# CANUCS: UV and Ionising Properties of Dwarf Star Forming Galaxies at z
$\sim$ 5 to 7

Anishya Harshan,1, Maruša Bradač1, Roberto Abraham2,3, Yoshihisa Asada4,5,
Gabriel Brammer6,Guillaume Desprez4, Karthiek Iyer8, Nicholas S. Martis1,4,9,
Jasleen Matharu6,7, Lamiya Mowla10,Adam Muzzin11, Gaël Noirot4, Gregor
Rihtaršič1, Ghassan T. E. Sarrouh11, Marcin Sawicki4,Victoria Strait6,7, Chris
J. Willott9,
1 Department of Mathematics and Physics, Jadranska ulica 19, SI-1000
Ljubljana, Slovenia
2 David A. Dunlap Department of Astronomy and Astrophysics, University of
Toronto, 50 St. George Street, Toronto, Ontario, M5S 3H4, Canada
3 Dunlap Institute for Astronomy and Astrophysics, 50 St. George Street,
Toronto, Ontario, M5S 3H4, Canada
4 Department of Astronomy & Physics and Institute for Computational
Astrophysics, Saint Mary’s University, 923 Robie Street, Halifax, NS B3H 3C3,
Canada
5 Department of Astronomy, Kyoto University, Sakyo-ku, Kyoto 606-8502, Japan
6 Niels Bohr Institute, University of Copenhagen, Jagtvej 128, DK-2200
Copenhagen N, Denmark
7 Cosmic Dawn Center (DAWN), Denmark
8Columbia Astrophysics Laboratory, Columbia University, 550 West 120th Street,
New York, NY 10027, USA
9 National Research Council of Canada, Herzberg Astronomy & Astrophysics
Research Centre, 5071 West Saanich Road, Victoria, BC, V9E 2E7, Canada
10 Whitin Observatory, Department of Physics and Astronomy, Wellesley College,
106 Central Street, Wellesley, MA 02481, USA
11 Department of Physics and Astronomy, York University, 4700 Keele St.
Toronto, Ontario, M3J 1P3, Canada E-mail<EMAIL_ADDRESS>lj.si 0000-0001-9414-6382 0000-0001-5984-0395 0000-0002-4542-921X
0000-0003-3983-5438 0000-0003-2680-005X 0000-0001-8325-1742
0000-0001-9298-3523 0000-0003-3243-9969 0000-0002-7547-3385
0000-0002-8530-9765 0009-0009-4388-898X 0000-0001-8830-2166
0000-0002-7712-7857 0000-0002-6338-7295 0000-0002-4201-7367

(Accepted XXX. Received YYY; in original form ZZZ)

###### Abstract

The epoch of reionisation progressed through the emission of ionising photons
from galaxies to their local intergalactic medium. In this work, we
characterise the dwarf star-forming galaxies as candidates for the source of
ionising photons that drove EoR. We investigate the ionising properties and
star formation histories of star-forming dwarf galaxies at the last stages of
EoR at $4.8<\rm{z}<7$ using observations from the CAnadian NIRISS Unbiased
Cluster Survey (CANUCS). The magnification due to gravitational lensing allows
us to probe large dynamic ranges in stellar mass ($2\times
10^{6}\leq\rm{M}_{*}/\rm{M}_{\odot}\leq 5\times 10^{9}$) and UV magnitudes
($-22.68\leq$M${}_{UV}\leq=-15.95$).We find a median UV slope
$\beta_{1500}\,$of $-2.56\pm 0.23$ and the production efficiency of ionising
photons $\log$ $\xi_{\rm{ion}}\,$$=25.39\pm 0.6$ for the full sample
($4.8<\rm{z}<7$) with a median stellar mass of $6.3\pm 0.5\times
10^{7}\rm{M}_{\odot}$. We find both $\beta_{1500}\,$and $\xi_{\rm{ion}}\,$are
marginally correlated with the stellar mass of the galaxy, indicating a
possible greater contribution of dwarf galaxies to the reionisation of the
Universe. We find that on average, galaxies in our sample are experiencing a
recent rise/burst of star formation which translates to a higher scatter in
$\xi_{\rm{ion}}\,$and a large scatter in H$\alpha$ equivalent widths. Finally,
we investigate the trends of H$\alpha$ and [OIII]+H$\beta$ EWs with UV
magnitude and find MUV is correlated between H$\alpha$ but not with
[OIII]+H$\beta$ EWs indicating low metallicities and recent burst in the UV
faint galaxies.

###### keywords:

Galaxies: high-redshift – Galaxies: evolution – dark ages, reionization, first
stars

††pubyear: 2024††pagerange: CANUCS: UV and Ionising Properties of Dwarf Star
Forming Galaxies at z $\sim$ 5 to 7–References

##  1 Introduction

The production of ionising photons is a fundamental process that plays a
crucial role in shaping the reionisation history of the Universe. However, the
sources of ionizing photons that drove reionisation at redshifts z $>5.5$
(e.g., Bolan et al., 2021; Davies et al., 2018; McGreer et al., 2014) are
poorly understood. Current observational evidence suggests that reionisation
proceeded through the escape of ionizing photons from young massive stellar
populations in galaxies (see review Robertson (2022) and references within).
To ascertain the contribution of different galaxies to reionisation, we need
to determine the rate of ionizing photons emitted into the inter-galactic
medium (IGM) from different galaxy populations. The rate of ionizing photons
emitted by galaxies can be determined by combining the non-ionising UV
luminosity function, escape fraction of ionising photons into the IGM and the
ionising photon production efficiency.

The ionising photon production efficiency ($\xi_{\rm{ion}}\,$) is the measure
of rate of hydrogen-ionising photon production ($\rm{E}\geq 13.6$ eV) by young
massive stars in a galaxy per unit non-ionising UV continuum luminosity
produced on average by the less massive stars. Thus $\xi_{\rm{ion}}\,$should
depend on the fraction of massive ionising stars which is regulated by the
initial mass function and the star formation history of the galaxy. Along with
the escape fraction of ionising photons ($f_{\rm{esc}}$), $\xi_{\rm{ion}}\,$is
used to determine whether a galaxy is capable of reionising the local IGM.
Direct measurement of $\xi_{\rm{ion}}\,$requires detection of ionising Ly-
continuum photons emitted by the galaxy which becomes increasingly difficult
for high redshift galaxies as the radiation would be absorbed by the
intergalactic medium. Thus the measurement of $\xi_{\rm{ion}}\,$for high
redshift galaxies has exclusively relied on indirect methods. As the bright
nebular recombination line H$\alpha$ (6562Å) is directly related to the total
number of Ly-continuum photons produced by stars in a galaxy (assuming an
escape fraction of zero : Leitherer & Heckman, 1995), H$\alpha$ line can be
used to constrain $\xi_{\rm{ion}}\,$(e.g., Bouwens et al. (2016); Chisholm et
al. (2022); Stefanon et al. (2022); Prieto-Lyon et al. (2022)).

The past decade has seen many studies estimating $\xi_{\rm{ion}}\,$using
indirect H$\alpha$ at z $\sim$ 4 to 5 based on stacking Spitzer/IRAC
photometry (e.g.,Bouwens et al. (2016); Lam et al. (2019); Stefanon et al.
(2019)) and at lower redshifts z$\sim$1 to 3.7, where H$\alpha$ or H$\beta$
was observable from ground based telescopes (Nakajima et al., 2016;
Nanayakkara et al., 2020; Matthee et al., 2016). These studies indicate that
the $\xi_{\rm{ion}}\,$increases with redshift, and thus the average escape
fraction required for galaxies to ionise the local IGM would be $\approx
10-20\%$ (Ouchi et al., 2009; Robertson et al., 2015; Finkelstein et al.,
2019; Naidu et al., 2019) at z = 6. However, most studies relied on low
statistics, lower redshift analogs or wide band photometry and image stacking
due to lack of access to Balmer lines. This has been mitigated with the launch
of the James Webb Space Telescope (JWST), and we are able to observe Balmer
lines using spectroscopy and/or medium/narrow band photometry to accurately
measure H$\alpha$ fluxes. Recently a number of studies using JWST observations
like Lin et al. (2023); Simmonds et al. (2023); Tang et al. (2023); Saxena et
al. (2023); Prieto-Lyon et al. (2022); Atek et al. (2023); Mascia et al.
(2023) have measured $\xi_{\rm{ion}}\,$, however, these studies rely on
luminous and/or high mass galaxies or small samples for dwarf galaxies. Thus
the ionisation properties of faint, low-mass galaxies remain unclear.

Observational studies suggest that low-mass galaxies should have a high
contribution to the reionisation of the Universe because of their abundance
indicated by the steep slope at the faint end of the UV luminosity function in
the high redshift Universe (Sawicki & Thompson, 2006; Reddy & Steidel, 2009;
Bouwens et al., 2011; Dressler et al., 2015; Finkelstein et al., 2015;
Ishigaki et al., 2015; Livermore et al., 2017; Mehta et al., 2017; Atek et
al., 2018; Bhatawdekar et al., 2018; Atek et al., 2023). The same is also
suggested by simulation studies like Balu et al. (2023), who suggest that
inclusion of low mass halos significantly increases the progression of
reionisation. Additionally, owing to the low gravitational potential along
with stochastic star formation histories, low stellar mass galaxies are
thought to have a higher escape fraction of ionising photons into the local
IGM (Paardekooper et al., 2012; Wise et al., 2014; Erb, 2015; Anderson et al.,
2017; Karman et al., 2016) at high redshifts. In order to determine the
contribution of low-mass galaxies to the reionisation of the Universe, we need
to investigate their star formation and ionising properties and compare them
to their massive counterparts. However, due to the faintness of low-mass
galaxies, most studies have focused on more massive and luminous galaxies.

To that end, we use the CAnadian NIRISS Unbiased Cluster Survey (Willott et
al., 2022, CANUCS), to study the low mass galaxies at redshift z $>5$. The
magnification provided by the lensing galaxy clusters along with the
capabilities of the JWST means we are now able to spectroscopically observe
low stellar mass faint galaxies that were previously hidden at z $>5$. With
CANUCS, we are able to reach UV magnitude $\rm{M}_{UV}\,$$\approx-15.95$
compared to $\rm{M}_{UV}\,$$\approx-16.4$ from the deep imaging from the JADES
(Eisenstein et al., 2023; Endsley et al., 2023a) for galaxies at $6<\rm{z}<9$.
We use medium and broad band photometry from NIRCam and prism spectroscopy
from NIRSpec to study the ionisation properties and star formation histories
of star-forming galaxies at $5<\rm{z}<7$. The outline of the paper is as
follows: We describe the observations, data reduction, and sample selection in
section 2. In section 3, we describe the methodology followed for flux
measurements from photometric and spectroscopic observations, dust correction,
and measurements of UV and ionising properties. In section 4, we discuss the
results on the UV slope, $\xi_{\rm{ion}}\,$, and emission line equivalent
widths and finally summarise our findings in section 5.

We assume a flat $\Lambda$CDM cosmology with
$\Omega_{m}=0.3,\Omega_{\Lambda}=0.7,\rm{h}=0.7$, all magnitudes are in the AB
system.

##  2 DATA and Target Selection

###  2.1 Imaging Data

In this work, we use data from the Canadian NIRISS Unbiased Cluster Survey
(Willott et al., 2022, CANUCS), a JWST GTO program (Program ID 1208; PI
C.Willott) and the HST program 16667 (PI M. Bradač). We select our sample from
the observations of the MACS J0417.5-1154 cluster (CLU) field and the
respective NIRCam flanking (NCF) field. In the central CLU field, the CANUCS
imaging data consists of HST/ACS filters: F435W, F606W, F814W and JWST/NIRCam
filters: F090W, F115W, F150W, F200W, F277W, F356W, F410M, F444W. In the NCF
field we have HST/WFC3 filters: F438M, F606W and JWST/NIRCam filters: F090W,
F115W, F140M, F150W, F162M, F182M, F210M, F250M, F277W, F300M, F335M, F360M,
F410M, F444W. CANUCS image reduction and photometry procedure is described in
detail in Noirot et al. (2023). In short, we use a modified version of the
Detector1Pipeline (calwebb_detector1) stage of the official STScI pipeline and
jwst_0916.pmap JWST Operational Pipeline (CRDS_CTX) to reduce the NIRCam data.
We perform astrometric alignment of the different exposures of JWST/NIRCam to
HST/ACS images, sky subtraction, and drizzling to a common pixel scale of
0.04′′ using version 1.6.0 of the grism redshift and line analysis software
for space-based spectroscopy (Brammer & Matharu, 2021, Grizli). The source
detection and photometry is done with the Photutils package (Bradley et al.,
2022) on the $\chi_{mean}$ detection image created using all available images.
For each detected source, total fluxes are measured in elliptical apertures
based on the Kron radius and circular apertures of diameter 0.3$\arcsec$ and
0.7$\arcsec$ (Asada et al., 2024). In this work, we use $0.7\arcsec$-diameter
aperture photometry on HST/ACS and JWST/NIRCam images that were PSF-
homogenized to the resolution of the F444W data (Sarrouh et al., in prep). We
calculate the photometric redshifts using EAZY-py (Brammer et al., 2008;
Brammer, 2023a) with SED templates from Larson et al. (2022) that are based on
FSPS (Conroy & Gunn, 2010) and BPASS (Eldridge et al., 2017) stellar
population synthesis models and CLOUDY (Ferland et al., 2017; Byler, 2018)
photoionization code.

We select our photometric sample between redshift 4.8 and 5.5 such that the
medium band F410M of JWST/NIRCam includes flux from the H$\alpha$ (6562Å)
emission line creating a flux excess. We get a sample of 270 objects with flux
excess in F410M (i.e., $\rm{Flux}_{\rm{F410M}}>\rm{Flux}_{\rm{F444W}}$) in the
selected redshift range. We impose SNR cuts for Lyman-break dropout
($\rm{SNR}_{\rm{F606W}}<2\,\rm{and}\,\rm{SNR}_{\rm{F090W}}>3$) and visually
inspect each object and select our final sample of 156 galaxies. We refer to
this sample as the NIRCam sample throughout the paper.

###  2.2 Spectroscopic Data

Galaxies selected with excess flux in F410M and Lyman break drop-out in F606W,
F814W or F090W were selected for spectroscopic follow-up without imposing a
magnitude limit with JWST/NIRSpec micro-shutter assembly in the low-resolution
Prism mode. Our NIRSpec data has been reduced using the JWST pipeline for
stage 1 corrections and then the msaexp (Brammer, 2023b) to create wavelength
calibrated, background subtracted 2D spectra. The 1D spectrum is then created
for each line by collapsing the spectrum in the spatial axis and extracting
the 1D spectrum within 3 $\sigma$ of the peak of the collapsed spectrum. From
the CANUCS spectroscopic observations, we confirm a sample of 33 galaxies with
H$\alpha$ emission line at $4.8<z<7$.

The wavelength coverage of the NIRSpec prism allows for observation of
H$\alpha$ emission at $4.8<\rm{z}<7$. Thus, our NIRSpec data covers a higher
redshift range compared to our NIRCam sample which covers $4.8<\rm{z}<5.5$.
The NIRCam data is limited in wavelength to allow for accurate measurement of
H$\alpha$ flux, which can be achieved when H$\alpha$ emission falls in the
F410M band (in $4.8<\rm{z}<5.5$). The lower observational depth of the
spectroscopic data compared to the NIRCam imaging leads to a sample of lower
magnification uncorrected MUV of -24.37 to -18.45 with median
M${}_{UV}=-20.95\pm 1.15$ in our NIRSpec Sample compared to uncorrected the
MUV range of -23.13 to -18.10 with median M${}_{UV}=-20.56\pm 0.85$ in our
NIRCam Sample. Similarly, the magnification uncorrected stellar masses of the
NIRSpec sample is in the range 7.78 $<$ $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$<$
9.51 with a median $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=8.11\pm 0.42$ compared
to the $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$range 7.67 $<$
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$<$ 9.75 with a median
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=8.04\pm 0.38$ for the NIRCam sample. The
properties of the two sample sets are presented in Table 1 and shown in Figure
1.

Sample | z | $\log\rm{M}_{*}/\rm{M}_{\odot}$ | MUV | $\beta_{1500}$ | $\xi_{\rm{ion}}\,$
---|---|---|---|---|---
NIRCam |  5.15 $\pm$ 0.2 (4.8 - 5.5) |  7.8 $\pm$ 0.5 (6.3 - 9.7) |  -20.0 $\pm$ 1.2 (-22.7 - -15.9) |  -2.58 $\pm$ 0.2 (-3.15 - -0.83) |  25.36 $\pm$ 0.04 (24.26 - 26.37)
NIRSpec |  5.5 $\pm$ 0.6 (4.8 - 7) |  7.9 $\pm$ 0.5 (6.7 - 9.2) |  -20.1 $\pm$ 1.2 (-21.8 - 17.0) |  -2.48 $\pm$ 0.4 (-2.78 - -1.73 ) |  25.48 $\pm$ 1.0 (21.25 - 26.75)
Table 1: Summary of median values and ranges (in parantheses) of physical
properties of the NIRCam and NIRSpec sample. Stellar mass
($\log\rm{M}_{*}/\rm{M}_{\odot}$), UV magnitude (MUV) are corrected for
magnification.

##  3 Methods

###  3.1 SED fitting and Flux Measurements

Figure 1: Distribution of Stellar mass (left), UV Magnitude in AB system
(center) and the UV slope at 1500 Å(right) for our selected sample. The orange
histograms represent the NIRCam sample at redshift $4.8>\rm{z}>5.5$, the
violet histograms represent the NIRSpec sample at $4.8>\rm{z}>7$. The filled
and unfilled histograms represent the magnification corrected and uncorrected
quantities respectively. Gravitational lensing correction improves our
detection limits by 1 dex in $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$and 2.1 dex in
$\rm{M}_{UV}\,$.

We calculate the photometric redshifts using EAZY-Py (Brammer et al., 2008;
Brammer, 2023a) including SED templates from Larson et al. (2022) that are
better suited to fit the SEDs of blue high redshift ($5<\rm{z}<8$) galaxies.
We used Dense Basis (Iyer & Gawiser, 2017; Iyer et al., 2019) SED fitting code
to determine other physical properties of galaxies: stellar masses, star
formation rates (SFRs), metallicities, stellar dust attenuation and non-
parametric star formation histories (SFHs). Dense Basis uses Flexible Stellar
Population Synthesis (FSPS) code (Conroy & Gunn, 2010) which includes a
prescription for nebular emission from CLOUDY (Ferland et al., 2017; Byler,
2018). We adopt the Calzetti et al. (2000) dust model and assume Chabrier
(2003) IMF. We fit the photometry from 3 HST/ACS bands and 8 JWST/NIRCam bands
covering a wavelength range of 0.4 $\mu m$ to 4 $\mu m$ for the CLU field and
2 HST/WFC3 bands and 14 JWST/NIRCam bands for the NCF field covering a
wavelength range of 0.4 $\mu m$ to 4 $\mu m$. The photometric sample is
selected with H$\alpha$ flux excess in the F410M medium band and has been
visually inspected to be a Lyman-continuum drop-out in the F606W or F814W
bands. Thus, we run Dense Basis with uniform redshift prior in $4.7<\rm{z}<6$
range. For the spectroscopic sample, we fix the redshift at the measured
spectroscopic redshift while running Dense Basis. We use flat stellar mass
prior between $5<$$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$<12$, flat sSFR prior
between $-12<$ sSFR ($yr^{-1}$) $<-7$, varied metallicity in the range
$-2.5<\log(Z/Z_{\odot})<0.25$ and used an exponential prior for dust
attenuation. We then correct the stellar mass, SFR, and SFHs for magnification
from gravitational lensing from the foreground cluster. The magnification
coefficients are calculated using an updated lens model for MACS0417 (Desprez
2024, in prep.) created with Lenstool (Kneib et al., 1993; Jullo et al.,
2007). The model improves upon the Mahler et al. (2019) model by adding
several new spectroscopically confirmed multiply imaged systems.

Figure 1 shows the stellar mass distributions before and after magnification
corrections. Our sample shows (not corrected for magnification) a lower limit
of $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=7.3$ (orange unfilled histogram, left)
for the NIRCam sample and $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=7.78$ (purple
unfilled histogram, left) for the NIRSpec sample. After correcting for
magnification from gravitational lensing from the cluster, the stellar mass
sample ranges between $6.36<$ $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$<9.76$ with
median $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=7.88\pm 0.57$ and $6.69<$
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$<9.21$ with median
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=7.94\pm 0.53$ for the NIRCam and NIRSpec
samples respectively shown in filled histograms in 1. In our sample, the
median lensing magnification is $3\pm 1$. Given the distance of the NCF field
from the cluster center, we assume a magnification of 1.

We measure the H$\alpha$ flux from the photometry by following the two-filter
method and the three-filter method described in Vilella-Rojo et al. (2015) for
the CLU and NCF field respectively. In the CLU field, we use the F444W broad
band filter to describe the stellar continuum and the F410M medium band with
flux excess from H$\alpha$ ($4.8<\rm{z}<5.5$). In the NCF field, we calculate
the continuum with the F360M medium band filter and the F444W broad band
filter and use the F410M medium band that contains the H$\alpha$ flux.
Similarly, only in the NCF field, we calculate the [OIII]+H$\beta$ flux for
the NIRCam sample using the F300M, F335M, and F360M bands. We do not calculate
the [OIII]+ H$\beta$ flux for galaxies in the CLU field as the [OIII]+
H$\beta$ falls in the F277W and F356W broad bands for the NIRCam sample which
would include spectral features like [OII], Balmer break, etc. We calculate
the restframe equivalent width (EW) for each emission line measurement using
the extracted emission line following Vilella-Rojo et al. (2015). We bootstrap
the photometry within the photometric errors and measure the line fluxes and
restframe EWs. We take the median values and $1\sigma$ of the distribution as
the measured line flux and EWs and associated errors.

For our NIRSpec data, we use the ID spectra and correct for slit loss by
performing a spline interpolation of the ratio of mock photometry from the 1D
spectrum and the observed photometry and smoothing the interpolated function.
For the spline interpolation, we also ignored the photometric bands where the
mock photometry from the NIRSpec spectrum was less than 2 SNR. We then extract
the 1D spectrum in 200 Å wavelength windows around emission lines H$\alpha$,
[OIII], and H$\beta$ and subtract the local continuum if present. Fluxes and
accurate redshifts are then calculated by fitting Gaussian curves on the
emission line without putting constraints on the width of the Gaussian. We
bootstrap the spectrum with the error spectrum and calculate fluxes. The
median flux and redshift and the $1\sigma$ of the distribution of the
bootstrap are taken as the measured values and associated errors. Given the
low resolution of the spectroscopic data from the NIRSpec prism, we note that
the H$\alpha$ emission may have contamination from [NII](6585Å) emission, and
the [OIII] (5007,4959Å) doublet is not always fully resolved (depending on
SNR). Cameron et al. (2023) found no significant observation of [NII] in deep
observation of Lyman break galaxies in $\rm{z}\sim 5.5-9.5$. Thus we assume a
negligible contribution of [NII] to the measured H$\alpha$ flux. We follow a
similar assumption while calculating H$\alpha$ flux from the medium band
photometry. However, we note that if we are to assume $\approx 10\%$
contribution of [NII] as is observed at $z\sim 2$ (Coil et al., 2014; Alcorn
et al., 2019), our H$\alpha$ fluxes and quantities measured with H$\alpha$
fluxes will be lowered by $\approx 10\%$. Figure 2 shows reasonable agreement
( $<7\%$ difference) between the H$\alpha$ flux measured with photometric data
vs spectroscopy. We note that this comparison has been done within the
overlapping NIRCam+NIRSpec sample (at $4.8<\rm{z}<5.5$).

Figure 2:  Comparison of H$\alpha$ flux (top), and UV Luminosity (bottom)
measured from photometry and spectroscopic data. Our photometric measurements
of H$\alpha$ flux (from F410M) and $\rm{L}_{UV}$ (from F090W) are consistent
with the spectroscopic measurements. Figure 3:  The distribution of
$\xi_{\rm{ion}}\,$corrected and uncorrected for dust obscuration is shown in
unfilled and filled histograms respectively. The dust correction follows
Calzetti et al. (2000) dust law for the NIRCam sample (orange) and using
Balmer decrement in the NIRSpec sample (purple). The NIRSpec sample shows no
significant difference in the median of the distribution but a slight increase
in the $\sigma$ of the distribution. The NIRCam sample shows a lower median
$\xi_{\rm{ion}}\,$in the dust corrected sample by $\sim 0.2$ dex.

###  3.2 UV Luminosity and UV continuum slope

We measure the UV luminosity of galaxies in the NIRCam sample using filters
covering rest-frame 1400–1600Å. Thus we use F090W for galaxies between the
redshift range of 4.8 to 5.5 which avoids the Lyman break and Lyman $\alpha$
emission. For the spectroscopic sample, we use the slit loss corrected 1D
spectrum and calculate the UV luminosity in the wavelength window containing
1500 Å determined by the F090W or F115W for each object depending on the
redshift. We correct the measured UV luminosity for both photometric and
spectroscopic data for lensing magnification. Finally, we bootstrap the
measurements within observational errors and report the median values and
1$\sigma$ errors. Figure 2 compares the UV luminosity measured using
photometric and spectroscopic data. We find reasonable agreement between the
UV luminosity measured with the two methods with the relative difference being
$0.11\pm 0.45$.

We calculate $\beta_{1500}\,$from the model SED from EAZY SED fitting of the
observed photometry. We measure $\beta_{1500}\,$by fitting model SED between
rest-frame 1400–2000 Å with a single power law in the wavelength windows
defined by Calzetti et al. (1994) to avoid absorption and emission lines.
$\beta_{1500}\,$measured with EAZY SED fitting is highly dependent on the
templates. The inclusion of the Larson et al. (2022) improves the measurement
of $\beta_{1500}\,$by increasing the range to reach up to $\beta_{1500}=-3.1$.

Figure 1 shows the UV magnitude and $\beta_{1500}\,$distributions before and
after magnification corrections. Our sample shows a lower limit (before
magnification correction) of $\rm{M}_{UV}\,$$=-18.1$ (orange unfilled
histogram, center) for the NIRCam sample and $\rm{M}_{UV}\,$$=-18.45$ (purple
unfilled histogram, center) for the NIRSpec sample. After correcting for
magnification from lensing from the cluster, the UV magnitude ranges between
$-22.68<$ $\rm{M}_{UV}\,$$<-15.95$ with median $\rm{M}_{UV}\,$$=-20.07\pm
1.27$ and $-21.7<$ $\rm{M}_{UV}\,$$<-17.01$ with median
$\rm{M}_{UV}\,$$=-20.1\pm 1.17$ for the NIRCam and NIRSpec samples
respectively (filled histograms in 1, center ). Given the achromatic nature of
lensing, $\beta_{1500}\,$is not affected by lensing magnification. The
distribution of $\beta_{1500}\,$shows a median $\beta_{1500}=-2.58\pm 0.26$
for the NIRCam sample and a median $\beta_{1500}=-2.48\pm 0.42$ in the NIRSpec
sample. After figure 1, we only present magnification corrected quantities.

Figure 4:  UV continuum slope ($\beta_{1500}\,$) vs redshift (left), stellar
mass (center) and MUV (right). Stars show the binned sample and the dashed
lines show the linear fit to the full sample. Within the uncertainties, we
find no significant correlation between $\beta_{1500}\,$and redshift or
$\rm{M}_{UV}\,$. However, we do find a moderate correlation between the
$\beta_{1500}\,$and stellar mass in our samples.

###  3.3 Dust Correction

The measured H$\alpha$ fluxes are corrected for nebular dust attenuation to
account for the light absorbed by dust in the star forming regions in the
galaxy. The Balmer decrement (H$\alpha$/H$\beta$) is one of the most robust
ways to correct for nebular dust attenuation. To calculate the intrinsic
H$\alpha$ luminosity for our spectroscopic sample, we determine the dust
attenuation towards H$\alpha$ by calculating the Balmer color excess following
the Case B recombination value (Osterbrock, 1989).

$E\left(\rm{H}\beta-\rm{H}\alpha\right)=2.5\log\left(\frac{\rm{H}\alpha\rm{/}\rm{H}\beta}{2.86}\right)$

Following the Calzetti dust law (Calzetti et al., 2000), the intrinsic
H$\alpha$ luminosity is determined as:

$\displaystyle L_{\rm{H}\alpha,int}=10^{0.4\rm{A}(\rm{H}\alpha)}\times
L_{\rm{H}\alpha,obs}$
$\displaystyle\rm{A}(\rm{H}\alpha)=6.6\log\left(\frac{\rm{H}\alpha/\rm{H}\beta}{2.86}\right)$

For our photometric sample, where we do not have measurements of H$\beta$ flux
to determine the balmer decrement, we use the total attenuation ($\rm{A}v$)
determined using Dense Basis SED fitting to calculate the attenuation towards
H$\alpha$ luminosity. For our sample, we calculate the median
$\rm{A}v=0.11^{+0.04}_{-0.06}$. We adopt the Calzetti dust law following the
recent results from Markov et al. (2024), who find the dust law for galaxies
at $\rm{z}>4.5$ is comparable to the Calzetti dust law. Following Calzetti
dust law (Calzetti et al., 2000), attenuation towards H$\alpha$ is determined
as:

$\displaystyle\rm{A}(\rm{H}\alpha)=0.82\times\rm{A}v$

Given the dust attenuation is higher in the UV wavelengths, the observed UV
luminosity in both photometric and spectroscopic data is similarly corrected
to determine the intrinsic UV luminosity using the Calzetti dust law at
$\lambda=1500$Å as:

$\displaystyle\rm{A}(1500)=2.55\times\rm{A}v$

###  3.4 $\xi_{\rm{ion}}\,$Measurement

Lyman-continuum photon production efficiency in the presence of a non-zero
$f_{esc,LyC}$ is used to determine the contribution of an object in ionising
the IGM. Since the precise value of $f_{esc,LyC}$ is uncertain, we assume a
$f_{esc,LyC}=0$. From indirect measurements of $f_{esc}$, studies find median
predicted $f_{esc,LyC)}<0.2$ at $6<\rm{z}<9$ (Mascia et al., 2023; Saxena et
al., 2023).

Leitherer & Heckman (1995) found the following relation between the H$\alpha$
luminosity and the intrinsic Lyman-continuum photons production rate computed
for dust free Case B recombination (Osterbrock, 1989) assuming no escape of
ionizing photons:

$\rm{L}(\rm{H}\alpha)[ergs^{-1}]=1.36\times
10^{-12}\dot{N}_{(H_{0})}[s^{-1}].$

Thus, we express $\xi_{\rm{ion}}\,$0 as the ratio of the Lyman-continuum
photons production rate to the intrinsic rest-frame UV luminosity
($\rm{L}_{UV}$) as:

$\xi_{\rm{ion,0}}=\frac{\dot{N}_{(H_{0})}}{\rm{L}_{UV}}$

We show the distribution of dust corrected and uncorrected $\log$
$\xi_{\rm{ion}}\,$for the NIRCam and NIRSpec samples in figure 3. We find that
for our NIRCam sample on average, dust corrected $\xi_{\rm{ion}}\,$is $0.20$
dex lower than the uncorrected $\xi_{\rm{ion}}\,$. We note that for this
sample we do not have information on the Balmer decrement. In our NIRSpec
sample, for which we have the Balmer decrement, the dust corrected
$\xi_{\rm{ion}}\,$is $<0.1$ dex higher than the uncorrected
$\xi_{\rm{ion}}\,$. Similarly, if we assume SMC-like dust attenuation, dust
corrected $\xi_{\rm{ion}}\,$is $0.2$ and 0.1 dex lower in the NIRCam and
NIRSpec samples respectively. Due to the lack of significant effect of dust on
the median $\xi_{\rm{ion}}\,$, we report the dust uncorrected
$\xi_{\rm{ion}}\,$in the paper.

##  4 Results

###  4.1 The UV slope

The UV continuum slope ($\beta_{1500}\,$) of a galaxy traces the light emitted
by young massive stars thus is crucial to constrain the stellar population and
star formation history of a galaxy. $\beta_{1500}\,$is dependent on the ages,
metallicities, and dust content in a galaxy (Duncan & Conselice, 2015; Reddy
et al., 2018). Given its dependence on the dust content of the galaxy,
$\beta_{1500}\,$is often used to constrain the dust attenuation of the
spectrum where Balmer decrement or infrared spectrum is not observed. However,
intrinsically, for a dust corrected spectrum, the $\beta_{1500}\,$is dependent
on the fraction of very young and metal-poor stellar population. Specifically,
young and metal-poor stellar populations result in bluer
$\beta_{1500}\,$compared to older metal-rich stellar populations. Given that
the main source of ionising UV radiation in a star forming galaxy is from the
young massive stellar population, the production efficiency of ionising UV
radiation ($\xi_{\rm{ion}}\,$) is expected to correlate with the
$\beta_{1500}\,$. In this section, we study the distribution and the evolution
of $\beta_{1500}\,$with galaxy properties.

In section 3.2 we describe the method we have adopted to measure
$\beta_{1500}\,$for the NIRCam samples. In figure 1, we present the
distribution of $\beta_{1500}\,$with 156 galaxies in the photometric (orange).
We find $-3.15<\beta_{1500}<-0.83$ with the median at $\beta_{1500}=-2.56\pm
0.26$ in the photometric sample. In figure 4, we plot $\beta_{1500}\,$as a
function of redshift, stellar mass, and $\rm{M}_{UV}\,$for both the NIRCam
(orange) and NIRSpec (purple) samples. The binned sample along with the linear
regression between $\beta_{1500}\,$and redshift, stellar mass, and
$\rm{M}_{UV}\,$are also shown.

Redshift Evolution of $\beta_{1500}\,$: We find no significant evolution of
$\beta_{1500}\,$with the redshift in the NIRCam sample (slope: 0.12, Spearman
Coefficient: 0.10). However, we note that our NIRCam sample is restricted to a
short range of redshift between $4.8<\rm{z}<5.5$. In our NIRSpec sample, the
linear regression measures a slope of 0.07 with a large scatter. Thus we do
not find a significant correlation between $\beta_{1500}\,$and z. This overall
trend is comparable to the results in the literature (Topping et al., 2023;
Nanayakkara et al., 2023; Jiang et al., 2020; Bouwens et al., 2014). We note a
large scatter in our sample and a lower correlation compared to the empirical
relation of $\beta_{1500}\,$with redshift shown by Bouwens et al. (2014). We
also note that previous studies like Jiang et al. (2020) are unable to recover
$\beta_{1500}<-2.6$ with SED fitting due to the limitations of the then
available templates, whereas $\beta_{1500}\,$calculated using broad band
photometry at high redshift (Bouwens et al., 2014) are affected by the
uncertainties in redshifts as well as spectral features.

Correlation of $\beta_{1500}\,$with Stellar Mass: In the middle panel of
figure 4, we present the correlation of $\beta_{1500}\,$with the stellar mass
of the galaxy. The stellar mass (magnification corrected) in our NIRCam sample
ranges from $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$= 6.3 to 9.75. We find a
moderate correlation of $\beta_{1500}\,$with the magnification corrected
stellar mass of the galaxies in both our NIRCam sample such that
$\beta_{1500}\,$gets shallower with increasing stellar mass. The linear
regression of $\beta_{1500}\,$with stellar mass for the NIRCam sample gives a
slope of 0.19 and a Spearman coefficient of 0.46, and a slope of 0.007 with
low significance in the NIRSpec sample. In the NIRCam sample, the lower mass
sample of $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$<8$ (median = $7.76\pm 0.04$)
has a $\beta_{1500}\,$$=-2.62\pm 0.02$ compared to $\beta_{1500}\,$$=-2.46\pm
0.04$ in the higher mass sample $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$\geq 8$
(median = $8.26\pm 0.05$). The bluer $\beta_{1500}\,$of low mass galaxies
implies that the low mass galaxies could have lower dust content, possible
higher fraction of ionising radiation, or lower metallicities compared to high
mass galaxies. Bluer $\beta_{1500}\,$is also associated with high escape
fraction (Chisholm et al., 2022; Mascia et al., 2023), indicating a higher
escape fraction in low mass galaxies and thus a higher contribution of low
stellar mass galaxies during the epoch of reionisation. This result is
comparable to Nanayakkara et al. (2023) who found a correlation between
$\beta_{1500}\,$and the stellar mass of galaxies at $4<\rm{z}<8$ similar to
our NIRCam sample. We also note that the $\beta_{1500}\,$calculated in
Nanayakkara et al. (2023) follows a similar procedure to measure
$\beta_{1500}\,$as our NIRCam sample but they do not perform magnification
correction for the stellar mass.

Correlation of $\beta_{1500}\,$with UV Magnitude: Finally, we present the
correlation of UV magnitude to the $\beta_{1500}\,$in the right panel in
figure 4. For our sample with UV magnitude $\rm{M}_{UV}<-19$, we find a median
$\beta_{1500}\,$$=-2.58\pm 0.02$ and for the fainter sample $\rm{M}_{UV}>-19$,
we median find $\beta_{1500}\,$$=-2.54\pm 0.02$. In our NIRCam sample, we do
not observe a significant UV magnitude evolution of the $\beta_{1500}\,$(with
slope $=-0.01$ and the Spearman coefficient= -0.02). Similarly, in the NIRSpec
sample, we do not observe a significant UV magnitude evolution of the
$\beta_{1500}\,$with slope $=0.05$ and Spearman coefficient = 0.03.

We find correlation presented in Nanayakkara et al. (2023) and Bouwens et al.
(2014) for a sample at z $=4$ to 7, and Topping et al. (2023) for a sample at
z $=5$ to 7 comparable to our NIRCam sample, albeit with a shallower slope of
the linear fit. The binned median $\beta_{1500}\,$in Nanayakkara et al. (2023)
from the GLASS JWST survey at a given UV magnitude is higher compared to our
NIRCam sample. However, this discrepancy could be explained by the photometric
redshift selection of galaxies in Nanayakkara et al. (2023), whereas we have
an additional condition of F410M flux excess from H$\alpha$ emission which
biases our sample towards actively star forming galaxies. Similarly, Topping
et al. (2023), who calculate $\beta_{1500}\,$directly from photometry also
have higher median $\beta_{1500}\,$values at UV magnitude $\rm{M}_{UV}<-19$
which could be driven by the Lyman break selection. However, previous studies
like Yamanaka & Yamada (2019) find an opposite correlation between
$\beta_{1500}\,$and $\rm{M}_{UV}$ in the range ($-22>\rm{M}_{UV}>-20$) at z
$\sim 4$. The Lyman break selected galaxies in Yamanaka & Yamada (2019) are
possibly biased towards higher dust content.

###  4.2 Ionising Photon Production Efficiency $\xi_{\rm{ion}}\,$

Figure 5: Evolution of the ionising photon production efficiency
$\xi_{\rm{ion}}\,$(uncorrected for dust) with redshift in the epoch of
reionisation. The purple and orange squares of NIRSpec and NIRCam selected
samples respectively are shown with various measurements of
$\xi_{\rm{ion}}\,$from the literature. The method of target selection is
mentioned in parentheses. Circles show binned measurements of $\log$
$\xi_{\rm{ion}}\,$, whereas squares show individual galaxy measurements. The
grey line shows the linear fit to the canonical value of
$\xi_{\rm{ion}}\,$required to ionise the local IGM as calculated by Robertson
et al. (2015). There is no significant evolution of $\xi_{\rm{ion}}\,$during
the epoch of reionisation and the $\xi_{\rm{ion}}\,$of our sample at
$\rm{z}<5.5$ is comparable to their higher redshift counterparts from the
literature within the errors.

Constraining $\xi_{\rm{ion}}\,$during the epoch of reionisation for different
galaxy populations is important to understand the contribution of different
galaxies to EoR and to understand how the reionisation of the Universe
proceeded. In this section we explore the evolution of $\xi_{\rm{ion}}\,$with
redshift and other galaxy properties at z $\sim$ 4.8 to 7 in our NIRCam and
NIRSpec samples.

####  4.2.1 Evolution of $\xi_{\rm{ion}}\,$

We calculate the median $\xi_{\rm{ion}}\,$of H$\alpha$ selected NIRCam sample
in the redshift range $4.8<\rm{z}<5.5$ $\log\,$$\xi_{\rm{ion}}\,$$=25.36\pm
0.40$ compared to the NIRSpec sample in the same redshift range with
$\log\,$$\xi_{\rm{ion}}\,$$=25.42\pm 0.3$. In this redshift range, we find
comparable results (within $1\sigma$) between our NIRCam and NIRSpec samples.
Whereas, the median $\xi_{\rm{ion}}\,$for galaxies in the NIRSpec sample in
redshift range $5.5<\rm{z}<7$ is $\log\,$$\xi_{\rm{ion}}\,$$=25.5\pm 0.2$
which is higher than the median $\xi_{\rm{ion}}\,$at $4.8<\rm{z}<5.5$ by
$<1\sigma$.

We put in context our measurements by comparing with H$\alpha$ emitters at
$4<\rm{z}<4.5$ from Faisst et al. (2019), Lyman-break galaxies at $4<\rm{z}<6$
from Bouwens et al. (2016), [OIII] emitters at $5<\rm{z}<9$ from Matthee et
al. (2023), Tang et al. (2023) and Mascia et al. (2023)(also H$\alpha$ and Ly
$\alpha$ emitters), and Lyman-alpha emitters (LAEs) at $\rm{z}>4$ from Lam et
al. (2019), Ning et al. (2022), Simmonds et al. (2023) and Saxena et al.
(2023). Among these,Matthee et al. (2023), Tang et al. (2023) and Saxena et
al. (2023) measure Balmer line fluxes directly from spectroscopy and Bouwens
et al. (2016), Faisst et al. (2019), Lam et al. (2019), Ning et al. (2022) and
Simmonds et al. (2023) make measurements from photometry.

The median $\log\,$$\xi_{\rm{ion}}\,$$=25.36\pm 0.04$ at $4.8<\rm{z}<5.5$ in
our photometric sample is comparable to the median $\log$
$\xi_{\rm{ion}}\,$$=25.27\pm 0.03,25.5,25.36\pm 0.08$ reported in Bouwens et
al. (2016), Faisst et al. (2019) and Lam et al. (2019) at similar redshifts.
At $\rm{z}\sim 6$, $\xi_{\rm{ion}}\,$from Ning et al. (2022) and Simmonds et
al. (2023) (median $\log$ $\xi_{\rm{ion}}\,$$=25.48\pm 0.4$ and
$25.44^{+0.21}_{-0.15}$ respectively) are also comparable to our
$\xi_{\rm{ion}}\,$at $\rm{z}<5.5$. At $5.5<\rm{z}<7$, the median $\log$
$\xi_{\rm{ion}}\,$of $=25.6\pm 0.2$ in our NIRSpec sample is comparable to
$\log\,$$\xi_{\rm{ion}}\,$$=25.3,25.8\pm 0.09$ and $25.56$ at $6<\rm{z}<8$
reported in Matthee et al. (2023),Tang et al. (2023) and Saxena et al. (2023).

From our NIRSpec sample, we confirm that 4 out of 33 galaxies are Ly $\alpha$
emitters (LAE) with median $\log$ $\xi_{\rm{ion}}\,$= $25.49\pm 0.17$ compared
to the median $\log\,$$\xi_{\rm{ion}}\,$$25.48=\pm 0.2$ of the non-LAE. We
find no significant difference between the $\xi_{\rm{ion}}\,$of LAE and non-
LAE in our NIRSpec sample. We also find no significant difference between LAE
reported in Lam et al. (2019), Ning et al. (2022), Simmonds et al. (2023), and
Saxena et al. (2023) and the non-LAE in our sample. The lack of significant
difference between $\xi_{\rm{ion}}\,$in the LAE and non-LAE also indicates
different physical processes driving the production of ionising photons and
creating channels of escape for Lyman $\alpha$ photons in different galaxies
similar to the findings in Saxena et al. (2023).

Overall, we find marginal evolution of median $\xi_{\rm{ion}}\,$between our
sample and median $\xi_{\rm{ion}}\,$reported in the literature between
$4<\rm{z}<9$. At $\rm{z}<5.5$. Median $\log\,$$\xi_{\rm{ion}}\,$$=25.36\pm
0.04$ and $\log\,$$\xi_{\rm{ion}}\,$$=25.48\pm 1$ for our NIRCam and NIRSpec
sample respectively is lower ($<1\sigma$) than $25.8\pm 0.09$ and $25.56$
reported in Tang et al. (2023) and Saxena et al. (2023). However, it is
consistent with $\log\,$$\xi_{\rm{ion}}\,$$=25.36\pm 0.07$ and 25.3 in (Mascia
et al., 2023) and Matthee et al. (2023) respectively. We note that the
selection of H$\alpha$ emitters for our sample biases the sample towards
higher $\xi_{\rm{ion}}\,$compared to a LBG selection that is done in the
stated literature studies and we might miss galaxies with low
$\xi_{\rm{ion}}\,$. We also find a large scatter in $\xi_{\rm{ion}}\,$,
especially in the NIRCam sample, which indicates a stochastic star formation
in galaxies at $z>5$.

####  4.2.2 $\xi_{\rm{ion}}\,$vs Stellar Mass and Star Formation

Figure 6: The ionising photon production efficiency ($\xi_{\rm{ion}}\,$) as a
function of stellar mass (left) and the specific star formation rate (right).
The purple and orange colors show our NIRSpec and NIRCam samples respectively.
The squares and stars show individual galaxies and binned samples with the
lines showing linear fits to the sample. We find a moderate negative
correlation of $\xi_{\rm{ion}}\,$with the stellar mass of galaxies and a
moderate positive correlation of $\xi_{\rm{ion}}\,$with the sSFR. Dwarf star
forming galaxies have a higher photon production efficiency and will require a
lower escape fraction to ionise their local IGM.

Figure 7: The ionising photon production efficiency ($\xi_{\rm{ion}}\,$) is
slightly positively correlated with T${}_{75}/$T50 (left). A more recent burst
in star formation has a smaller T${}_{75}/$T50. The markers have been color-
coded with the magnification-corrected stellar mass of the galaxy. The right
panel shows the star formation history of galaxies in bins of
$\xi_{\rm{ion}}\,$with median $\xi_{\rm{ion}}\,$of the bin stated in the
legend.  Figure 8: The ionising photon production efficiency
($\xi_{\rm{ion}}\,$) as a function of UV slope ($\beta_{1500}\,$) (left) and
the UV magnitude ($\rm{M}_{UV}$) (right). The purple and orange colors show
the NIRSpec and NIRCam samples respectively. The squares and stars show
individual galaxies and binned samples with the lines showing linear fits to
the sample. We find a positive correlation of $\xi_{\rm{ion}}\,$with the
$\rm{M}_{UV}$ in both NIRCam and NIRSpec samples similar to past studies.
However, we find no significant correlation between $\xi_{\rm{ion}}\,$and
$\beta_{1500}\,$.

The dependence of the production of ionising photons on the young and massive
stellar population in a galaxy indicates that $\xi_{\rm{ion}}\,$should show a
correlation with the stellar mass and the star formation history of a galaxy.
In this section, we explore the evolution of $\xi_{\rm{ion}}\,$with the
stellar mass and star formation history of the galaxies.

Figure 6 shows $\xi_{\rm{ion}}\,$as a function of magnification-corrected
stellar mass and the specific star formation rates calculated from Dense Basis
SED fitting of the NIRCam (orange squares) and NIRSpec sample (purple
squares). The NIRCam sample covers a range of magnification corrected
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=6.3-9.8$ and the NIRSpec sample covers
the range of $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=7.2-9.1$. We further bin the
sample into 5 stellar mass bins of
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$=6.3-7$, $7-7.5$, $7.5-8$, $8-8.5$ and
$>8.5$. The stars show the median $\xi_{\rm{ion}}\,$and the median stellar
mass of the binned sample. We find that $\xi_{\rm{ion}}\,$decreases marginally
(by $\sim 0.12$ dex) with increasing stellar mass such that the median
$\log\,$$\xi_{\rm{ion}}\,$$=25.57\pm 0.06$ for galaxies with
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$<7$ and $=25.46\pm 0.1$ for
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$>8$. The linear fit also shows a negative
slope of -0.16 and -0.28 for the NIRCam and NIRSpec samples respectively.
Although the negative slopes indicate a moderate negative correlation between
$\xi_{\rm{ion}}\,$and the stellar mass of the galaxy, we note that the
intrinsic scatter of the $\xi_{\rm{ion}}\,$measurement is large at standard
deviation $1\sigma=0.40$ for the NIRCam sample and $1\sigma=1.03$ for the
NIRSpec sample. Further, we calculate the Spearman correlation coefficient. We
find a negative correlation coefficient of -0.03 for the NIRCam sample and
-0.21 for the NIRSpec sample. Our NIRSpec sample indicates a slight negative
correlation of $\xi_{\rm{ion}}\,$with the stellar mass of the galaxies within
a large intrinsic scatter, however, the Spearman correlation finds no
significant correlation between $\xi_{\rm{ion}}\,$and stellar mass in our
NIRCam sample.

Figure 9:  The ionising photon production efficiency ($\xi_{\rm{ion}}\,$) as a
function of H$\alpha$ equivalent width (left) and [OIII] equivalent width
(right). The purple and orange colors show our NIRSpec and NIRCam samples
respectively. The [OIII] equivalent width is only shown for the galaxies in
the NCF field which have medium band observation of 5007 Å restframe
wavelength. The squares and stars show individual galaxies and binned samples
with the lines showing linear fits to the sample. We find a positive
correlation of $\xi_{\rm{ion}}\,$with the H$\alpha$ equivalent width. We also
find a moderate positive correlation of $\xi_{\rm{ion}}\,$with the [OIII]
equivalent width.

Given the difficulty in observing faint low stellar mass galaxies at $z\gtrsim
5$, which has only recently been made available with the launch of JWST,
similar results have been reported in the literature albeit at lower
redshifts. Lam et al. (2019) and Castellano et al. (2023a) find similar slopes
of the linear fit for the correlation between $\xi_{\rm{ion}}\,$and stellar
mass at $\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$>7$ and
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$$>8$ at redshift $\sim 5$ respectively.
Compared to this sample, we can extend the range of stellar mass by $>1$ dex
towards the lower mass end. The marginal elevation $\xi_{\rm{ion}}\,$of the
lower mass galaxies has important implications for the progression of
ionisation and the sources of ionising photons during the epoch of
reionisation. The steep slope of the faint end of the UV luminosity function
at $z>5$ (Bouwens et al., 2015; Livermore et al., 2017; Atek et al., 2018,
2023) coupled with higher $\xi_{\rm{ion}}\,$of low mass galaxies indicate such
dwarf systems may emit significant ionising photons into the IGM to reionise
their local environment depending on their escape fraction of ionising
photons. However, we note that our sample which is biased towards high
$\xi_{\rm{ion}}\,$galaxies especially at the magnification uncorrected low
stellar mass end due to the H$\alpha$ selection could be driving this
difference.

In the right panel of Figure 6, we show $\xi_{\rm{ion}}\,$as a function of the
specific star formation rates (sSFR) of the galaxies as measured from SED
fitting (refer to section 3.1 for the description of SED fitting). We note
that both $\xi_{\rm{ion}}\,$and sSFR are not affected by magnification
correction. Our samples cover a range of log sSFR = -9 to -7 $\rm{yr}^{-1}$.
Similar to the stellar mass, we have binned the sample in sSFR and the stars
depict the median $\xi_{\rm{ion}}\,$vs the median sSFR of the binned sample.
We bin the sample with log sSFR = $-9\,\rm{to}-8.5$, $-8.5\,\rm{to}-8$,
$-8\,\rm{to}-7.5$ and $>-7.5$ $\rm{yr}^{-1}$. In both the NIRCam and NIRSpec
samples, we find a positive correlation between $\xi_{\rm{ion}}\,$and sSFR
with slope of the linear fit 0.48 for the NIRCam sample and 0.29 for the
NIRSpec sample. However, we also find a small sub-sample of outliers to this
correlation at the low sSFR end (log sSFR $<8.5\rm{yr}^{-1}$). This low sSFR
end of our sample ($\sim 10\%$ of the sample) shows a larger scatter and
higher median $\xi_{\rm{ion}}\,$. This difference could be a result of the
H$\alpha$ selection, which would bias our sample to higher $\xi_{\rm{ion}}\,$,
especially at low sSFR. We note that between log sSFR -8.5 to -7.5, where
$\sim 85\%$ of the sample lies, we find no significant correlation of
$\xi_{\rm{ion}}\,$but a large intrinsic scatter of $\sigma=0.38$. We further
calculate the Spearman coefficient of -0.06 and -0.13 for correlation between
$\xi_{\rm{ion}}\,$and log sSFR for the NIRCam sample and the NIRSpec sample
respectively. Although the linear fit and the Spearman coefficient point
towards a slight positive correlation between $\xi_{\rm{ion}}\,$and the sSFR
of a galaxy, we note that these results have high intrinsic scatter and do not
show a clear correlation.

We compare our results with Castellano et al. (2023b), who find a very
significant monotonically increasing correlation between $\xi_{\rm{ion}}\,$and
sSFR of galaxies at $2<\rm{z}<5$. They report that the
$\xi_{\rm{ion}}\,$increases from $\log$ $\xi_{\rm{ion}}\,$$=24.5$
$\rm{Hz}\,\rm{erg}^{-1}$at $\log\rm{sSFR}=-9.5\,\rm{yr}^{-1}$ to $=25.5$
$\rm{Hz}\,\rm{erg}^{-1}$at $\log\rm{sSFR}=-7.5\,\rm{yr}^{-1}$. They also found
a Spearman correlation coefficient of $\sim 0.79$ compared to 0.013 and a
large p-value of 0.5 in our sample. Similar to our results, Castellano et al.
(2023b) also find a larger scatter of $\xi_{\rm{ion}}\,$at the lower end of
sSFR indicating a lower correlation of $\xi_{\rm{ion}}\,$with sSFR at the low
sSFR end, however, unlike our result, the median $\xi_{\rm{ion}}\,$at the
lower sSFR is lower than $\xi_{\rm{ion}}\,$at the higher sSFR end. The
difference in the results could be driven by the H$\alpha$ selection or could
also be explained by the redshift evolution of the median sSFR of the galaxies
indicating that at $\rm{z}>5$, $\xi_{\rm{ion}}\,$is not highly correlated to
the sSFR of the galaxy as galaxies may have a stochastic star formation
history which will rapidly fluctuate the sSFR of a galaxy.

Given the possible effect of stochasticity, we explore further the time scales
with which $\xi_{\rm{ion}}\,$changes with the star formation by studying the
correlation of $\xi_{\rm{ion}}\,$with stellar ages and star formation
histories. We derive the times when the galaxy creates 50% and 75% of its
stellar mass ($\rm{T}_{50}$ and $\rm{T}_{75}$, at the time of observation)
using the non-parametric histories of Dense Basis SED fitting. Figure 7 shows
$\xi_{\rm{ion}}\,$as a function of the ratio $\rm{T}_{75}$/$\rm{T}_{50}$ (left
panel) with each galaxy colored by its stellar mass. The ratio
$\rm{T}_{75}$/$\rm{T}_{50}$ is indicative of the relative time of the last
burst of star formation in the galaxy such that a lower
$\rm{T}_{75}$/$\rm{T}_{50}$ indicates a more recent burst. We find a moderate
positive correlation between $\xi_{\rm{ion}}\,$and
$\rm{T}_{50}$/$\rm{T}_{75}<0.3$ such that $\xi_{\rm{ion}}\,$is decreasing on
average with more recent bursts. However, we find a small sample of galaxies
with $\rm{T}_{50}$/$\rm{T}_{75}>0.3$ that have a lower median
$\xi_{\rm{ion}}\,$. This indicates a potential correlation of
$\xi_{\rm{ion}}\,$with the age of the starburst, however, we note that the
effect is also dependent on the star formation history and the strength of the
starburst. We also find the lowest stellar mass galaxies have had a more
recent burst compared to the more massive galaxies in our sample. We note that
the H$\alpha$ selection biases our sample to galaxies with ongoing active star
formation i.e. either to a rising or bursty star formation history.

We further divide our sample into $\xi_{\rm{ion}}\,$bins and plot their median
star formation histories (right panel, figure 7). The median
$\xi_{\rm{ion}}\,$of each bin and their respective medians magnification
corrected stellar masses are: $\log$ $\xi_{\rm{ion}}\,$= $24.86\pm
0.05,\,25.28\pm 0.02,\,25.69\pm 0.02,\,26.21\pm 0.04$ and
$\log{\rm{M}_{*}/\rm{M}_{\odot}}\,$= $7.78\pm 0.14,\,7.89\pm 0.07,7.88\pm
0.1,\,7.90\pm 0.12$. We find that on average our sample is experiencing an
ongoing star formation burst. However, this could be a result of the selection
of H$\alpha$ emitters exclusively. The bin with the highest
$\xi_{\rm{ion}}\,$started the burst $<100$ Myrs earlier than the lowest
$\xi_{\rm{ion}}\,$bin. Thus, we infer that there may be a potential delay of
increase in the production rate of ionising photons from the start of the last
rise in star formation.

Figure 10:  H$\alpha$ equivalent width (left) and [OIII](+H$\beta$) equivalent
widths (right) as a function of UV magnitude. The purple and orange colors
show our NIRSpec and NIRCam samples respectively. The [OIII] equivalent width
is shown for the NIRSpec sample and [OIII]+H$\beta$ EW for galaxies in the NCF
field which have medium band observation of 5007 Å restframe wavelength. The
squares and stars show individual galaxies and binned samples with the lines
showing linear fits to the sample. We find a positive correlation of H$\alpha$
EW with the UV magnitude and no significant correlation of [OIII](+H$\beta$)
EW with the UV magnitude.

####  4.2.3 $\xi_{\rm{ion}}\,$vs UV properties

In this section, we study the correlation of UV properties with
$\xi_{\rm{ion}}\,$. In figure 8, we show $\xi_{\rm{ion}}\,$as a function of
the UV slope ($\beta_{1500}\,$, left panel) and the UV magnitude
($\rm{M}_{\rm{UV}}$, right panel). We find that $\xi_{\rm{ion}}\,$correlates
positively with $\beta_{1500}\,$in our NIRCam sample with slope = 0.49 and the
Spearman correlation coefficient = 0.32. Similarly,
$\xi_{\rm{ion}}\,$correlates positively with $\beta_{1500}\,$with slope of 0.5
in out NIRSpec sample. However, the $\beta_{1500}\,$measurement from EAZY SED
fitting recovers $\beta_{1500}\,$in a small range
($-3.1<$$\beta_{1500}\,$$<2$), and we find a significant scatter of
$\xi_{\rm{ion}}\,$within this range. Compared to other studies, Bouwens et al.
(2016) and Castellano et al. (2023b) find a negative correlation of
$\beta_{1500}\,$with $\xi_{\rm{ion}}\,$, whereas Lam et al. (2019) find no
significant correlation. From the variability of $\beta_{1500}\,$with
measurement and the difference in results across literature, we infer that
$\xi_{\rm{ion}}\,$is not correlated with $\beta_{1500}\,$ at $\rm{z}>5$.

We measure the correlation between $\xi_{\rm{ion}}\,$and the
$\rm{M}_{\rm{UV}}$. We find a positive correlation with a slope and Spearman
correlation coefficients of 0.16 and 0.34 in our NIRCam sample, and 0.18 and
0.61 in our NIRspec sample. We find a steeper correlation between
$\xi_{\rm{ion}}\,$and $\rm{M}_{\rm{UV}}$ compared to Bouwens et al. (2016),
Castellano et al. (2023b) and Lam et al. (2019). We are able to increase the
range of $\rm{M}_{\rm{UV}}$ towards the faint end to $\sim-16$ and our result
indicates a higher production rate of ionising photons for UV faint galaxies
compared to other studies.

###  4.3 Ionisation Conditions from restframe Emission Lines

The ionising photon production efficiency depends on the star formation and
the ionising conditions of the galaxy ISM. In this section, we study the
correlation between $\xi_{\rm{ion}}\,$and H$\alpha$ and [OIII](+H$\beta$)
equivalent widths which trace the average stellar ages and the ionisation
parameter of the ISM respectively. Figure 9 shows $\xi_{\rm{ion}}\,$as a
function of H$\alpha$ EW (left) and [OIII](+H$\beta$) EW (right).
$\xi_{\rm{ion}}\,$is highly correlated with H$\alpha$ EW in both NIRCam (slope
0.7, Spearman coefficient 0.6) and NIRSpec (slope 0.5, Spearman coefficient
0.5) samples. Although partially the correlation found is driven by the fact
that $\xi_{\rm{ion}}\,$is measured with H$\alpha$ luminosity,
$\xi_{\rm{ion}}\,$is also dependent on UV luminosity, and H$\alpha$ EW is
dependent on the strength of the stellar continuum as well. Our results are
comparable with Atek et al. (2022), who find a correlation with a slope of
0.63 for low stellar mass galaxies at z $\sim 1$ and other studies at low
redshifts ( z $\sim 1-2$) (Emami et al., 2020; Tang et al., 2019; Matthee et
al., 2016).

At lower redshifts (z $\sim 1-2$), $\xi_{\rm{ion}}\,$is known to correlate
with the [OIII]+H$\beta$ EW (Chevallard et al., 2018; Tang et al., 2019;
Onodera et al., 2020). At higher redshifts Tang et al. (2023) show for a small
sample of $z>7$ galaxies that the $\xi_{\rm{ion}}\,$is similarly correlated
with [OIII]+H$\beta$ EW and also that [OIII]+H$\beta$ EW is correlated with
the O32 ratio which traces the ionisation parameter of the galaxy ISM. Here we
investigate the correlation of $\xi_{\rm{ion}}\,$[OIII](+H$\beta$) EW in our
NIRSpec and NIRCam (only in the NCF field) samples. We find that,
$\xi_{\rm{ion}}\,$is moderately correlated with [OIII]+H$\beta$ EW in the
NIRCam sample (slope 0.12, Spearman coefficient 0.5) and with [OIII] EW in the
NIRSpec sample (slope 0.4, Spearman coefficient 0.3). This result is
consistent with the correlation found in both lower and higher redshift
samples (Chevallard et al., 2018; Tang et al., 2019; Onodera et al., 2020;
Tang et al., 2023). In conjunction with the result in Tang et al. (2023), this
indicates that $\xi_{\rm{ion}}\,$is correlated with the ionisation parameter
of the galaxy.

In the NIRCam sample, we find median [OIII]+H$\beta$ EW $=1861\pm 433$ Å which
is comparable to $1993\pm 214$ Å for [OIII] emitters at z $\sim 8$ (Tang et
al., 2023) but higher than the $\sim 700$ Å at z $\sim 6$ found in Endsley et
al. (2023a). The higher [OIII]+H$\beta$ EW in our sample compared to Endsley
et al. (2023a) could be driven by our H$\alpha$ selection which biases the
sample towards higher star forming and hence emission line galaxies. In our
NIRSpec sample, we find a median [OIII] EW of $802\pm 360$Å which is higher
compared to the lower redshift sample ($\sim$100 Å for star forming galaxies
at z$=2$ (Reddy et al., 2018)), but similar to the [OIII] EWs in extreme
emission line galaxies at z $\sim 3$ (Gupta et al., 2023).

Further, we investigate the correlation of H$\alpha$ and [OIII]+H$\beta$ EWs
with the UV magnitude shown in figure 10. We find a positive correlation
between H$\alpha$ and the MUV in the NIRCam sample with a slope of 0.12 and a
Spearman correlation coefficient of 0.41 with a very small p-value indicating
a strong correlation. However, we find no significant correlation between
H$\alpha$ and the MUV in the NIRSpec sample with 0 slope and a large p-value
for the Spearman correlation coefficient. The difference in correlation of
H$\alpha$ with MUV between the NIRSpec and NIRCam sample might be driven by
the H$\alpha$ selection and shallower depth of the NIRSpec sample compared to
the NIRCam sample. We note that at M${}_{\rm{UV}}<-18$, we also find a large
scatter in H$\alpha$ (median H$\alpha$ EW $=339.27$Å and $\sigma=1651.06$Å)
compared to the fainter end (M${}_{\rm{UV}}>-18$; median H$\alpha$ EW
$=517.8$Å and $\sigma=794.69$Å). Although the UV faint sample
(M${}_{\rm{UV}}>-18$) has been magnified due to gravitational lensing from the
foreground cluster, H$\alpha$ EW is independent of the magnification. Our
results are comparable to the median H$\alpha$ EW ($\approx 400$ Å) found in
previous studies (Faisst et al., 2019; Lam et al., 2019). However, we report a
lower median H$\alpha$ EW compared to EW reported in Endsley et al. (2023b),
who also do not find a correlation between H$\alpha$ EW and MUV in the Lyman
break selected galaxies.

Figure 10 shows the correlation between [OIII]+H$\beta$ EW and the UV
magnitude. We find no significant correlation between [OIII]+H$\beta$ EW in
the bright UV sample (M${}_{\rm{UV}}<-18$). Due to the lack of medium bands
observations of the [OIII]+H$\beta$ emission in the CLU field which are
magnified due to gravitational lensing, we are limited to the
M${}_{\rm{UV}}<-18$ sample. Within the range $-23<$M${}_{\rm{UV}}<-18$, we
find a median [OIII]+H$\beta$ EW $=917.27$ Å and a large scatter of
$\sigma=2621.65$Å. We also do not find a correlation between [OIII]+H$\beta$
EW and the UV magnitude with 0 slope and large p-value for Spearman
correlation coefficients. Similar to previous studies, we find a large
[OIII]+H$\beta$ EW compared to z$\sim 2$, and 46 extreme emission galaxies
with $>1200$ Å [OIII]+H$\beta$ EW. The median [OIII]+H$\beta$ EW of our NIRCam
sample is lower than 1994 Å reported in Tang et al. (2023) for z$>7$ galaxies
but higher than median [OIII]+H$\beta$ EW ($<890\pm 60$ Å) reported in Endsley
et al. (2023b). Endsley et al. (2023b) also find that the UV faint
(M${}_{\rm{UV}}>-19$) galaxies have a lower [OIII]+H$\beta$ EW which is driven
by lower metallicities as well as more recently-declining star formation
histories relative. However, in our sample, we find that the UV faint
(M${}_{\rm{UV}}>-19$) galaxies have a higher H$\alpha$ EW which indicates
lower metallicities and high star formation rates. The difference in trends
compared to Endsley et al. (2023b) could arise from differences in sample
selection strategies, where we have selected galaxies with F410M band excess
that biases our sample towards star forming galaxies with higher nebular
emission, whereas Endsley et al. (2023b) follow a Lyman-break selection which
allows them to select galaxies that are not biased towards higher emission.

##  5 Conclusions

In this work, we present the UV and ionisation properties and star formation
of dwarf galaxies at z $\sim 5$ to 7. We use the CANUCS NIRCam and NIRSpec
observations of the MACS0417 CLU field and the respective NCF field. Our
sample is selected with a F410M band flux excess at $4.8<\rm{z}<5.5$ such that
the H$\alpha$ emission is included in the medium band and we can measure
accurate emission line flux and EWs. We confirm the line fluxes for a subset
of the NIRCam sample with NIRSpec follow-up (figure 2). With the magnification
from the foreground cluster scale lens in our field, we are also able to push
to fainter and lower mass galaxies compared to previous studies at similar
redshifts. Using this data, we discussed the evolution of $\beta_{1500}\,$and
$\xi_{\rm{ion}}\,$and their dependence on the galaxy properties and star
formation histories. We also study the ionising properties of our sample using
emission line EWs. We summarise our results as follows:

1\. We find bluer UV slopes of dwarf galaxies with median
$\beta_{1500}\,$$-2.56\pm 0.26$ in the NIRCam sample. We find no significant
evolution of $\beta_{1500}\,$with redshift during the epoch of reionisation
but find a significant correlation between $\beta_{1500}\,$and the stellar
mass of the galaxy in both our sample sets. These results indicate a lack of
dust build-up or a higher presence of ionising radiation in star forming dwarf
galaxies at z$\sim 5$.

2\. We do not find any evolution of $\xi_{\rm{ion}}\,$with redshift in the EoR
and no significant difference between $\xi_{\rm{ion}}\,$of Ly$\alpha$ emitters
reported in the literature with our sample (median $\log$
$\xi_{\rm{ion}}\,$$=25.36\pm 0.04$ and $25.49\pm 0.18$ in NIRCam and NIRSpec
samples respectively, figure 5). The median $\log$ $\xi_{\rm{ion}}\,$of our
sample sets is also above the canonical value of 25.2 required to reionise the
local IGM with approximately $20\%$ escape fraction (Robertson et al., 2015).
The lack of difference between the median $\xi_{\rm{ion}}\,$Ly$\alpha$
emitters and non-emitters indicates different physical processes affecting the
production of ionising photons and the creation of escape channels for Lyman
$\alpha$ photons.

3\. We find a moderate correlation of $\xi_{\rm{ion}}\,$with the stellar mass
and the specific star formation rates in a galaxy, such that
$\xi_{\rm{ion}}\,$decreases with increasing stellar mass and increases with
increasing sSFR (figure 6). On further investigation of the star formation
histories, we find that the majority of our H$\alpha$ selected galaxies are
undergoing recent star formation raise/burst which creates a large scatter in
the $\xi_{\rm{ion}}\,$. We also find that the relative time of burst is
correlated to average $\xi_{\rm{ion}}\,$and indicates a delay in of $\approx
50$ Myrs between the final rise in star formation/burst and increasing
$\xi_{\rm{ion}}\,$(figure 7).

4\. We investigate the correlation between $\xi_{\rm{ion}}\,$and UV properties
$\beta_{1500}\,$and MUV. We find a significant correlation between MUV and
$\xi_{\rm{ion}}\,$such that $\xi_{\rm{ion}}\,$increases with decreasing MUV.
This implies a possible greater contribution of UV faint and dwarf galaxies to
reionising the Universe. However, we find no significant and opposite
correlation between $\beta_{1500}\,$and $\xi_{\rm{ion}}\,$. The NIRCam sample,
which covers a small dynamic range of beta finds higher $\xi_{\rm{ion}}\,$for
redder $\beta_{1500}\,$. The large scatter in $\beta_{1500}\,$and
$\xi_{\rm{ion}}\,$which arise due to the stochastic nature of star formation
histories in dwarf galaxies could explain the observed discrepancy.

5\. We also find a significant correlation between $\xi_{\rm{ion}}\,$and EWs
of restframe optical emission lines. We find that $\xi_{\rm{ion}}\,$increases
highly with increasing H$\alpha$ EW and moderately with [OIII]+ H$\beta$ EW.
We further explore the correlation of restframe optical emission EWs with MUV.
We find that on average H$\alpha$ EW increases with MUV, although our bright
end of the MUV range has a high scatter in H$\alpha$ EW indicating a
stochastic star formation history with very recent bursts. However, our UV
faint sample shows a high H$\alpha$ EW. On the other hand, we do not find a
significant correlation between [OIII]+ H$\beta$ EW and MUV. However, the lack
of medium band observation covering the [OIII]+ H$\beta$ emission in the CLU
field limits us to M${}_{\rm{UV}}<-18$, where we similarly find a large
scatter in [OIII]+ H$\beta$ EW.

Our results from one of the five cluster fields of CANCUS provide a large set
of empirical measurements of UV and ionising properties of dwarf star forming
galaxies at z $>5$. We demonstrate here the use of medium band photometry to
accurately derive emission line fluxes without having to rely solely on
spectroscopy. Similar studies characterising the properties of dwarf galaxies
across the epoch of reionisation are required to fully understand how
reionisation of the Universe progressed. This work will be supplemented by
future studies with the full CANUCS data at z$>5$, which will provide a better
understanding of the general population of galaxies across the history of the
Universe.

## Acknowledgements

AH, MB, GR, and NM acknowledge support from the ERC Grant FIRSTLIGHT and
Slovenian national research agency ARRS through grants N1-0238 and P1-0188. MB
acknowledges support from the program HST-GO-16667, provided through a grant
from the STScI under NASA contract NAS5-26555. This research was enabled by
grant 18JWST-GTO1 from the Canadian Space Agency and funding from the Natural
Sciences and Engineering Research Council of Canada. This research used the
Canadian Advanced Network For Astronomy Research (CANFAR) operated in
partnership by the Canadian Astronomy Data Centre and The Digital Research
Alliance of Canada with support from the National Research Council of Canada
the Canadian Space Agency, CANARIE and the Canadian Foundation for Innovation.
The Cosmic Dawn Center (DAWN) is funded by the Danish National Research
Foundation under grant No. 140.

## Data Availability

Raw JWST data used in this work is available from the Mikulski Archive for
Space Telescopes (https://archive.stsci.edu; doi: 10.17909/ph4n-6n76).
Processed data products will be available on http://canucs-jwst.com.

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