relation. We find a scatter in the residuals
to be $0.33$dex. A similar power law slope is identified in Wuyts et al.
(2013) where, as in this work, a linear relation between $A_{cont}$ and
$A_{H\alpha}$ is assumed.

Figure 8: The H$\alpha$-derived SFR compared to the $L_{UV}$ (rest-frame 2800
Å) -derived SFR. Targets with FORS2 emission line detections, that can confirm
their redshift, are shown in red whilst those which were undetected in FORS2
are in grey. Both SFR measurements are corrected for dust assuming $A_{\rm
H\alpha}=1$ mag. The black line shows the 1:1 line. The best fit model for the
whole sample has a log slope of $1.15\pm 0.10$ and the sub-sample with FORS2
detections has a log slope of $0.98\pm 0.14$.

####  3.5.3 Stellar population fits

The available broadband photometry and emission line flux measurements allows
us to sample each target’s spectral energy distribution (SED) from which we
can constrain galaxy properties including the stellar population, stellar mass
and SFR. The composite spectrum of a galaxy is dictated by several factors
including the galaxy’s star formation history, initial mass function (IMF) and
dust extinction law. In this section we utilise the Bayesian analysis of
Galaxy SEDS (BEAGLE, version 0.24.5, Chevallard & Charlot 2016) to model the
SED of the subset of our sample with sufficient broadband coverage. We
therefore do not consider WISP survey field 236 which only has photometry in
the HST/WFC3 F140W filter and is unable to place constraints on the stellar
templates.

We fix the galaxy redshift to the spectroscopic redshift measured from either
the FORS2 or HST/WFC3 emission lines. We assume a star formation history that
is comprised of a declining exponential component and a burst. This reflects
that the emission line galaxies identified through the HST/WFC3 WFSS are star
forming galaxies (typically with high sSFR, indicative of a burst). We assume
a Calzetti et al. (2000) dust attenuation law and Chabrier (2003) IMF (which
finds near identical stellar masses and SFR results to the Kroupa 2001 IMF
e.g., Chomiuk & Povich 2011, which we adopted for both the H$\alpha$\- and
$L_{UV}$-derived SFRs for consistency). We input flux densities and filter
transmission curves for each broad-band, along with the emission line fluxes
and wavelengths from our spectroscopy. We do not remove the flux contribution
from emission lines in the broadband photometry as this is considered as part
of the modelling.

We fit a total of seven parameters in BEAGLE: stellar mass, stellar age,
characteristic star formation timescale (the exponential component), SFR (the
burst), stellar metallicity, effective dust attenuation, and effective galaxy-
wide ionisation parameter. We freely vary the ionisation parameter so the
emission line fluxes can better constrain the spectral fits. A burst component
is included for physical reasons while also enabling better identification of
multi-modal solutions. Within the SED fitting, the derived stellar mass acts
as a free parameter used to constrain the normalisation of the composite
synthetic galaxy stellar population spectrum. In Figure 9 the BEAGLE SED
derived mass distribution for the 56 galaxies with sufficient broadband
photometry to constrain the stellar population is presented (excluding field
236 which only had photometry available in F140W). In particular, the
availability of Spitzer/IRAC channel 1 photometry (3.6$\mu$m) for three of our
four fields gives us the rest-frame continuum at $>1\mu$m, which is more
sensitive to the underlying stellar mass than recent star formation (unlike at
shorter wavelengths), and improves our measurement of the stellar mass. We
note that of the 56 galaxies covered by Spitzer, 14 are undetected down to
$2\sigma$ limits of AB=24.2-24.5mag, and these are consistent with being very
low mass systems ($M_{\rm stellar}<10^{8}M_{\odot}$).

With a median mass of $\log_{10}(M/M_{\odot})=8.94$ and a dynamic range of
$7<\log_{10}(M/M_{\odot})<11$, our sample reaches lower masses and is
typically fainter on average than broadband-magnitude-limited spectroscopic
surveys e.g., VVDS (Garilli et al. 2008; Le Fèvre et al. 2005, see Section
3.7). We note that due to the requirement for the galaxies to be detected in
the WISP survey direct imaging, to calibrate the wavelength of the emission
lines, the lowest mass galaxies may still be missing from our sample.

We additionally use our SED fitting to estimate the SFRs of our sample, and in
Figure 10 we present their comparison to our H$\alpha$-derived SFRs. We find
reasonable agreement between the two methods, with a fitted power law slope of
1.05$\pm$0.08 (1.40$\pm$0.10 when we consider only the FORS2 detected sub-
set). We find a scatter in the residuals to be $0.30$dex, similar to that
found by Reddy et al. (2015) (0.34dex) in the comparison of SED- and
H$\alpha$-based SFR estimates. We also determine an offset from the 1:1 line
of 0.21$\pm$0.05 dex compared to the H$\alpha$-derived SFRs, which we put down
to the difference in underlying assumptions within the SFR calibrations
between Kennicutt & Evans (2012) and BEAGLE (e.g., IMF, mass range,
metallicity).

Figure 9: Stellar mass distribution, derived using BEAGLE SED photometric
fitting code. This includes all galaxies excluding those from field Par236
where there was insufficient photometric data points to constrain the SED.
Figure 10: The H$\alpha$-derived SFR compared to the SED-derived SFR. Targets
with FORS2 emission line detections, that can confirm their redshift, are
shown in purple whilst those which were undetected in FORS2 are in grey. The
black curve shows the 1:1 line. The best fit model for the whole sample has a
log slope of $1.05\pm 0.08$ with an offset of 0.21dex, while the FORS2
detected sub-sample has a steeper log slope of $1.40\pm 0.10$. Two galaxies
have been removed due to having significantly underestimated SFRs which may
indicate AGN contamination, see Section 3.4

####  3.5.4 Star forming main sequence

Figure 11: The main sequence, H$\alpha$-derived star formation rate against
SED-derived stellar mass. H$\alpha$-derived SFR are adjusted for seeing, [Nii]
contribution, stellar absorption and reddening corrections. Grey dashed lines
indicated lines of constant sSFR. Over a range of redshifts we over-plot the
literature main-sequence from Schreiber et al. (2015) (solid), Speagle et al.
(2014) (dashed) and Santini et al. (2009) (dot-dashed). Our emission line
selected galaxies, colour coded by redshift, typically lie above the main-
sequence.

Galaxies exhibit a relation between their stellar mass and star formation
rate, commonly known as the star forming main sequence, which has been studied
in great detail from local redshifts out to beyond $z>4$ (e.g., Speagle et
al., 2014; Renzini & Peng, 2015; Schreiber et al., 2015; Battisti et al.,
2022). Most commonly the main-sequence is parameterised with a log-space slope
and intercept, with the redshift evolution mainly affecting the normalisation
of the relation in line with the increasing SFR density with redshift (e.g.,
Madau & Dickinson, 2014). We present the stellar mass - H$\alpha$ derived SFR
‘main-sequence’ in Figure 11 for the subset of our sample which have measured
H$\alpha$ fluxes. We over-plot the main-sequence from three studies over a
redshift range $0<z<2.5$ (Speagle et al., 2014; Schreiber et al., 2015;
Santini et al., 2009). Galaxies within our sample lie above the main-sequence
of the literature curves at the corresponding redshift, matching the
expectation that the emission line selected galaxies in the HST/WFC3 WFSS
exhibit high sSFR, as one would expect with an increasing SFR, such as a
burst. The overall trend of our sample is flatter than the literature main-
sequence due to the Eddington bias imposed by our selection on strong
H$\alpha$ emitters. At low masses, only those galaxies with the highest SFR
produce sufficient H$\alpha$ luminosity to make it into our selection. This
selection-driven flattening of the main sequence has been reported for surveys
that select on SFR-sensitive proprieties, such as surveys selecting on strong
emission lines or UV continuum selections (e.g., Battisti et al., 2022;
Cochrane et al., 2018; Rodighiero et al., 2014, 2011; Erb et al., 2006).

###  3.6 Determination of Metallicity from Emission Lines

One of the key ISM properties that can be inferred from our observations is
the gas-phase metallicity, and in this Section we will derive the gas-phase
oxygen abundance from two different line-ratio diagnostics. Using this, we
will investigate the relation between the metallicity and the stellar mass of
the galaxies in our emission-line selected sample.

The observed metallicity as measured from the gas-phase oxygen abundance is
sensitive to the galaxy’s stellar population, star formation history and
history of gas inflows and outflows. The chemical enrichment of the ISM
reflects the star formation history, with metal-enriched gas returned to the
ISM over time through stellar ejecta and explosions. The degree of enrichment
of the ISM can be diluted by the flow of cold gas (typically of lower
metallicity, and perhaps pristine) from the inter-galactic medium (IGM) or
circum-galactic medium (CGM) into the galaxy. Outflows of chemically-enriched
gas being ejected from the galaxy driven by supernovae or black hole feedback
may also alter the ISM metallicity (e.g., Lilly et al., 2013).

####  3.6.1 Metallicity Determinations using the R23 and O32 Diagnostics

The wavelength range available from the combined WFC3 and FORS2 spectroscopy
provides coverage of metallicity-sensitive nebular emission lines, in
particular the [Oii]$\lambda\lambda 3727,3729$ and [Oiii]$\lambda\lambda
4959,5007$ doublets. In this Section we will utilise these strong oxygen
emission lines along with empirical calibrations of the gas-phase oxygen
abundance in star-forming galaxies to derive the metallicity of our sample.
Alternative approaches include the measurement of stellar metallicity rather
than the gas-phase (often using absorption lines, e.g., Cullen et al. 2019) or
“direct methods" to determine gas-phase metallicity based on electron
temperature measurements using auroral emission lines (e.g., Sanders et al.,
2016; Curti et al., 2023b; Laseter et al., 2024). However, our spectra from
WFC3 and FORS2 are insufficiently deep to achieve good detections of
absorption lines or weak auroral emission lines, and hence we can only use
strong-line metallicity diagnostics for our sample.

The flux ratio of recombination emission lines (e.g., H$\alpha$, H$\beta$) to
forbidden collisional emission lines (e.g., [Oiii]$\lambda 5007$,
[Oii]$\lambda 3727$, [Nii]) is sensitive to the gas-phase metallicity and
ionisation conditions of the ISM. Standard nebular line flux ratios R2 =
f([Oii]$\lambda 3727,3729$)/f(H$\beta$) and R3 = f([Oiii]$\lambda
5007$)/f($H\beta$) and the combination of these by Pagel et al. (1979) into
R23 = f([Oii]$\lambda 3727,3729$ \+ [Oiii]$\lambda 5007,4959$)/f(H$\beta$) are
frequently used as strong-line metallicity indicators. However, these
empirically show non-monotonic behaviour (i.e., multiple metallicities can
exhibit the same diagnostic value) and, traditionally, a second line
diagnostic is introduced to break the degeneracy (e.g., Alloin et al. 1979;
Pagel et al. 1979; Kewley & Dopita 2002; Maiolino et al. 2008; Sanders et al.
2016; Strom et al. 2017). Many works have noted that the excitation conditions
in high redshift galaxies are very different from galaxies and HII regions at
$z\approx 0$ (e.g., Masters et al., 2014; Strom et al., 2017), and the strong-
line metallicity calibrations depend on the ionisation conditions (e.g.,
Kewley et al., 2013b). Typically, the metallicity indicator O32 =
f([Oiii]$\lambda 5007$)/ f([Oii]$\lambda\lambda 3727,29$) or the
f(H$\alpha$)/f([Nii]$\lambda 6583$) line flux ratios are used as they are
sensitive to the ionisation conditions of the ISM. Since [Nii] is blended into
the H$\alpha$ emission line at the spectral resolution of the HST/WFC3 WFSS,
and the nearby [Sii]$\lambda\lambda 6717,31$ doublet is often at very low
signal-to-noise in our WFC3 spectra, we use the O32 diagnostic (rather than
[Nii]) to break any degeneracy of the R23 metallicity indicator.

We utilise the Curti et al. (2017) empirically-calibrated metallicity
diagnostics for R23 and O32 to derive the metallicities for galaxies in our
sample. Curti et al. (2017) use the direct temperature method to measure the
metallicity of SDSS galaxies and of individual low-metallicity candidates,
from which they construct strong emission line – metallicity calibrations
using both R23 and O32.

We additionally determine a highest likelihood metallicity. Here, we combine
the metallicity estimates with associated Gaussian uncertainties from the
Curti et al. (2017) R23, O32 and R3 metallicity indicators to create a
posterior likelihood distribution. The peak of the likelihood and the 68%
confidence intervals of the distribution give a best estimate for the
metallicity.

The metallicities for the galaxies in our sample are presented in Table 8. We
present the line diagnostic R2-R3 in Figure 12 and R23-O32 in Figure 13 for
the individual galaxies within our sample (colour coded by redshift), and
compare these with the low redshift results from SDSS, and the empirical
metallicity calibration from Curti et al. (2017). Henry et al. (2013, 2021)
also analysed the metallicity of a different sub-sample of galaxies from the
WISP survey, based on the WFC3 spectra alone and focusing on higher redshifts
than in this paper where all the lines [Oii], H$\beta$ and [Oiii] are covered
by the HST/WFC3 WFSS. Our current paper can explore the metallicities of WISP
galaxies down to lower redshift thanks to our VLT/FORS spectroscopic follow-up
at shorter wavelengths.

Figure 12: [Oii] vs [Oiii] diagnostics normalised by H$\beta$, for the sub-
sample of 23 galaxies that have detections in all of [Oii], [Oiii] and
H$\beta$, split into three redshift bins. The over-plotted Curti et al. (2017)
strong-line diagnostic curve (colour coded by metallicity) indicates that the
WISP galaxies generally lie at sub-solar metallicities, with a trend of
decreasing metallicity with increasing galaxy redshift. A heat map of SDSS SFG
density at $z\sim 0$ is under-plotted, taken form Curti et al. (2017). Figure
13: O32 against R23 diagnostic, for the sub-sample of 23 galaxies that have
detections in all of [Oii], [Oiii] and H$\beta$, split into three redshift
bins. The over-plotted Curti et al. (2017) strong-line diagnostic curve
(colour coded by metallicity) indicates most lie at sub-solar metallicities,
with a trend of decreasing metallicity with increasing galaxy redshift.

The diagnostics diagrams in Figures 12 & 13 show measurements from individual
galaxies where the [Oii], [Oiii] and H$\beta$ emission lines are all detected
at $S/N>2$. We note that we have removed one galaxy (FORS2 ID: 309_2_18) which
has a large spatial extent and where the FORS2 slit spectrum would not capture
the full flux from the [Oii] emission line, and after removing this one object
we have 23 galaxies with individual measurements, of which 18 also have
H$\alpha$ flux measurements. We also consider galaxies where individual lines
are undetected ($<2\sigma$) by combining the emission line fluxes from several
galaxies together in a stacking analysis. We stack our galaxy spectra, so that
sources with fainter emission lines are also considered. We generate several
sub-samples and scaling schemes, and these are shown in Figures 14 & 15.
First, we perform a straight average of the emission line fluxes (which would
typically minimise the noise, but would give equal weight to low-luminosity
galaxies at lower redshift and higher luminosity galaxies at greater redshift
with the same observed line flux). Secondly, we perform a straight average of
the emission line luminosity, so as not to penalise higher redshift sources.
Next, we considered a stack where we normalise the line luminosities by the
stellar mass before averaging. Finally, to ensure that we are not dominated by
a small number of very bright sources, we normalise the individual line
luminosities before averaging such that the integrated line luminosity from
H$\alpha$ was the same (where the H$\alpha$ luminosity is a proxy for the star
formation rate, and has been corrected for [Nii], reddening and stellar
absorption, as described in Section 3.3.2).

In this stacking, we only include galaxies with faint emission line
measurements ($<2\sigma$) if an accurate redshift is available from the
higher-spectral-resolution FORS2 spectrum, which enables us to accurately
locate the wavelength of the emission line in the extracted spectra. For each
emission line of interest, we sum the line fluxes, luminosities or the
luminosities after normalising by the stellar mass or H$\alpha$ luminosity,
and take the ratios of the summed fluxes for different samples to plot on the
diagnostic diagrams. For inclusion in the H$\alpha$ luminosity-normalised
stacked spectrum we require each galaxy to have H$\alpha$, H$\beta$, [Oii] and
[Oiii] coverage across our FORS2 or WFC3 spectroscopy, which results in a
sample of 30 galaxies, 15 of which have $S/N<2$ in one or more of these
emission lines (typically H$\beta$). The other 15 galaxies entering the sample
for the stacking analysis are a sub-set of the 23 individual objects plotted
in Figures 12 and 13 with five galaxies excluded as H$\alpha$ was not covered
by the WFSS at their redshift and three excluded as they were spatially
extended and the [Oiii], H$\beta$ & [Oii] line fluxes determined from FORS2
will be subject to slit losses compared to the H$\alpha$ line measured from
the HST/WFC3 WFSS (see Section 3.3.2). Our sample covers a broad redshift
range and to study any evolutionary trend we consider sub-samples of objects
binned by redshift (low $z<0.7$ and medium $0.7<z<1.28$). We note that there
are only two galaxies in the sample at $z>1.28$ that meet our criteria for the
stacked sub-samples. We additionally split our stacking sub-samples by
H$\alpha$ rest-frame equivalent width, which is sensitive to the presence of
bursty star formation and young stellar populations. We wish to test if the
ISM conditions depend on the H$\alpha$ rest-frame equivalent width,
$EW_{0}$(H$\alpha$), and we create sub-samples888There are 7 galaxies in the
low-redshift low-H$\alpha$ EW stack, 2 galaxies in the low-redshift
high-H$\alpha$ EW stack, 8 galaxies in the medium-redshift low-H$\alpha$ EW
stack, and 11 galaxies in the medium-redshift high-H$\alpha$ EW stack  of
galaxies with $EW_{0}$(H$\alpha$)$<100$Å and $EW_{0}$(H$\alpha$)$>100$Å
(corrected for [Nii] and stellar absorption). We note that the high-
equivalent-width galaxies identified in the WISP WFSS may have been missed in
traditional broad-band selected spectroscopic galaxy surveys, which we will
discuss further in Section 3.7.

The medium redshift - low H$\alpha$ equivalent width sub-sample of 8 galaxies
exhibited no H$\beta$ detections, even in the stack, so we plot instead
$2\sigma$ limits for H$\beta$. The stacks of these sub-samples are shown in
Figures 14 and 15, with the results of Curti et al. (2017) at low redshift
shown for comparison. The stacks of our galaxies in each of our various sub-
samples all lie on or near the locus of SDSS $z\sim 0$ galaxies. We note that
each of our sub-samples is consistent with being sub-solar metallicity.

In recent years concern has been raised over the contribution of line emission
from the Diffuse Ionised Gas (DIG) affecting the metallicity inferred from the
strong-line diagnostic ratios (e.g., Sanders et al., 2017; Vale Asari et al.,
2019). In local galaxies the DIG can be responsible for 30-60% of the
H$\alpha$ line emission (e.g., Zurita et al., 2000). Sanders et al. (2017)
present a correction for DIG contamination involving the [Nii] emission line.
Since our observations do not recover the [Nii] line emission flux, we do not
apply this DIG correction, but we note that at the high redshifts of our WISP
galaxies ($z\sim 1$) the contamination from the DIG drops to $<$20% (Sanders
et al., 2017).

Figure 14: As in Figure 12, the line diagnostic [Oii] vs [Oiii] normalised by
H$\beta$ plot for sub-samples of galaxies binned by redshift and H$\alpha$
rest-frame EW. Four different weighting schemes are plotted, as in the legend.
Since the medium-$z$ low-EW sample of 8 objects had no H$\beta$ detections,
even in the stack, we present the H$\beta$ $2\sigma$ limit. Figure 15: As in
Figure 13, the line diagnostic O32 vs R23 plot for sub-samples of redshift and
H$\alpha$ rest-frame EW (as in Figure 14).

####  3.6.2 Metallicity trend with redshift

As apparent from Figures 12-15, we find a trend that metallicity, as measured
from the Curti et al. (2017) calibration, decreases with increasing redshift.
This redshift evolution reflects changes in the conditions of HII regions,
although a changing contribution of the DIG at different redshifts may also
contribute to apparent evolution of the diagnostic ratios. This trend with
redshift is supported by previous surveys: our low redshift sample lies
consistently within the R23 and O32 region occupied by the $0.5<z<1$ sample of
Lilly et al. (2003) and our medium and high redshift galaxies are consistent
with the higher redshift $z\sim 2-3$ sample from Cullen et al. (2014), which
exhibit a higher ionisation parameter (higher O32 and R23 values) indicative
of a harder ionising radiation field than local galaxies. This supports the
conclusions of Cullen et al. (2014), Hainline et al. (2009) and Nakajima et
al. (2013) whose higher-redshift samples ($z\sim 2$) are systematically offset
to higher O32 than low-redshift SDSS galaxies. Strom et al. (2017) and
Maiolino et al. (2008) at even higher redshift ($z\sim 3$) show offsets to
still larger values of R23 and O32. These results at higher redshift are in
broad agreement with our highest redshift WISP galaxies. The rise of
[Oiii]/H$\beta$ with redshift is often attributed to a rise in the ionisation
parameter, which could be driven by the changing metallicity, age and geometry
of the stellar population in HII regions with redshift (e.g., Kewley et al.,
2015; Jaskot et al., 2019).

####  3.6.3 Metallicity trends with H$\alpha$ Equivalent Width

We find that galaxies exhibiting a high rest-frame equivalent width of
H$\alpha$ ($>100$Å) typically have higher O32 values (and hence lower
metallicities on the Curti et al. 2017 calibration) than the low-EW galaxies
at similar redshifts, which agrees with previous studies who find a positive
trend between the equivalent width of Balmer lines and the O32 line ratio
(e.g., Kewley et al. 2015 at $0.2<z<0.6$ and Reddy et al. 2018 at
$1.6<z<2.5$). As can be seen in Figure 14, there is a dramatic difference in
the [Oiii]/H$\beta$ line flux ratio (and similarly in both the O32 and R23
ratios in Figure 15) going from low-EW of H$\alpha$ to high-EW in the low-$z$
sub-samples, with the higher-ionisation [Oiii] line becoming more dominant
compared to [Oii] for the galaxies with high EW H$\alpha$. This trend is
driven by a higher ionisation parameter at higher EWs, indicative of a young
stellar population and high sSFR due to the relative abundance of young
ionising stars to older non-ionising stars (Mingozzi et al., 2020; Kaasinen et
al., 2018; Kewley et al., 2015)

####  3.6.4 Metallicity trends with stellar mass

The metallicity of star forming galaxies is typically found to increase with
their stellar mass. This trend, the “mass-metallicity relation", has been well
studied observationally over a broad redshift range (e.g., Tremonti et al.
2004 at $z\sim 0.1$; Yabe et al. 2014 at $z\sim 1.4$; Revalski et al. 2024 at
$z\sim 1-2$; Henry et al. 2013 at $z\sim 2$; Sanders et al. 2018 at $z\sim
2.3$; Maiolino et al. 2008 at $z\sim 3.5$; Curti et al. 2023a at $z\sim
3-10$). The mass-metallicity relation can be motivated theoretically and may
reflect different levels of star forming chemical enrichment and regulation
driven by secular processes including gas inflows and outflows, such as in the
bathtub model of Lilly et al. (2013), with outflows more efficiently removing
material at lower galaxy stellar masses (Kobayashi et al. 2007, see also
models by Forbes et al. 2014). At a fixed mass, galaxies at higher redshifts
are typically observed to exhibit lower metallicities (see for example the
review by Maiolino & Mannucci 2019). Within this redshfit evolution the
observed shape of the mass-metallicity relation remains roughly constant.
These observational results have also been recovered in theoretical chemical
evolution models (e.g., Tinsley, 1980) and in high resolution hydro-dynamic
simulations which trace the evolution of chemical enrichment (e.g., Taylor &
Kobayashi, 2016; Torrey et al., 2018; De Rossi et al., 2017).

Here we compare the derived stellar masses (see Section 3.5.3) to the
metallicity of the galaxies within our sample. We present the mass-metallicity
relation for the two gas-phase metallicities derived using the R23 and O32
line diagnostics, shown in Figure 16 colour coded by the derived star
formation rate, and in Figure 17 colour coded by the redshift. In Figure 18,
the highest likelihood metallicity MZR is presented with redshift and SFR
colour coding. We over-plot three local observed relations derived from SDSS
samples, first by Tremonti et al. (2004) who derived metallicities using
strong-line ratios, Curti et al. (2020) who derived metallicities using direct
temperature methods and Sanders et al. (2017) who also use a direct
temperature method and adjust their relation to correct for DIG. Our
metallicities come from the O32 and R23 strong-line method which are
calibrated against the direct temperature method by Curti et al. (2017, 2020).
Additionally we over-plot two higher redshift samples; Ly et al. (2016) at
$0.5<z<1.0$ who use direct temperature methods to derive their metallicities,
and the binned data of Henry et al. (2021) at $z\sim 1.9$ who use strong-line
derived metallicities (and find consistency with Sanders et al. 2018 at $z\sim
2.3$ who use direct temperatures methods).

The mass-metallicity relation in our sample becomes very apparent when we bin
our galaxies by stellar mass (Figures 16 and 17), and individually we find
that our data points lie typically in between the $z\sim 0.1$ and $z\sim 1.9$
mass-metallicity trends of Tremonti et al. (2004) and the high-$z$ WISP sample
of Henry et al. (2021). Within the scatter of our data we find a trend that
higher redshift galaxies exhibit a lower metallicity at a given mass, as shown
by the colour-coding of the individual data points in Figure 17. This trend is
found in both the O32 and R23 diagnostic derived metallicity values.

Many studies have probed dependencies on the scatter within the mass-
metallicty relation, which led to the development of the Fundamental
Metallicity Relation (FMR, Mannucci et al. 2010) where the scatter is thought
to be driven by the SFR of the galaxies (see also, Tremonti et al. 2004, Lara-
López et al. 2010, Hunt et al. 2012). However, observationally the FMR is not
consistently detected within galaxy samples (e.g., Sánchez et al. 2017;
Barrera-Ballesteros et al. 2017, c.f., Cresci et al. 2019) and some work has
claimed that the FMR correlations may arise from observational systematics,
for example calibration uncertainties in nebular emission line metallicity
diagnostics, (Telford et al., 2016), or slitloss effects from fibre/slitmask
spectroscopic surveys compared to integral field spectrograph results
(Barrera-Ballesteros et al., 2017). In high resolution hydro-dynamic
simulations (e.g., De Rossi et al., 2017; Torrey et al., 2019), agreement with
the empirical form of the FMR has been found. The anti-correlation between
metallicity and SFR at a fixed stellar mass in the FMR may arise from the
joint dependency of the SFR and metallicity on the gas fraction $M_{HI}/M_{\rm
stellar}$ (e.g., Bothwell et al., 2013). A galaxy with a plentiful reservoir
of pristine gas (a high gas fraction) may fuel a large SFR and has a
corresponding low metallicity. After a period of star formation the SFR will
decrease as the reservoir becomes depleted (a decreasing gas fraction) whereas
chemical enrichment from the preceding star forming episode will increase the
metallicity. The similarity of the time-scale of the SFR and metallicity
variability drives the observable anti-correlation in the two galaxy
properties (Torrey et al., 2018).

To investigate the possible existence of the FMR, in Figure 16 we colour-code
by the derived SFR (similar to Maiolino & Mannucci 2019 figure 22), using our
H$\alpha$-derived SFRs for galaxies with detected H$\alpha$ and the
$L_{\rm{UV}}$-derived SFR for those at higher redshifts where H$\alpha$ was
not available (which we have shown to be comparable methods in Figure 8). In
the mass-metallicity diagram based on the O32 diagnostic we see an obvious
trend in the mass-metallicity relation, in that low-SFR galaxies have higher
metallicities than high-SFR galaxies of the same stellar mass. The trend is
less obvious when we use R23-based metallicities, because our H$\beta$
detections (which go into the R23 diagnostic) are often low S/N.

The FMR defines a surface that galaxies occupy in the 3D space of stellar
mass, metallicity and SFR. Hence, the scatter in the mass-metallicity relation
can be reduced by scaling the mass as a function of the star formation rate.
We adopt the Mannucci et al. (2010) modified mass-metallicity scaling
parameter $\mu=\log_{10}(M)-\alpha\,\log_{10}(SFR)$ where $\alpha=0.32$ to
inspect whether our scatter decreases. We determine the scatter by considering
the RMS of the residuals after fitting our data with a standard mass-metal
relation parameterisation (e.g., Sanders et al., 2017)

$12+\log_{10}\left(O/H\right)=12+\log_{10}\left(O/H\right)_{asym}-\log_{10}\left(1+\left(\frac{M_{TO}}{M}\right)^{\gamma}\right)$
(1)

where each term defines the asymptotic gas-phase metallicity, the turn-over
mass ($M_{TO}$), and a power slope ($\gamma$). Plotting metallicity against
$\mu_{0.32}$ in Figure 19 shows a slightly tighter relation than seen when
plotted against mass, with an RMS scatter of 0.146 compared to 0.157 when
plotted against mass for the O32 metallicity (and 0.172 and 0.199 for
$\mu_{0.32}$ and mass using R23). This effect is subtle but we also note that
we find that $\alpha=0.32$ tightens the scatter to a greater extent than the
best fit $\alpha=0.17$ measured by Henry et al. (2021). The best fit
asymptotic metallicity, turn over mass, and $\gamma$ are given in Table 9.

We have found a mass metallicity relation using the metallicities derived from
the O32 and R23 strong line diagnostics. We also find that the scatter in
these reduced when we consider the SFR as a third dependent, as part of the
FMR. However, our best fit models for the O32 and R23-derived work are not
identical, this disparity has also been found by Topping et al. (2021) who
find that the evolution of the MZR depends on the strong line diagnostic used
to determine the metallicity.

Diagnostic | $asym^{\rm{a}}$ | $M_{TO}^{\rm{b}}$ | $\gamma$
---|---|---|---
Mass-metallicity (O32) | 8.55$\pm$0.07 | 8.14$\pm 0.31$ | 0.67$\pm 0.30$
Mass-metallicity (R23) | 8.74$\pm 0.08$ | 8.65$\pm 0.28$ | 0.95$\pm 0.26$
$\mu_{0.32}$-metallicity (O32) | 8.55$\pm 0.06$ | 7.84$\pm 0.27$ | 0.74$\pm 0.30$
$\mu_{0.32}$-metallicity (R23) | 8.72$\pm 0.06$ | 8.26$\pm 0.21$ | 1.13$\pm 0.26$
Table 9: The best fit parameters (a asymptotic metallicity, b turnover
$\log_{10}$ mass) for the mass-metallicity and modified
$\mu_{0.32}$-metallicity diagnostics. Figure 16: Mass metallicity relation for
O32 (left panel) and R23 (right panel) derived metallicities, colour coded by
star formation rate (H$\alpha$, unless unavailable then SFR-UV is used, these
are shown as triangles). Circles are the locations of galaxies with undetected
H$\beta$ where we instead infer the H$\beta$ flux from the measured H$\alpha$
flux, as in Figures 6 and 7. Black circles show the data binned by mass for
$\log_{10}(M/M_{\odot})$ = 7.5-8.5, 8.5-9.5 and 9.5-10.5. Figure 17: Mass
metallicity relation for O32 (left panel) and R23 (right panel) derived
metallicities, colour coded by redshift. Circles are the locations of galaxies
with undetected H$\beta$ where we instead infer the H$\beta$ flux from the
measured H$\alpha$ flux, as in Figures 6 and 7.  Figure 18: Mass metallicity
relation for highest likelihood metallicity, colour coded by redshift (left)
and star formation rate (right), as in Figures 16 and 17. Figure 19: Modified
mass-metallicity diagram, with $\mu$=log10(M)-$\alpha$log10(SFR) and
$\alpha=0.32$ from Mannucci et al. (2010). Left panel: metallicity derived
from O32. Right panel: metallicity derived from R23. In both panels the data
are colour coded by the SFR, as in Figure 17. The best fit parameterisation is
given by the blue curve.

###  3.7 High equivalent width H$\alpha$ sample

The WFSS from the WISP survey selects galaxies on the basis of their line
emission. This is in contrast to the usual broad-band magnitude-limited
surveys, which select on the continuum emission. Hence WISP may miss galaxies
which have very low SFR (and hence weak line emission) but we are more
sensitive to galaxies with high equivalent width emission lines and weak
stellar continuum - these low-mass but actively star-forming systems would
typically not enter a broad-band selection. To examine this we consider deep
spectroscopic surveys targetting $z\sim 1$ galaxies. These typically extend to
optical magnitudes of $AB=22.5$ mag over wide fields and $AB=24$ mag over
smaller regions, for example: VVDS-wide with $I_{AB}<22.5$ (Garilli et al.,
2008), VVDS-deep with $I_{AB}<24.0$ (Le Fèvre et al., 2005); DEEP2 with
$R_{AB}<24.1$ (Newman et al., 2013); zCOSMOS-wide $I_{AB}<22.5$, zCOSMOS-deep
with $I_{AB}<24.0$ (Lilly et al., 2007); VUDS $I_{AB}<25.0$ (Le Fèvre et al.,
2015). Many of our WISP sources with reliable detections of emission lines
have $H_{AB}\sim 24-25$ (see Figure 1). A typical star forming galaxy with
moderate extinction $E(B-V)=1$ at $z\approx 1$ has a colour of
$(I-H)_{AB}\approx 1$ mag (e.g., figure 1 of Doherty et al. 2005, where
$(I-H)_{AB}\approx(I-H)_{\rm{Vega}}-0.9$). About half (51$\%$) of the emission
line galaxies we detect in WISP, and spectroscopically confirm in this paper,
are fainter than $H_{AB}=24$ mag ($I_{AB}\sim 25$) and will have escaped
previous spectroscopic surveys, and 30$\%$ of our WISP galaxies are fainter
than $H_{AB}>25$ mag.

We determine the H$\alpha$ equivalent width of our sources through the ratio
of the H$\alpha$ emission line flux, corrected for [Nii] contribution and
stellar absorption (see Sections 3.3.1 and 3.3.2), and the continuum flux
density determined from the broadband magnitude of the photometric filter the
line fell in. We remove the contribution of the emission line to the flux in
the broad-band filter when calculating the stellar continuum, using the
transmission profile of the filter and assuming a spectral slope of
$f_{\lambda}\propto\lambda^{\beta}$ with $\beta=-2$ (a slope flat in $f_{\nu}$
appropriate for ongoing star formation in the absence of significant
reddening, e.g., Wilkins et al. 2011). We convert all the observed-frame
equivalent widths to the rest-frame values ($EW_{0}$) using
$EW_{0}=EW_{obs}/(1+z)$. A distribution of the H$\alpha$ rest-frame equivalent
widths is shown in Figure 20, and we also compare our distribution of
H$\alpha$ rest-frame equivalent widths with that determined from a broad-band-
selected survey from Mouhcine et al. (2005). We note that we have a tail of
high-$EW_{0}$ galaxies picked up in the WFSS that is missing from the broad-
band selection. The high-$EW_{0}$ tail will also be enhanced compared to the
$z\sim 0.06$ Mouhcine et al. (2005) sample due to the evolution of H$\alpha$
EW with redshift.

We examine the distribution of rest-frame H$\alpha$ equivalent widths across
our three redshift bins. The median (and mean) rest-frame H$\alpha$ equivalent
widths for the low ($z<0.7$), medium ($0.7\leq z<1.28$) and high ($z\geq
1.28$) redshift bins are 78 Å (mean $115\pm 23$ Å), 112 Å (mean $211\pm 47$ Å)
and 126 Å (mean $265\pm 101$ Å) respectively, from bins of 27, 36 and 6
galaxies with H$\alpha$ observations, where we quote the standard error on the
mean. We show this data binned by redshift in Figure 21, and we parameterize
the growth of rest-frame EW with redshift as

$EW_{0}\propto(1+z)^{P}$ (2)

where we determine the best-fit value of $P$ to be $1.88\pm 0.32$.

Our data shows a trend of increasing H$\alpha$ rest-frame EW with
redshift999We note that our sensitivity to lines vs.  continuum (i.e. EW) is
boosted at high redshift due to a fixed observed-frame EW limit dropping in
rest-frame EW0 by $EW_{obs}/(1+z)$, but most of our sources are well above the
EW threshold for line identification in WFSS, and the main selection effect is
the H$\alpha$ S/N., in line with the picture of increasing sSFR (e.g. Mármol-
Queraltó et al. 2016). Similar results on the redshift evolution of H$\alpha$
equivalent width are obtained by the 3DHST survey (Fumagalli et al., 2012)
which also uses WFSS with HST/WFC 3 and determine the evolution of rest-frame
H$\alpha$ equivalent width101010In the HST Grism the H$\alpha$ emission line
is blended with the [Nii] doublet and Fumagalli et al. (2012) do not correct
for the contribution from [Nii]. The value of the power law evolution will
remain comparable to our results unless there is significant evolution in the
[Nii]/H$\alpha$ ratio.of $P=1.79\pm 0.18$ for H$\alpha$ detected sources at
$10<\log_{10}(M_{stellar}/M_{\odot})<10.5$ using the same parameterization as
Equation 2, which agrees with our determination of $P=1.88$. However, we note
that our results are not directly comparable to Fumagalli et al. (2012), who
select a sample based on multi-colour imaging in the well-studied CANDELS
fields and hence also include galaxies with undetected line emission (i.e. low
SFR, below the sensitivity of WFC 3 spectroscopy). Such galaxies are not
included in our emission-line-selected sample, where we prioritise
spectroscopic follow-up of high equivalent width sources, and hence the
average SFR in our sample are higher than the average of the whole sample in
Fumagalli et al. (2012), but are comparable to the sub-set of star forming
galaxies (SFGs) shown in their figure 2 (but we note that they plot the
combined equivalent width of H$\alpha$+[Nii]).

We can use our spectroscopic follow-up to analyse any differences with
H$\alpha$ equivalent width in the physical properties of galaxies. In Section
3.6.1 we split the population approximately in half by H$\alpha$ equivalent
width, and showed that galaxies in our sample with $EW_{0}>100$Å had higher
[Oiii]/H$\beta$, indicating lower metallicity and/or higher ionisation
parameters than galaxies with $EW_{0}<100$Å (Figures 14 $\&$ 15). This
supports our contention that the population of galaxies captured by broadband
photometric selection criteria do not represent the full variety of star
forming galaxy properties, and may miss low stellar mass galaxies with high
specific star formation rates.

Figure 20: Upper panel: Logarithmic H$\alpha$ rest-frame equivalent width
distribution of the WISP selected galaxies with follow-up FORS2 observations.
H$\alpha$ rest-frame equivalent widths are corrected for seeing, [Nii]
contribution and stellar absorption. We remove two AGN candidates (see Section
3.4). Lower panel: we compare our EW distribution (blue histogram) with that
determined from the broad-band selected survey of Mouhcine et al. (2005) in
red, and note the tail of high-EW galaxies which is missed in the broad-band
selection. The Mouhcine et al. 2005 sample has selected on $EW_{0}(H\beta)>0$
Å, which results in the sharp decline in the red histogram at
$EW_{0}(H\alpha)<40$Å). Figure 21: Mean H$\alpha$ rest-frame equivalent width
against mean redshift of the low, medium and high redshift samples. A power
law trend of the form $EW_{0}\propto(1+z)^{P}$ is fit with a best fit power
law of $P=1.88\pm 0.32$.

##  4 Conclusions

In this paper we have followed up galaxies identified through line emission in
the near-infrared in the WFSS HST/WFC3 WISP survey, using VLT/FORS2 optical
spectroscopy to confirm the redshifts and to study the reddening and
metallicity of this emission line population. Half of the WISP galaxies in our
sample are fainter than $H_{AB}=24$ mag, and would not have been included in
many well known spectroscopic surveys based on broad-band magnitude selection.
Over 4 WISP survey fields, we targetted 85 out of 138 line emission objects
identified in the WFC3 WFSS spectra over a redshift range $0.4<z<2$. We
confirm 95% of the initial WFC3 grism redshifts in the 38 cases where we
detect lines in the FORS2 spectra. Spectroscopic confirmation from FORS2 is
important because in many cases the WFC3 spectroscopy detected only a single
emission line, usually assumed to be H$\alpha$. For the 43 single-line WFC3
sources targetted with FORS2 at $z<1.28$ (where we expted line emission to
fall in the FORS2 wavelength coverage), we confirm the initial WISP-based
redshifts in 15 out of 17 galaxies where emission lines were detected in
FORS2. However, there were a further 26 single-line WFC3 sources where we
expected to see line emission in FORS2 which were not detected, most likely
indicating that some of the single-line low-S/N WFC3 sources were spurious.
From this, we determine a maximum potential false-detection rate of WFC3 WFSS
single emission line galaxies of 65$\%$ (28/43 at $z<1.28$) which improves to
33% (1/3) using the latest public v1.00 WISP emission line catalogue.

We measure the Balmer decrement (the H$\alpha$/H$\beta$ flux ratio, after
correcting for stellar absorption and for [Nii] emission blended with
H$\alpha$ at the resolution of WFC3 grism), and find that the extinction of
the WISP galaxies is consistent with $A($H$\alpha)=1$ mag with some evidence
for an increase in reddening with H$\alpha$ luminosity, and less reddening
than seen in $z\sim 0$ samples. After correction for reddening, we find good
agreement between star formation rates derived from the H$\alpha$ emission
line and those from the rest-frame UV continuum ($L_{UV}$) with a near-linear
relation of $SFR(L_{UV})=[SFR(H\alpha)]^{1.15\pm 0.10}$. We obtain comparable
star formation rates to those from the dust-corrected rest-UV from the SED-
fits of the stellar population with BEAGLE on multi-band photometry (including
Spitzer $3.6\,\mu$m). We find that stellar masses derived from this fitting
have a median mass of $\log_{10}(M_{stellar}/M_{\odot})=8.94$, and our
emission-line-selected galaxies tend to lie above the star-forming main
sequence when plotting SFR against stellar mass (i.e. they have higher sSFR
than the comparison samples at similar redshifts).

We use emission line ratios to identify two likely AGN ($\sim$5% of the
sample) from the [Sii]-BPT diagram (modified to use [Sii] rather than [Nii])
and the mass-excitation (MEx) diagnostic. For the star-forming galaxies, we
use the [Oiii], [Oii] and H$\beta$ lines to derive gas-phase metallicities
using the strong-line O32 and R23 diagnostics and the calibrations from Curti
et al. (2017). Individual galaxies detected in these lines lie within the
region of the diagrams occupied by the low-$z$ SDSS galaxies, but our galaxies
typically have sub-solar metallicity, with metallicity decreasing with
redshift.

Our WISP galaxies have a mass–metallicity relation, and lie below the $z=0$
relation (i.e. the WISP galaxies have lower metallicity) and our results are
consistent with the evolution seen in other high redshift studies. We see a
trend that for galaxies of the same mass, those with higher SFR have lower
metallicity, consistent with the existence of a Fundamental Metallicity
Relation between SFR, stellar mass and metallicity.

Finally, we consider the evolution of the H$\alpha$ rest-frame equivalent
width of galaxies in our sample, and find a strong dependence on redshift of
$EW_{0}(H\alpha)\propto(1+z)^{1.88\pm 0.32}$. When we split our sample by
H$\alpha$ equivalent width at $EW_{0}(H\alpha)=100$ Å, we find that higher EW
galaxies have a larger [Oiii]/H$\beta$ and O32 ratio on average, suggesting a
lower metallicity or higher ionisation parameter in these extreme emission
line galaxies.

Looking forward, we emphasise the importance of securing multiple line
detections in future WFSS to obtain robust redshifts and avoid single emission
line ambiguity. The next generation of WFSS surveys on JWST and Euclid will
provide rich samples of star forming galaxies below traditional photometric
broadband thresholds, and to higher redshifts than possible with HST/WFC3
WFSS. Towards higher redshifts, where galaxies typically show higher sSFR,
WFSS is even better positioned to capture more complete samples down to
fainter magnitudes, crucial for the study of galaxy evolution and the most
extreme emission line galaxies. We note that while high purity (low false-
detection rates) can be achieved in these future WFSS surveys with high S/N
thresholds, it is important that follow up spectroscopy at complimentary
wavelengths is still utilised to confirm single-emission line galaxies below
these S/N thresholds that would otherwise be discarded from such pure samples.
As shown in this paper, multiple emission lines from such follow-up
spectroscopy can help characterise the physical conditions of these galaxies.

## Acknowledgements