# Star formation exists in all early-type galaxies – evidence from ubiquitous
structure in UV images

Divya Pandey1, Sugata Kaviraj2, Kanak Saha3, Saurabh Sharma1
1Aryabhatta Research Institute of Observational Sciences, Manora Peak,
Nainital 263 002, India
2Centre for Astrophysics Research, University of Hertfordshire, College Lane,
Hatfield AL10 9AB, UK
3Inter-University Centre for Astronomy & Astrophysics, Postbag 4, Ganeshkhind,
Pune 411 007, India<EMAIL_ADDRESS><EMAIL_ADDRESS>
###### Abstract

Recent surveys have demonstrated the widespread presence of UV emission in
early-type (elliptical/S0) galaxies, suggesting the presence of star formation
in many of these systems. However, potential UV contributions from old and
young stars, together with model uncertainties, makes it challenging to
confirm the presence of young stars using integrated photometry alone. This is
particularly true in ETGs that are fainter in the UV and have red UV-optical
colours. An unambiguous way of disentangling the source of the UV is to look
for structure in UV images. Optical images of ETGs, which are dominated by old
stars, are smooth and devoid of structure. If the UV is also produced by these
old stars, then the UV images will share this smoothness, while, if driven by
young stars, they will exhibit significant structure. We compare the UV and
optical morphologies of 32 ETGs (93 percent of which are at $z<0.03$) using
quantitative parameters (concentration, asymmetry, clumpiness and the Sérsic
index), calculated via deep UV and optical images with similar resolution.
Regardless of stellar mass, UV-optical colour or the presence of interactions,
the asymmetry and clumpiness of ETGs is significantly (often several orders of
magnitudes) larger in the UV than in the optical, while the UV Sérsic indices
are typically lower than their optical counterparts. The ubiquitous presence
of structure demonstrates that the UV flux across our entire ETG sample is
dominated by young stars and indicates that star formation exists in all ETGs
in the nearby Universe.

###### keywords:

galaxies: formation – galaxies: evolution – galaxies: elliptical and
lenticular, cD – ultraviolet: galaxies – galaxies: star formation

††pagerange: Star formation exists in all early-type galaxies – evidence from
ubiquitous structure in UV images–A

##  1 Introduction

Massive early-type galaxies (ETGs), i.e. elliptical and S0 systems, dominate
the stellar mass density in the nearby Universe (e.g. Baldry et al., 2004),
making them fundamental to a complete understanding of galaxy evolution.
Classical models of ETG evolution, largely underpinned by their optical
properties – e.g., red optical colours with low intrinsic scatter (e.g.
Gladders et al., 1998) and high alpha-to-iron ratios (e.g. Thomas et al.,
2005) – have postulated that these galaxies form in rapid starbursts at high
redshift ($z>2$), followed by passive aging thereafter (e.g. Larson, 1974;
Chiosi & Carraro, 2002). In this ‘monolithic’ formation scenario, the stellar
populations of ETGs in the nearby Universe are, by construction, purely old.

While old stellar populations are generally expected to be faint in the UV,
some ETGs (typically bright systems in dense environments) show an upturn in
flux (Burstein et al., 1988; O’Connell, 1999) between the near-UV (NUV; 2500Å)
and the far-UV (FUV; 1500Å). In the context of the classical model, the flux
in these ‘UV upturn’ systems has been postulated to originate from evolved
metal-rich horizontal branch stars (e.g. Yi, 2008). An alternative source of
UV flux in old stellar populations could come from hot subdwarf stars in
binary systems, which are expected to be in place by $z\sim 1$ (e.g. Han et
al., 2007). However, the predicted redshift evolution of the FUV to NUV slope
in such models does not fit observational data (Ree et al., 2007), making them
less likely to be the dominant source of old UV emission in ETGs.

The unexpected recent discovery, via GALEX (e.g. Martin et al., 2005)
observations, of the widespread presence of UV sources in ETGs (e.g. Yi et
al., 2005; Kaviraj et al., 2007), has challenged these longstanding models for
their formation. While massive ETGs in large surveys like the SDSS (e.g.
Abazajian et al., 2009) exhibit the well-known optical colour-magnitude
relation with low intrinsic scatter, the same galaxies show almost 6
magnitudes of spread in UV-optical colours (e.g. Kaviraj et al., 2007;
Schawinski et al., 2007). Comparison to the most extreme nearby ‘UV upturn’
ETGs – in which the UV flux is assumed to be driven by old stars – shows that
around a third of massive ETGs have bluer UV-optical colours than even the
strongest UV upturn galaxies. This suggests that these ETGs are likely to have
experienced star-formation events within the last $\sim$0.5 Gyrs, with the
young stars accounting for at least a few percent of the stellar mass of the
galaxy (e.g. Kaviraj et al., 2007).

Interestingly, this large spread in the rest-frame UV-optical colours of
massive ETGs remains virtually unchanged at intermediate redshift ($z\sim
0.5$, e.g. Kaviraj et al., 2008). At this epoch, the Universe is too young for
the UV-producing horizontal-branch to be in place (although binary hot
subdwarfs may appear at earlier epochs), further suggesting a persistent
presence of young stars in the ETG population. It is worth noting that these
UV results are supported by studies that have found strong emission lines
(H$\alpha$$\lambda 6563\AA$ and O[III]$\lambda 5007\AA$) in nearby massive
ETGs (e.g. Fukugita et al., 2004; Dhiwar et al., 2023). A strong coincidence
between the presence of UV flux and morphological disturbances indicative of
(minor) mergers (e.g. Kaviraj et al., 2011) suggests that the trigger for the
star formation seen in the ETG population are interactions with lower mass
galaxies, which bring in the gas that fuels the star formation (Kaviraj et
al., 2009). This picture appears consistent with the presence of molecular gas
in ETGs (e.g. Davis et al., 2015; Williams et al., 2023) and the fact that the
gas and stars are often kinematically misaligned, suggesting an external
origin for the gas (e.g. Combes et al., 2007). Taken together, these studies
demonstrate that, rather than being passively-evolving, many massive ETGs
continue to build stellar mass at late epochs ($z<1$) through low-level star
formation driven by minor mergers, the process that has also been shown to
drive their size evolution (e.g. Newman et al., 2012).

However, some questions remain. The fraction of ETGs with star formation is
often estimated via comparison to the UV-optical colour of strong UV upturn
galaxies, in which the UV flux is assumed to come from old stars. The
rationale is that, if the ETG in question is bluer than strong UV upturn
systems, then some of its UV flux must be contributed by sources other than
old stellar populations, i.e., young stars. For example, Kaviraj et al. (2007)
use $(NUV-r)=5.5$, the rest-frame colour of NGC 4552, as the blue limit that
can be achieved by old stars alone. Since around a third of the ETGs in their
study have $(NUV-r)$ colours are bluer than this value, they conclude that the
fraction of ETGs that host recent star formation is likely to be at least 30
percent. This value is, by construction, a lower limit, which leads to the
question: what fraction of ETGs with $(NUV-r)>5.5$ are likely to host star
formation activity, and could a more precise value for the fraction of star-
forming ETGs be calculated? While the persistent large scatter in the
$(NUV-r)$ colours of ETGs out to $z\sim 0.5$ (where old HB stars do not exist)
argues that the star-forming fraction is probably much larger than 30 percent,
a potential contribution to the UV flux from hot subdwarf stars (which can be
in place at $z\sim 1$) complicates this argument.

An unambiguous route to disentangling the primary source of the UV flux seen
in ETGs is to look for the presence of structure in the UV images. It is well
established that the distribution of optical light in ETGs, which is driven by
the old stellar population, is smooth and devoid of structure (e.g. de
Vaucouleurs, 1959), exhibits relatively high Sérsic indices (typically greater
than 2, e.g. Graham, 2013) and shows low values of morphological parameters
such as asymmetry and clumpiness (e.g. Conselice, 2003). If the UV is driven
by the same old stars, then the UV images will share the smoothness and lack
of structure seen in the optical images. However, since star formation is
inherently patchy (e.g. Crockett et al., 2011), if the UV flux in ETGs is
driven by young stars, then one expects to see significant structure in the UV
images, which should manifest itself as higher values of asymmetry and
clumpiness and lower values of the Sérsic index than what is measured in the
optical. Crucially, this method will indicate the presence of young stars
irrespective of the strength of the UV flux in the ETG in question.

This exercise requires deep, high-resolution images of a large sample of ETGs
in both the optical and UV, ideally where the resolution of the optical and UV
images are similar. It is also best performed at low redshift, where the
structure induced by star formation is well-resolved. The purpose of this
paper to perform such a study, using optical and UV images from the Dark
Energy Camera Legacy Survey (DECaLS , Dey et al., 2019) and the Ultra Violet
Imaging Telescope (UVIT, Tandon et al., 2017) respectively.

Differences in the UV and optical morphologies of ETGs have already been noted
by some past studies. For example, Windhorst et al. (2002) find that galaxies
that are classified as ETGs in the optical wavelengths can show a variety of
morphological structures in the mid-UV that might lead to a different
morphological classification in these wavelengths. Kuchinski et al. (2001)
find that some early-type spiral galaxies have high asymmetry in the FUV,
driven by features that are enhanced in the FUV compared to the optical
images. Mager et al. (2018) have recently studied the UV morphologies of
galaxies of all morphological types (including ETGs) using GALEX images.
Notwithstanding the relatively poor (6 arcsecond) resolution of GALEX, they
find that the measured concentrations and asymmetries of ETGs in the UV
resemble those of spiral and peculiar galaxies in the optical, suggesting the
presence of disks containing recent star formation in the ETG population.
While Mager et al. (2018) do not find significant differences between the
clumpiness of ETG images in the UV and optical, this is most likely due to the
poor resolution of GALEX when compared to ground and space based optical
telescopes. Here, we use deep optical and UV images of ETGs at low redshift
which have similar resolution, enabling us to perform a more precise and
consistent comparison between the optical and UV morphologies in the ETG
population.

The plan for this paper is as follows. In Section 2, we describe the
instruments from which our UV and optical images are derived and the selection
of a sample of nearby ETGs, using morphological classifications from the
Galaxy Zoo citizen-science project (Lintott et al., 2011; Willett et al.,
2013). In Section 3, we first describe the calculation of morphological
parameters (concentration, asymmetry, clumpiness and the Sérsic index) of our
ETGs, in the optical and the UV. We then compare the UV and optical
morphologies, as a function of stellar mass and UV-optical colour, and discuss
our findings in the context of whether the primary UV sources in ETGs are old
or young. We summarise our results in Section 4.

##  2 Data

###  2.1 UVIT

We use archival FUV imaging observations from UVIT, on board AstroSat, for the
morphological analysis of our ETGs in the UV. The FUV observations were
conducted in the BaF2 ($\rm\lambda_{e}\,=\,1541$ Å) or CaF2
($\rm\lambda_{e}\,=\,1481$ Å) broadband filters, over a two-year period
between 2016 and 2017. We employ CCDLAB (Postma & Leahy, 2017) to reduce, and
perform various corrections on, UVIT Level 1 data to create our science-ready
images. A comprehensive catalogue for the entire data set is under preparation
(Piridi et al., in preparation). The UVIT field-of-view (FOV) spans a diameter
of 28′. Here, we only use reduced UVIT images which have effective exposure
times greater than 10 ks, which facilitates the study of faint UV structure in
our ETGs. The 3$\sigma$/ 5$\sigma$ point-source detection limit of the UVIT
FUV observation with the lowest exposure time ($\approx$11 ks) in our sample
is 26.0/25.5 magnitudes. However, the majority of our galaxies have UVIT
observations with exposure times of 22.7 ks which have a 3$\sigma$/5$\sigma$
detection limit of 26.4/25.9 magnitudes. In comparison, the GALEX Deep Imaging
Survey (DIS) observations, which have similar exposure times ($\sim$ 30 ks),
reach a 5$\sigma$ detection limit of 24.8 magnitudes in the FUV filter
(Bianchi et al., 2017), around one magnitude shallower than UVIT. We note
that, even with an increased exposure time with GALEX, the magnitude limit
reached by UVIT observations is unattainable, as the confusion limit of GALEX
for UV sources lies close to 25 mag. The full width at half maximum (FWHM) of
the UVIT FUV point spread function (PSF) varies between 1.3′′ and 1.5′′
(Tandon et al., 2020). This is nearly three (four) times better than GALEX FUV
(NUV) imaging and is comparable to the spatial resolution of large-scale
optical surveys, such as DECaLS.

Figure 1: DECaLS images of a random sample of ETGs in our analysis. Columns
1-4 show galaxies classified as ellipticals, column 5 shows galaxies
classified as S0s and column 6 shows examples of ETGs that are classified as
having signs of an interaction.

###  2.2 DECaLS and SDSS

We use sky-subtracted co-added images from DECaLS , which uses the Dark Energy
Camera (DECam) and offers a sky area of $\sim$1400 deg2 in the northern
hemisphere in three optical bands ($g$, $r$, and $z$). The median FWHM of the
DECaLS PSF is 1.3′′ and the 5$\sigma$ limiting magnitude for a point source
within a single frame in $r$-band is $\sim$23.5 magnitudes. Spectroscopic
redshifts and stellar masses for our galaxies are taken from the GALEX-SDSS-
WISE Legacy Catalog (GSWLC; Salim et al., 2016).

###  2.3 A sample of nearby early-type galaxies

We use visual morphological classifications, provided by the Galaxy Zoo 2
(GZ2) catalogue (Willett et al., 2013), to assemble a sample of ETGs in the
nearby Universe ($z$ $\lesssim$ 0.15). We first select galaxies in GZ2 which
have debiased f_smoothness parameter (Willett et al., 2013) greater than 0.5.
The coordinates of these galaxies are matched with the central coordinates of
the FOVs of UVIT pointings, using a radius of 13.5′, to ascertain whether they
have a UVIT observation.

Figure 2: DECaLS images of a random sample of galaxies that are classified as
late-types and removed from our analysis.

We obtain a 50′′ $\times$ 50′′ FUV cutout for all ETGs that have been observed
with UVIT. We run SExtractor (Bertin & Arnouts, 1996) over the cutouts to
select sources that are above a detection limit of 2$\sigma$, with a minimum
number of nine pixels required for an object to be identified as a source.
This yields an initial sample of 88 galaxies. We then visually inspect the
DECaLS color-composite images of these 88 galaxies to (1) separate our ETGs
into elliptical and S0 galaxies (2) identify objects which have signatures of
an interaction, such as tidal tails and interacting companions and (3)
identify (contaminating) late-type galaxies in the sample. We remove these
late-type galaxies from our analysis. This leaves a parent sample of ETGs
comprising 78 objects, which have stellar masses in the range 108.85 M⊙ $<$ M⋆
$<$ 1011.61 M⊙ and redshifts in the range $0.006<z<0.147$.

Note that, as described in the next section, to ensure reliable estimation of
morphological parameters, we impose additional cuts on the detection signal-
to-noise (SNR) and the signal-to-noise per pixel (SNRpixel) of our galaxies,
which reduces the final sample that is used for the morphological analysis to
32 ETGs. Figure 1 shows DECaLS images of a random sample of ETGs in our
analysis. Columns 1-4 show galaxies classified as ellipticals, column 5 shows
galaxies classified as S0s and column 6 shows examples of ETGs that are
classified as having signs of an interaction. Figure LABEL:fig:ltg_examples
shows example DECaLS images of galaxies that are classified as late-types and
removed from our study.

Before we begin our analysis, it is worth exploring the biases that may be
induced by the detection limits of the UV and optical data used here. Since
our goal is to explore the UV and optical morphologies of ETGs in the context
of star formation, it is important to estimate the redshifts out to which
galaxy populations are complete and the UV red sequence is detectable in these
datasets. Using complete samples allows us to probe the presence of star
formation in objects that span the full range of UV-colours seen in ETGs. This
includes UV-red galaxies where star formation is likely to be weak and the
degeneracy between old and young stars, in terms which dominates the UV
emission, is difficult to break (e.g. in Kaviraj et al. (2007) the UV-red
population is considered to be ETGs where $(NUV-r)$ > 5.5).

We define the redshift at which galaxy populations of a given stellar mass are
complete as the redshift at which a purely-old stellar population of a given
stellar mass, that forms in an instantaneous burst at $z=2$, is detectable, at
the detection limit of the survey in question. We construct this instantaneous
burst using the Yi (2003) stellar models, assuming half solar metallicity.
This corresponds to the metallicity at the mean stellar mass of our sample
($\sim$1010.3 M⊙), calculated using the mass-metallicity relation in the
nearby Universe (e.g. Panter et al., 2008). Such a purely-old population
represents a faintest ‘limiting’ case, since real galaxies, which are not
composed uniquely of old stars, are more luminous than this limiting value. If
this limiting case is detectable at the depth of a survey, then it is
reasonable to conclude that the entire galaxy population at a given stellar
mass will also be detectable.

Figure 3 shows the redshifts at which complete galaxy populations can be
observed in the SDSS $r$-band, the UVIT observations (red and green) and, for
comparison, the GALEX ‘Deep Imaging Survey’ (DIS; orange) and the GALEX ‘All-
Sky Imaging Survey’ (AIS; blue), given the detection limits of the respective
observations. The DIS and AIS represent the deepest and shallowest layers of
the GALEX surveys respectively. The red dashed-dotted line corresponds to the
UVIT observation with the lowest exposure time (10.9 ks), which has a
3$\sigma$ detection limit of 26 magnitudes, while the green solid line
corresponds to a UVIT observation with an exposure time of 22.7 ks which has a
3$\sigma$ detection limit of 26.4 magnitudes. The latter describes most of the
ETGs in this study. The black circles indicate galaxies which are used for our
morphological analysis. The grey circles indicate galaxies which are not
eventually included in our analysis because they fall outside the signal-to-
noise cuts that we impose to ensure robust parameter estimation (see Section
3.1 below). This figure demonstrates that the overwhelming majority of our
ETGs are in parts of the redshift vs stellar mass space where even purely old
stellar populations are visible and galaxy populations will therefore be
complete and unbiased.

Figure 3: Redshifts at which complete galaxy populations can be observed in
the SDSS $r$-band, the UVIT observations (red and green) and, for comparison,
the GALEX ‘Deep Imaging Survey’ (DIS; orange) and the GALEX ‘All-Sky Imaging
Survey’ (AIS; blue), given the detection limits of the respective
observations. The DIS and AIS represent the deepest and shallowest layers of
the GALEX surveys respectively. The red dashed-dotted line corresponds to the
UVIT observation with the lowest exposure time (10.9 ks), while the green
solid line corresponds to a UVIT observation with an exposure time of 22.7 ks
(which describes most of our ETGs). The black circles indicate galaxies which
are used for our morphological analysis. The grey circles indicate galaxies
which are not eventually included in our analysis because they fall outside
the signal-to-noise cuts that we impose to ensure robust parameter estimation
(see text in Section 3.1).

Figure 4: GALEX FUV, UVIT FUV and DECaLS $r$-band images of three galaxies
from our sample. The black crosses represent the optical centroids of each
galaxy. The GALEX-SDSS $(NUV-r)$ color and stellar mass of each galaxy is
indicated on the images. Each panel represents the same region for each
galaxy.

##  3 UV vs optical morphology of nearby ETGs

###  3.1 Measurement of morphological parameters

We use two well-known approaches, the ‘CAS’ system (Conselice et al., 2000;
Conselice, 2003) and the Sérsic index (Sérsic, 1963) to quantitatively compare
the morphology of ETGs in the UV and optical wavebands. We begin by briefly
describing these approaches.

CAS comprises three parameters - concentration ($C$), asymmetry ($A$) and
clumpiness ($S$) - based on a pixel-wise analysis of observed physical
features within galaxies. A rich literature has used the CAS methodology, both
to separate galaxies of different morphological types (e.g. Bershady et al.,
2000) and to identify interesting sub-populations like merging and interacting
galaxies (Conselice et al., 2003). We briefly describe the CAS parameters
below.

The concentration index is calculated by computing the ratio of the radii
which enclose 80 and 20 per cent of the total light of the galaxy
respectively. This parameter is defined as follows:

$\rm\mathit{C}=5\times
log_{10}\left(\frac{\mathit{R}_{80}}{\mathit{R}_{20}}\right)$ (1)

where $R_{\rm 80}$ and $R_{\rm 20}$ correspond to the radii enclosing 80 and
20 per cent of the total light of the galaxy respectively. In massive
galaxies, the light concentration varies significantly as a function of
morphological type (Abraham et al., 1994; Conselice, 2003). For example, the
more strongly peaked flux distribution in ETGs leads to larger values of
concentration in the optical wavelengths compared to their late-type
counterparts (Bershady et al., 2000; Conselice, 2003).

The asymmetry index is obtained by subtracting the original image of the
galaxy from a version where the image is rotated by 180∘. This pixel wise
subtraction is performed out to 1.5 times the petrosian radius
($R\rm_{petro}$). In massive galaxies, this index, when calculated using
optical images, is typically lower in ETGs, which have fewer star-forming
regions, than in their late-type counterparts (Abraham et al., 1996; Bershady
et al., 2000; Conselice, 2003). Asymmetry is defined as follows:

$\rm\mathit{A}=\frac{\sum_{\mathit{i},\mathit{j}}\mid\mathit{I}_{ij}-\mathit{I}_{ij}^{180}\mid}{\sum_{\mathit{i},\mathit{j}}\mid\mathit{I}_{ij}\mid}-\mathit{A}_{bgr}$
(2)

where $I\rm_{i,j}$ and $I\rm_{i,j}^{180}$ are the pixel values of the original
and the rotated images, respectively and $A\rm_{bgr}$ is the asymmetry of the
background.

Finally, the clumpiness parameter (sometimes also called the smoothness
parameter) characterises the patchiness of the light distribution within a
galaxy. The parameter is calculated by subtracting a smoothed image from the
original image of a galaxy, as defined below.

$\rm\mathit{S}=\frac{\sum_{\mathit{i},\mathit{j}}\mathit{I}_{ij}-\mathit{I}_{ij}^{S}}{\sum_{\mathit{i},\mathit{j}}\mathit{I}_{ij}}-\mathit{S}_{bgr}$
(3)

where $I\rm_{i,j}$ and $I\rm_{i,j}^{S}$ are the pixel values of the original
image and its smoothed version, respectively. The smoothed image is obtained
using a boxcar filter of width $\sigma$. The $\sigma$ value used is 0.25
$R\rm_{petro}$, as in Lotz et al. (2004). In massive galaxies, ETGs typically
show a fairly smooth light distribution in the optical wavelengths, resulting
in lower clumpiness indices than their late-type counterparts (Conselice,
2003).

We employ Statmorph (Rodriguez-Gomez et al., 2019) to compute CAS parameters
for our sample of ETGs, using background-subtracted optical $r$-band and UV
images from DECaLS and UVIT respectively. As we are interested in comparing
the CAS parameters of ETGs in the UV and optical wavelengths, we measure the
parameters within the same aperture (1.5 times the FUV petrosian radius) in
both wavebands. The segmentation required by Statmorph to mask neighboring
sources of the main galaxy are generated using SExtractor for both the UV and
DECaLS observations. Weight-maps in the optical are extracted from the archive
for the DECaLS observations, while the FUV weight maps are computed using
SExtractor. Statmorph provides SNRpixel and a flag that quantifies the
reliability of the CAS parameters. The values for the flag are integers
between 0 and 4, which represent ‘good’ to ‘catastrophic’ quality estimates
respectively. We find that 46 (32) out of our 78 galaxies have FUV SNRpixel
greater than 2.0 (2.5) with flagFUV $=$ 0 or 1.

The SNR and spatial resolution of the images in question play a key role in
determining the reliability of CAS measurements (e.g. Conselice et al., 2000;
Lotz et al., 2004; Lotz et al., 2006). We make several further cuts to ensure
the robustness of our morphological parameters. Lotz et al. (2004) show that
the deviation in morphological parameters is less than 10 per cent when they
are derived from images that have SNRpixel $\geq$ 2\. Furthermore, the $A$ and
$S$ parameters are relatively unbiased if calculated using images that have
physical resolutions better than around 1 kpc. Following Lotz et al. (2004) –
see also Rodriguez-Gomez et al. (2015) and Tohill et al. (2021) – we restrict
our study to galaxies which have SNRpixel $\geq$ 2\. This cut reduces our
original sample to 30 (42) galaxies with SNRpixel greater than 2.5 (2),
respectively.

$R_{\rm 20}$ – the radius that encloses 20 per cent of the light – is another
criterion that may impact the reliability of the measured CAS parameters. Lotz
et al. (2006) show that the measured parameters may have artificial values if
20 per cent of the light in a galaxy is concentrated within 1 $-$ 2 pixels.
Statmorph recommends that $R_{\rm 20}$ is greater than half of the PSF FWHM of
the image to ensure that the measured parameters are reliable. We, therefore,
further restrict our study to galaxies where $R_{20}$ $>$ 2 pixels ($\sim$
0.83′′ for UVIT, which is greater than half of the worst PSF FWHM in our UVIT
observations, $\sim$ 1.6′′). With this cut, our final sample contains 23 (32)
galaxies with SNRpixel greater than 2.5 (2), respectively. This sample spans a
very similar mass (108.85 M⊙ < $M_{\star}$ < 1011.6 M⊙) and redshift
($z<0.12$) range as the parent ETG sample described in Section 2. Around 93
per cent of our ETGs reside at redshifts less than 0.03 and the linear
resolution achieved by UVIT up to this redshift is better than 1 kpc.

In Figures 4 and 5, we present a comparison between UVIT and GALEX. Figure 4
shows GALEX FUV, UVIT FUV and DECaLS $r$-band images for two galaxies in our
sample. This figure illustrates the superior resolution of UVIT, which enables
it to resolve finer structure in UV images compared to GALEX. Figure 5 shows a
comparison between the integrated UVIT and GALEX FUV SNRs for our final
sample, computed in a similar manner to Mager et al. (2018). The integrated
UVIT FUV SNRs of our ETGs are greater than 20, with around 40 per cent of the
galaxies detected with UVIT being undetected (or detected with an integrated
SNR $<$ 2) in GALEX.

Figure 5: GALEX (red) and UVIT (blue) SNRs, calculated using integrated FUV
fluxes, for ETGs in our sample that have SNRpixel $\geq$ 2 and $R_{\rm
20}\,>2$ pixels (0.83′′).

The Sérsic function is commonly-used for parametrising the shape of the light
profile of a galaxy (Sérsic, 1963). The function is described as follows:

$I(R)=I_{e}\Bigg{\\{}-b_{\rm n}\Bigg{[}\Bigg{(}\frac{R}{R_{\rm
e}}\Bigg{)}^{\frac{1}{n}}-1\Bigg{]}\Bigg{\\}},$ (4)

where $R_{\rm e}$ is the radius enclosing half the light of the galaxy,
$I_{\rm e}$ is the intensity at $R_{\rm e}$ and $b_{\rm n}$ is a function of
the Sérsic index ($n$). We fit one-dimensional Sérsic profiles to the
isophotal distributions in the FUV and $r$-band images of our ETGs, using
PROFILER (Ciambur, 2016). While fitting isophotes to the optical light
profiles is straightforward, the FUV light profiles are more irregular. This
is directly related to the significant amounts of structure that exists in the
UV images, as discussed in Section 3.2 below. We, therefore, adopt several
steps in the Sérsic fitting to the FUV images of our ETGs. The FUV images are
first convolved with a Gaussian function, which reduces noise in the images
and helps determine the position of the centroid of each galaxy. The isophotal
fluxes are then measured on the original FUV images. A Sérsic profile can be
successfully derived from the FUV surface-brightness distribution for 19
galaxies. Of these, the errors in the measurement of $n$ ($\Delta\,n$) are
less than 0.25 for ten galaxies, and the remaining nine exhibit errors between
0.25 and 1. The FUV light profiles of the remaining ETGs are not smooth enough
to fit a Sérsic function.

The light profiles of some of our ETGs are shown in Figure 6. While the error
bars on individual points are plotted, they are too small to be visible. The
left-hand column shows examples of ETGs in which the FUV profiles show a
significant lack of smoothness (although the mean error in the surface
brightness is $\sim$ 0.1 mag/arcsec-2). The lack of smoothness of the FUV
light profiles is driven by the presence of underlying structure in the FUV
images. The right-hand column shows examples of galaxies where Sérsic
functions can be successfully fitted to both the FUV and optical images. Table
1 lists the coordinates, physical properties and morphological parameters of
the ETGs which are included in our analysis. Recall that these are galaxies
with FUV SNRpixel $\geq$ 2 and R20 $>$ 2 pixels (0.83′′).

Table 1: Coordinates, morphological and structural parameters and physical properties in the UVIT FUV and DECaLS $r$-band of our ETGs with FUV SNRpixel $\geq$ 2 and $R_{\rm 20}$ $>$ 2 pixels (0.83′′). ID | RA (J2000) | Dec (J2000) | $z$ |  CFUV |  AFUV |  SFUV |  Cr |  Ar |  Sr |  nFUV |  nr | $NUV-r$ |  log ($M_{\star}$/ M⊙)
---|---|---|---|---|---|---|---|---|---|---|---|---|---
1 | 12:29:59.10 | +12:20:55.2 | 0.007 | 2.24 | 0.507 | 0.163 | 2.778 | 0.099 | 0.002 |  1.37 $\pm$ 0.09 |  2.87 $\pm$ 0.02 | 4.89 | 10.3
2 | 12:59:19.87 | +28:05:03.4 | 0.015 | 2.59 | 0.361 | 0.221 | 2.805 | 0.034 | 0.013 |  |  3.10 $\pm$ 0.09 | 5.71 | 10.42
3 | 13:00:54.45 | +28:00:27.4 | 0.017 | 3.15 | 0.19 | 0.186 | 3.05 | 0.014 | -0.002 |  |  3.18 $\pm$ 0.01 | 5.91 | 10.75
4 | 13:00:09.14 | +27:51:59.3 | 0.018 | 2.77 | 0.235 | 0.122 | 2.576 | 0.158 | 0.023 |  2.02 $\pm$ 0.16 |  1.46 $\pm$ 0.03 | 2.89 | 9.31
5 | 13:02:21.52 | +28:13:50.8 | 0.019 | 2.98 | 0.2 | 0.483 | 3.224 | 0.031 | 0.043 |  |  2.68 $\pm$ 0.01 | 5.8 | 10.28
6 | 11:42:59.06 | +20:05:12.7 | 0.02 | 2.3 | 0.164 | 0.277 | 3.409 | 0.019 | 0.0 |  |  4.19 $\pm$ 0.13 | 5.71 | 10.43
7 | 11:44:02.16 | +19:56:59.4 | 0.021 | 3.03 | 0.394 | 0.262 | 3.218 | 0.004 | -0.005 |  2.11 $\pm$ 0.09 |  4.9 $\pm$ 0.06 | 5.63 | 11.39
8 | 11:43:56.42 | +19:53:40.5 | 0.021 | 2.69 | 0.406 | 0.208 | 3.119 | 0.023 | -0.003 |  3.28 $\pm$ 0.26 |  3.77 $\pm$ 0.03 | 5.74 | 11.0
9 | 11:44:02.16 | +19:58:18.9 | 0.021 | 2.81 | 0.275 | 0.33 | 3.438 | 0.016 | 0.005 |  |  5.28 $\pm$ 0.06 | 5.61 | 10.65
10 | 13:00:42.76 | +27:58:16.5 | 0.021 | 3.16 | 0.185 | 0.177 | 3.083 | 0.043 | 0.002 |  |  4.09 $\pm$ 0.1 | 5.77 | 10.57
11 | 13:00:08.13 | +27:58:37.0 | 0.022 | 2.95 | 0.167 | 0.139 | 2.989 | 0.014 | -0.002 |  3.59 $\pm$ 0.18 |  4.18 $\pm$ 0.05 | 5.19 | 11.61
12 | 11:43:01.19 | +19:54:35.3 | 0.022 | 2.58 | 0.417 | 0.285 | 2.514 | 0.022 | 0.019 |  2.75 $\pm$ 0.44 |  2.3 $\pm$ 0.07 | 3.53 | 9.09
13 | 11:44:05.75 | +20:14:53.5 | 0.022 | 2.51 | 0.409 | 0.318 | 3.208 | 0.023 | -0.002 |  1.99 $\pm$ 0.79 |  2.46 $\pm$ 0.11 | 4.44 | 10.11
14 | 12:59:43.73 | +27:59:40.9 | 0.022 | 3.51 | 0.178 | 0.19 | 3.027 | 0.03 | 0.018 |  3.22 $\pm$ 0.56 |  3.66 $\pm$ 0.08 | 5.9 | 10.2
15 | 12:59:29.41 | +27:51:00.5 | 0.023 | 2.95 | 0.336 | 0.26 | 3.099 | 0.039 | 0.001 |  |  1.97 $\pm$ 0.04 | 5.82 | 10.44
16 | 13:02:21.66 | +28:15:21.5 | 0.023 | 2.54 | 0.316 | 0.259 | 2.542 | 0.023 | -0.002 |  |  1.11 $\pm$ 0.03 | 5.72 | 10.41
17 | 13:00:48.65 | +28:05:26.6 | 0.023 | 3.39 | 0.234 | 0.238 | 3.256 | 0.012 | -0.001 |  |  2.59 $\pm$ 0.03 | 5.67 | 10.73
18 | 13:00:27.97 | +27:57:21.5 | 0.023 | 2.8 | 0.094 | 0.201 | 3.207 | 0.028 | -0.005 |  |  2.36 $\pm$ 0.14 | 6.14 | 10.2
19 | 12:59:44.41 | +27:54:44.8 | 0.023 | 3.57 | 0.162 | 0.161 | 3.209 | 0.024 | 0.015 |  |  2.02 $\pm$ 0.03 | 5.86 | 10.56
20 | 13:00:40.85 | +27:59:47.8 | 0.024 | 2.39 | 0.219 | 0.213 | 2.914 | 0.016 | -0.005 |  |  1.79 $\pm$ 0.03 | 5.9 | 10.48
21 | 12:59:34.12 | +27:56:48.6 | 0.024 | 3.28 | 0.01 | 0.116 | 3.698 | 0.045 | 0.003 |  |  5.15 $\pm$ 0.15 | 4.93 | 10.55
22 | 13:00:06.39 | +28:00:14.9 | 0.024 | 2.79 | 0.21 | 0.247 | 3.158 | 0.028 | -0.003 |  1.39 $\pm$ 0.16 |  3.0 $\pm$ 0.07 | 5.97 | 9.95
23 | 13:00:39.76 | +27:55:26.2 | 0.025 | 3.34 | 0.249 | 0.472 | 3.59 | 0.011 | -0.004 |  1.73 $\pm$ 0.61 |  2.71 $\pm$ 0.02 | 6.16 | 10.7
24 | 13:00:06.25 | +27:41:07.1 | 0.025 | 2.66 | 0.124 | 0.243 | 3.007 | 0.04 | 0.016 |  |  3.7 $\pm$ 0.05 | 5.44 | 10.07
25 | 12:59:37.91 | +27:54:26.3 | 0.027 | 3.67 | 0.134 | 0.252 | 3.359 | 0.024 | 0.015 |  2.44 $\pm$ 0.87 |  3.38 $\pm$ 0.08 | 5.98 | 10.54
26 | 12:59:56.01 | +28:02:05.0 | 0.027 | 3.14 | 0.285 | 0.257 | 3.009 | 0.019 | 0.022 |  |  2.21 $\pm$ 0.02 | 5.77 | 10.81
27 | 13:00:22.13 | +28:02:49.2 | 0.027 | 2.97 | 0.277 | 0.278 | 3.029 | 0.023 | 0.008 |  3.33 $\pm$ 0.53 |  2.42 $\pm$ 0.03 | 6.02 | 10.59
28 | 13:00:33.36 | +27:49:27.3 | 0.027 | 2.4 | 0.221 | 0.353 | 2.712 | 0.009 | 0.007 |  |  1.72 $\pm$ 0.03 | 4.84 | 9.96
29 | 12:59:54.86 | +27:47:45.6 | 0.028 | 2.22 | 0.233 | 0.242 | 2.95 | 0.018 | -0.008 |  |  2.32 $\pm$ 0.09 | 4.58 | 9.88
30 | 13:00:08.06 | +27:46:23.9 | 0.029 | 2.68 | 0.249 | 0.149 | 2.748 | 0.175 | 0.011 |  2.1 $\pm$ 0.13 |  1.99 $\pm$ 0.07 | 2.55 | 8.85
31 | 14:53:45.02 | +18:34:06.1 | 0.072 | 1.95 | 0.289 | 0.276 | 3.029 | 0.035 | -0.004 |  |  2.73 $\pm$ 0.07 | 5.55 | 11.01
32 | 12:19:14.58 | +29:51:21.8 | 0.102 | 2.4 | 0.201 | 0.141 | 2.716 | 0.03 | 0.053 |  1.41 $\pm$ 0.15 |  2.69 $\pm$ 0.08 | 3.0 | 10.64
Figure 6: Surface brightness profiles for a subset of our ETGs, in the DECaLS
$r$-band (red filled circles) and the UVIT FUV (blue filled circles). The 1-D
Sérsic fits to the $r$-band and FUV profiles are represented by the red and
black points respectively. The left-hand column shows examples of ETGs in
which a Sérsic function could not be fitted to the FUV surface brightness
profiles because they are not smooth enough, while the right-hand column shows
examples of galaxies where Sérsic indices could be derived in both the FUV and
$r$-band. Figure 7: A comparison of the CAS parameters calculated from the FUV
and $r$-band images of our ETGs. Elliptical (E) and lenticular (S0) galaxies
are shown using different symbols. The parameters are measured within the same
aperture in both bands (1.5 times the FUV petrosian radius). The larger
markers indicate galaxies with SNRpixel $\geq$ 2.5, while the smaller markers
indicate galaxies with SNRpixel between 2.0 and 2.5. The left-hand column
plots the FUV vs $r$-band values of each parameter. The right-hand column
plots the GALEX-SDSS $(NUV-r)$ colour vs stellar mass, colour-coded by the log
of the ratio between the FUV and $r$-band values of the parameter in question.
Galaxies that are interacting are shown using grey crosses.

###  3.2 FUV and optical morphologies of ETGs are different - the UV emission
in ETGs is driven by star formation

We proceed by comparing the quantitative morphologies of our ETGs in the
optical and FUV using the CAS parameters calculated in the previous section.
The left-hand column of Figure 7 compares concentration (top row), asymmetry
(middle row) and clumpiness (bottom row) in the FUV and optical wavelengths.
Recall that, in each galaxy, the CAS parameters are measured in the same
aperture (1.5 times the FUV petrosian radius) for both bands. The right-hand
column plots the GALEX-SDSS $(NUV-r)$ colour vs stellar mass, with the
galaxies colour-coded by the log of the ratio between the FUV and optical
values of the parameter in question. Galaxies with FUV SNRpixel $\geq$ 2.5 are
shown using larger symbols, while those with FUV SNRpixel between 2.0 and 2.5
are shown using smaller symbols. Interacting galaxies are indicated using grey
crosses. We note that the results do not change if the region within which
these parameters are measured is not restricted to 1.5 times the FUV petrosian
radius (see Figure 9 in the appendix).

We use the $(NUV-r)$ colour in our analysis for consistency with the previous
literature. Recall that $(NUV-r)$ serves as a useful tracer of the age of the
dominant stellar population in galaxies (e.g. Yi et al., 2005; Kaviraj et al.,
2007). ETGs in which the presence of recent star formation is considered
likely, based on integrated photometry, lie blueward of $(NUV-r)=5.5$ (Kaviraj
et al., 2007). ETGs with $(NUV-r)>5.5$, on the other hand, are relatively
passive, and there is some ambiguity about whether the dominant UV sources in
this galaxies are old or young. Evidently, our ETG sample spans the full
spectrum of systems, from those that are clearly star-forming to those that
are relatively passive. Indeed, at the higher end of our stellar mass range,
the sample is dominated by galaxies redder than $(NUV-r)=5.5$.

The mean values and standard deviations of Cr, Ar and Sr are 3.05 $\pm$ 0.28,
0.035 $\pm$ 0.037 and 0.007 $\pm$ 0.014, respectively, consistent with the
optical CAS parameters of ETGs derived in the literature (e.g. Conselice,
2003; Lotz et al., 2004; Hernández-Toledo et al., 2008; Hambleton et al.,
2011; Mager et al., 2018). In agreement with past work, our ETGs display
negligible clumpiness and asymmetry in their optical images which are
dominated by the old stellar populations that form the bulk of their stellar
mass. In contrast, the mean values and standard deviations of CFUV, AFUV and
SFUV are 2.82 $\pm$ 0.42, 0.247 $\pm$ 0.104 and 0.241 $\pm$ 0.085,
respectively. The values remain virtually unchanged if we restrict our ETGs to
the subset with FUV SNRpixel $\geq$ 2.5. While Cr is comparable or, in some
cases, lower than CFUV, we find significant differences between the asymmetry
and clumpiness parameters across the FUV and optical wavelengths. The values
of $A_{\rm FUV}$ and $S_{\rm FUV}$ are always greater than their optical
counterparts. Across our ETGs, the mean FUV-to-optical ratios of asymmetry and
clumpiness are $\sim$13 and $\sim$82, respectively. The asymmetry and
clumpiness in the FUV are typically at least several factors (and in some
cases several orders of magnitude) larger than their optical counterparts. It
is worth noting that these trends are present irrespective of the stellar
mass, $(NUV-r)$ colour or the presence of an interaction in our ETGs.

Asymmetry and clumpiness (particularly the latter) trace structure in galaxy
images. The significant differences seen in the CAS parameters in the UV and
optical indicate that the light in these two wavebands do not originate from
the same stellar populations in our ETGs. Since the optical light in ETGs is
known to come from old stars, our results indicate that the UV is not driven
by these old stellar populations. Furthermore, star formation is inherently
patchy which causes galaxies with later type morphologies to have higher
asymmetry and clumpiness in all wavelengths (e.g. Mager et al., 2018; Cheng et
al., 2021). The high asymmetry and clumpiness values in the UV demonstrate the
presence of star formation in our ETGs. Note that most of the very massive
(non-interacting) UV-red ETGs ($M_{\star}$ > 1010.5 M⊙) in our sample show
$A_{\rm FUV}$/$A_{r}$ and $S_{\rm FUV}$/$S_{\rm r}$ values greater than 10,
implying the presence of star-forming regions even in relatively passive ETGs.
The fact that the structure is only seen in the UV and not in the optical
confirms the suggestion in past work (e.g. Kaviraj et al., 2007) that the star
formation in most ETGs is at a relatively low level, which affects the star
formation sensitive UV image but not its optical counterpart.

Finally, it is worth noting that seven ETGs in our sample (IC 3976, NGC 4875,
NGC 4889, NGC 4883, NGC 4872, IC 4045 and LEDA 44656) are classified as ‘UV
upturn’ galaxies (Deharveng et al., 2002; Ali et al., 2018), in which the UV
flux is assumed to be driven exclusively by old stars. Such systems have been
typically selected using combinations of UV, optical and mid-infrared colours
(e.g. Yi et al., 2011; Ali et al., 2018) which minimize the contribution of
young stars to the UV. However, notwithstanding the assumption of old stars
driving the UV flux in these system, the mean FUV-to-optical ratios of
asymmetry ($\sim$9) and clumpiness ($\sim$93) are as high in UV upturn systems
as it is in the rest of our ETG population. This suggests that the UV fluxes
in these galaxies are also driven by (or at least significantly influenced by)
recent star formation and not only by the old stellar population. Although the
sample of such objects is relatively small, the large differences between the
UV and optical morphologies in these UV upturn galaxies suggests that an
assumption about old stars driving the UV flux in such systems cannot be made
using integrated UV colours alone.

It is worth considering our results in the context of Mager et al. (2018), who
have performed the first systematic study of massive galaxies, of all
morphological types, across the UV and optical wavelengths, using GALEX and
HST observations respectively. Interestingly, the most substantial differences
seen within a morphological class in this study are between the concentration
and asymmetry of ETGs in the optical and UV wavelengths. In a similar vein to
our results, they find that $C_{\rm FUV}$ and $A_{\rm FUV}$ in ETGs are higher
than their optical counterparts and mirror that of spiral and irregular
galaxies. While the authors do not arrive at a similar conclusion for the
$S_{\rm FUV}$ parameter, this is likely due to the fact that the relatively
low resolution of GALEX washes out small-scale structure in the UV images. In
contrast, the much higher resolution of our UV images (which are well-matched
to the resolution of the optical images) enables us to quantify the
differences in both clumpiness and asymmetry in ETGs across the UV and optical
wavelengths. Mager et al. (2018) conclude that the differences in the
morphological parameters in ETGs between the UV and optical wavelengths can be
explained by the presence of extended disks that contain recent star
formation, consistent with the conclusions of our study.

Figure 8: A comparison between the Sérsic indices calculated from the FUV and
$r$-band images of our ETGs. Galaxies that are ellipticals (E) and those that
are lenticular (S0) are shown using different symbols. The larger symbols
indicate galaxies where $\Delta n\leq 0.25$ (where $\Delta n$ is the error in
$n$), while the smaller symbols indicate galaxies with 0.25 $<\Delta n\leq$
1\. The galaxies are colour-coded by the log of the ratio between the FUV and
$r$-band Sérsic indices. Galaxies that are interacting are shown using
crosses.

We complete our study by comparing the Sérsic indices of our ETGs in the UV
and optical wavelengths. Figure 8 plots the $(NUV-r)$ colour vs stellar mass
of our ETGs, colour-coded by the ratio of the Sérsic indices in the UV and
optical wavelengths. As noted in Section 3.1, the lack of smoothness of the
FUV profile, which is a direct result of the structure seen in the UV image,
prevents us from fitting a Sérsic function in the FUV to around 55 per cent of
our ETGs. Therefore, the comparison can only be made for a subset of our
galaxies (see numbers in Section 3.1). The mean values of $n_{\rm FUV}$ and
$n_{\rm r}$ for ETGs corresponding to $\Delta n$ $<$ 0.25 (1) are 2.06 (2.14)
and 3.21 (3.15), respectively. In the vast majority of ETGs, the Sérsic
indices in the UV are lower than in the optical. The mean value and standard
deviation of $n_{\rm{FUV}}$/$n_{\rm{r}}$ is 0.7 $\pm$ 0.3. In line with the
conclusions from the morphological parameters above, this suggests that the UV
light in our ETGs is more extended (or flatter) than in the optical,
potentially signposting the presence of extended disks, as hypothesised by the
study of Mager et al. (2018).

##  4 Summary

The unexpected recent discovery of the ubiquitous presence of UV sources in
nearby ETGs has challenged traditional models for their evolution, which
postulate their formation in rapid starbursts at high redshift followed by
passive ageing thereafter. The UV fluxes in many ETGs appear stronger than
what can be produced via old stars alone, indicating the presence of recent
star formation. The coincidence of blue UV-optical colours, gas and
morphological disturbances out to at least intermediate redshift indicates the
persistent presence of merger-driven star formation in ETGs at late epochs.
Nevertheless, the possibility of the UV flux having contributions from both
old and young stars, coupled with uncertainties in theoretical models, means
that a definitive conclusion about the presence of star formation in all ETGs
is difficult to achieve using integrated photometry alone.

An unambiguous way of disentangling the source of the UV flux in ETGs is to
look for the presence of structure in the UV images. Old stars dominate the
optical images of ETGs, which are smooth, devoid of structure, exhibit low
values of morphological parameters, such as asymmetry and clumpiness, and high
values of the Sérsic index. If the UV is also driven by old stars then the UV
images will share the smoothness and lack of structure seen in the optical
images. If, on the other hand, it is driven by young stars, then there should
be significant structure in the UV images, which will manifest itself as
higher values of asymmetry and clumpiness and lower values of the Sérsic index
than what is measured in the optical wavelengths. Crucially, this is true
regardless of the strength of the UV flux, making this method a more effective
discriminator between old and young-star driven UV flux than integrated
photometry.

Here, we have compared the UV and optical morphologies of a sample of 32 ETGs
at $z<0.12$, 93 per cent of which have redshifts less than 0.03. We have used
deep UV and optical images from the DECam (via the DECaLS survey) and UVIT,
which have similar resolution, which enables an ‘apples-to-apples’ comparison.
Furthermore, our ETGs lie in the part of the redshift vs stellar mass plane
where galaxy populations are complete and unbiased, allowing us to probe the
presence of star formation regardless of the strength of the UV flux in our
ETGs. Our main results are as follows:

  * •

Regardless of stellar mass, UV-optical colour or the presence of an
interaction, the asymmetry and clumpiness of ETGs is typically significantly
larger in the UV than in the optical. The mean FUV to optical ratios of
asymmetry and clumpiness are $\sim$13 and $\sim$82 respectively. The asymmetry
and clumpiness in the FUV are typically at least several factors (and in some
cases several orders of magnitude) larger than in their optical counterparts.
The significant amounts of UV structure indicates that the UV flux in all ETGs
in our sample is either dominated by, or has a significant contribution from,
young stars.

  * •

Interestingly, the trends above are also seen in seven ETGs which are
classified as UV upturn systems in the literature i.e. galaxies in which the
UV flux is assumed to be driven solely by old stars. This assumption appears
incorrect, at least in these ETGs. It is plausible that the same may be true
of other UV upturn systems, suggesting that the assumption of old stars
driving the UV flux in such systems cannot be made on the basis of integrated
UV colours alone.

  * •

Mirroring the results from the morphological parameters, the Sérsic indices of
ETGs are lower in the UV than in the optical, suggesting the presence of disky
structures. Furthermore, unlike in the optical, the significant UV structure
produces FUV radial profiles which are not smooth, making it difficult to fit
Sérsic parameters to around 55 per cent of our ETGs.

Our results provide independent evidence and important corroboration for
recent work that suggests the presence of star formation in ETGs. This has
been based both on the widespread presence of UV sources in local ETGs and the
fact that the distribution of their UV-optical colours appears unchanged out
to intermediate redshift (where the Universe is too young for old stars to be
in place). The ubiquitous presence of structure in the FUV images of our ETGs,
regardless of stellar mass, UV-optical colour and the presence of
interactions, indicates that all ETGs, including those on the UV red sequence,
host star formation.

## Acknowledgements

DP thanks Sonika Piridi for assistance in UVIT data reduction. DP also
acknowledges the Inter University Centre for Astronomy and Astrophysics
(IUCAA), Pune, India for providing hospitality and travel grants. SK
acknowledges support from the STFC [grant number ST/X001318/1] and a Senior
Research Fellowship from Worcester College Oxford. KS acknowledges support
from the Indian Space Research Organisation (ISRO) funding under project
PAO/REF/CP167. For the purpose of open access, the authors have applied a
Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript
version arising from this submission.

## Data Availability

The GALEX-SDSS-WISE Legacy Catalog can be found at:
https://salims.pages.iu.edu/gswlc/. Data from the Galaxy Zoo citizen-science
project is located at: https://data.galaxyzoo.org/. This publication uses
archival data from the AstroSat mission of the Indian Space Research
Organisation (ISRO), which is archived at the Indian Space Science Data Centre
(ISSDC) and can be found here:
https://astrobrowse.issdc.gov.in/astro_archive/archive/Home.jsp. Data from the
DECaLS survey is located at: https://www.legacysurvey.org/decamls/.

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##  Appendix A UV and optical morphological parameters not restricted to the
same region of the galaxy

The analysis presented in the sections above employs morphological parameters
in the UV and optical that are derived within 1.5 times the petrosian radius
in the FUV image. Restricting the calculation to the same region of the galaxy
enables us to perform a like-with-like comparison of UV and optical
morphology. In this section we present, in Figure 9, a comparison of UV and
optical morphology without this restriction. Here, the UV and optical
parameters are derived within 1.5 times the petrosian radius of the image in
question. We find that the general trends in the UV and optical CAS parameters
remain unchanged. Our results are therefore not sensitive to the region of the
galaxy within which the CAS parameters are calculated in the UV and optical
wavelengths.

Figure 9: A comparison between the CAS parameters calculated from FUV and
$r$-band images of our ETGs. Galaxies that are ellipticals (E) and those that
are lenticular (S0) are shown using different symbols. Unlike Figure 7, the
parameter measurements in the UV and optical are not restricted to the same
apertures in both bands. The larger symbols indicate galaxies with SNRpixel
$>$ 2.5, while the smaller symbols indicate galaxies with SNRpixel between 2.0
and 2.5. The left-hand column plots the FUV vs $r$-band values of each
parameter. The right-hand column plots the GALEX-SDSS $(NUV-r)$ colour vs
stellar mass colour coded by the log of the ratio between the FUV and $r$-band
values of the parameter in question. Galaxies that are interacting are shown
using grey crosses.