# UV Absorption by Silicate Cloud Precursors in Ultra-hot Jupiter WASP-178b

Joshua D. Lothringer These authors contributed equally to this work. *e-mail:
<EMAIL_ADDRESS><EMAIL_ADDRESS>Department of Physics, Utah Valley
University, Orem, UT 84058, USA  Department of Physics and Astronomy, Johns
Hopkins University, Baltimore, MD, USA  David K. Sing  Department of Physics
and Astronomy, Johns Hopkins University, Baltimore, MD, USA  Department of
Earth & Planetary Sciences, Johns Hopkins University, Baltimore, MD, USA
Zafar Rustamkulov  Department of Earth & Planetary Sciences, Johns Hopkins
University, Baltimore, MD, USA  Hannah R. Wakeford  School of Physics,
University of Bristol, HH Wills Physics Laboratory, Tyndall Avenue, Bristol
BS8 1TL, UK  Kevin B. Stevenson  Johns Hopkins University Applied Physics
Laboratory, Laurel, MD 20723, USA  Department of Earth & Planetary Sciences,
Johns Hopkins University, Baltimore, MD, USA  Nikolay Nikolov  Space Telescope
Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA  Panayotis
Lavvas  Groupe de Spectrométrie Moléculaire et Atmosphérique, Université de
Reims, Champagne-Ardenne, CNRS UMR F-7331, France  Jessica J. Spake
Department of Astronomy, California Institute of Technology, Pasadena CA
91125, USA  Autumn T. Winch  Department of Physics, Bryn Mawr College, Bryn
Mawr, PA, USA

Aerosols have been found to be nearly ubiquitous in substellar atmospheres1,
2, 3. The precise temperature at which these aerosols begin to form in
exoplanets has yet to be observationally constrained. Theoretical models and
observations of muted spectral features suggest that silicate clouds play an
important role in exoplanets between at least 950 and 2,100 K 4. However, some
giant planets are thought to be hot enough to avoid condensation altogether5,
6. Here, we present the near-UV transmission spectrum of an ultra-hot Jupiter,
WASP-178b ($\sim$2,450 K), that exhibits significant NUV absorption. This
short-wavelength absorption is among the largest spectral features ever
observed in an exoplanet in terms of atmospheric scale heights. Bayesian
retrievals indicate the presence of gaseous refractory species containing
silicon and magnesium, which are the precursors to condensate clouds at lower
temperatures. SiO in particular has not been detected in exoplanets before,
but the presence of SiO in WASP-178b is consistent with theoretical
expectation as the dominant Si-bearing species at high temperatures. These
observations allow us to re-interpret previous observations of HAT-P-41b and
WASP-121b that did not consider SiO to suggest that silicate cloud formation
begins on exoplanets with equilibrium temperatures between 1,950 and 2,450 K.

We observed one transit of the ultra-hot Jupiter WASP-178b/KELT-26b7, 8
(WASP-178b hereafter) with HST/WFC3/UVIS using the G280 grism (0.2-0.8 $\mu$m,
R$\sim$70) on September 5th, 2020 as part of Program 16086 (PI: Lothringer).
WASP-178b is unique among known exoplanets for its especially hot host star:
at A1 IV-V and T${}_{\textrm{eff}}$=9360 K, WASP-178 is second-only to KELT-9
as the hottest planet-hosting star. Time-series spectra were obtained over 7.5
hours centered around the transit event, and were used to extract the
transmission spectra which probes the middle and upper atmosphere around the
day-night terminator. Further details regarding the data reduction and
observational setup are given in the Methods.

The resulting spectrum is shown in Fig. 1. A steep rise in transit depth is
seen toward short wavelengths, beginning at about 0.35 $\mu$m. The difference
in NUV transit depth (0.2-0.28 $\mu$m) compared the optical transit depth
(0.35-0.8 $\mu$m) is 2,500$\pm$138 ppm, an 18.0$\sigma$ significance. In terms
of the equilibrium atmospheric scale height (calculated at the equilibrium
temperature and assuming an H2-dominated atmosphere), the NUV transit depths
rise nearly 20 scale heights above the optical continuum, making this one of
the largest known spectral features yet seen in an exoplanet atmosphere. A
lack of transit asymmetry indicates that this absorption is present on each
limb (see Extended Data Fig. 1 and Methods). We are able to rule out a
scattering slope from, e.g., photochemical hazes, as well as stellar
inhomogeneities as causes for this feature (see Methods). We are thus
confident that the rise in the transit depths at NUV wavelengths is due to
absorption by gaseous species in the atmosphere of WASP-178b.

We ran a series of retrievals to obtain constraints on the atmospheric
properties from the observations (see Table 1). The retrievals included free
parameters for the abundance of major NUV and optical absorbers, including
SiO, TiO, VO, Fe I, Fe II, Mg I, and Mg II, plus a general [Fe/H] parameter
for the abundance of all other atmospheric species. We also used a five-
parameter temperature structure parameterization (described in Methods). Fig.
1 shows the retrieved best fit spectrum from our fiducial retrieval with all
opacity sources present and the contribution from these various opacity
sources. Also plotted are the constraints on the temperature structure. The
maximum transit depths of about 1.5% correspond to a radius of about 2
$R_{\textrm{Jupiter}}$. This corresponds to a pressure of about a microbar,
similar to the strong lines of Na and K at high spectral resolution.

In all the retrievals we tested, two scenarios were able to fit the data: 1)
an atmosphere with an approximately solar abundance of SiO or 2) an atmosphere
with a super-solar abundance of Mg I and Fe II but with no SiO. SiO absorbs
throughout the 0.2-0.35 $\mu$m range, enabling a good fit to the data. On the
other hand, bound-free opacity from Mg I absorbs shortward of 0.255 $\mu$m 9,
10, while Fe II absorbs between 0.24 and 0.3 $\mu$m. Thus the combined
absorption from Mg I and Fe II is also able to provide an adequate fit to the
observations, albeit at super-solar abundances (see Extended Data Fig. 2).
Taken in tandem, our analysis indicates that there is strong evidence
($\Delta{BIC}=8.39$) that SiO or Mg must be present in the atmosphere of
WASP-178b to explain our observations. Since both Mg and SiO are the major
constituents of silicate condensates like enstatite (MgSiO3) and forsterite
(Mg2SiO4), we can say with equally high confidence that silicates have not
rained out at the terminator of WASP-178b. Owing to the lack of transit
asymmetry mentioned above, this result holds for both the evening and morning
terminator.

This result is in line with theoretical expectations. Previous studies have
pointed out that above 2,000 K, SiO is expected to be a major absorber
shortward of 0.4 $\mu$m at its chemical equilibrium abundance 11, 12 and so we
would expect to see it in the transit spectrum a priori (also see Extended
Data Fig. 3). Similarly, we expect many neutral and ionized atomic species to
be present, as indicated by chemical equilibrium calculations and high-
resolution observations e.g., 13. While SiO and Mg I + Fe II independently
provide good fits to the data, our prior expectation based on chemical
equilibrium is that each of these opacity sources are likely present.

The non-detection of neutral and ionized Fe is somewhat surprising since the
species has been detected in planets of similar temperature, like
KELT-20b/MASCARA-2b14, WASP-76b15, 16, WASP-121b 17, 18, 13, 19. The apparent
absence of significant Fe I absorption in WASP-178b’s spectrum could be
explained by the high temperatures and high UV flux from the A-type host star
ionizing most of the Fe I. Ground-based high-resolution studies of WASP-178b
could provide a comprehensive census of neutral and ionized refractory
species, as has been done for other ultra-hot Jupiters 20, 13, 21.

To spectrally resolve potentially escaping neutral and ionized Fe and Mg
features, we additionally analyzed high resolution NUV transit data of
WASP-178b HST data taken with STIS/E230M (see Methods). The STIS data shows no
evidence for either Fe II or Mg II (see Extended Data Fig. 7), even though
both elements were easily detected in similar data of WASP-121b17. The STIS
E230M transmission spectrum is in good agreement with the broadband UVIS
spectrum, indicating unresolved escaping Fe II and Mg II lines are not the
cause of the NUV absorption feature in the UVIS spectrum, with continuum level
absorption by SiO, Mg I, and Fe II the most likely scenario.

Only a handful of observations exist that are precise enough to measure the
continuum of exoplanets shortward of 0.35 $\mu$m: HAT-P-41b (Teq = 1950 K) has
been observed with a similar setup to our observations of WASP-178b (i.e.,
HST/WFC3/UVIS/G280)22, while WASP-121b (Teq = 2350 K) has been observed at
high-resolution with HST/STIS/E230M with 4 binned points between 0.23 and 0.31
$\mu$m17. A clear difference between the spectrum of HAT-P-41b and those of
the hotter WASP-121b and WASP-178b is apparent (see Fig. 2). While WASP-121b’s
transit spectrum indicates a similar level of absorption at NUV wavelengths to
WASP-178b, HAT-P-41b’s spectrum shows a definite absence of absorption on both
limbs at these same wavelengths. This dichotomy suggests that while gaseous
refractory species like SiO, Mg, and Fe are abundant in the atmospheres of
WASP-121b and WASP-178b, such species have rained out of the gaseous phase in
HAT-P-41b. Because some of the NUV absorption in WASP-121b is from escaping
exospheric metals 17 and the difference between the morning and evening
terminator has not been well-constrained like WASP-178b, we choose to define
the equilibrium temperature of WASP-178b as the empirical upper limit for the
onset of silicate condensation in hot Jupiters. Therefore, silicate
condensation at the terminators must begin between equilibrium temperatures of
1,950 K and 2,450 K.

This empirical constraint on the onset of condensation is consistent with
theoretical predictions 23, 4. Fig. 3 compares pressure-temperature profiles
from theoretical 1D atmosphere models of HAT-P-41b, WASP-121b, and WASP-178b
to condensation curves of silicate and iron species. In equilibrium, silicates
and iron will condense between about 1500 and 2000 K between 1 mbar and 10 bar
for atmospheric metallicities between 1x and 10x solar. Throughout the
atmosphere, HAT-P-41b is much closer to the silicate condensation curve than
WASP-121b and WASP-178b and will almost certainly cross it on the nightside.
If WASP-121b and WASP-178b do reach temperatures cool enough to condense
silicates on the nightside, it also appears they are both able to avoid
rainout on either limb through rapid evaporation, vertical lofting,
insufficiently rapid nucleation and condensation, or some combination of these
and other hydrodynamic and microphysical processes 24, 25, 26. At depth, where
the temperatures in WASP-121b and WASP-178b are the closest to the
condensation curves, the higher internal temperature in hot and ultra-hot
Jupiters may also help such planets to avoid condensation 27.

As noted above, few NUV transit spectra exist for hot Jupiters. Future low-
and high-resolution observations, combined with multi-dimensional theoretical
modeling 24, 25, 26 and lab studies of aerosols 28, 29 in hot and ultra-hot
Jupiter, could provide more detailed constraints on the beginning of cloud
formation in these atmospheres, while taking into account the myriad processes
that promote or inhibit cloud formation, such as night-side cold-trapping,
rainout, and vertical mixing and other potentially confounding variables like
surface gravity and host star type. We estimate about two dozen planets Jovian
exoplanets can be characterized with HST/WFC3-UVIS/G280 with four or less
transits 30, 31. If combined with STIS/E230M observations to disentangle the
effects of atmospheric escape like we have done here, these planets can reveal
the conditions for and sequence of condensation in exoplanet atmospheres.
Observing, modeling, and retrieval of brown dwarfs at similar effective
temperatures will also shed light on these questions 32, 3.

Fig. 1: WASP-178b NUV-Optical Transmission Spectrum. a. WFC3/UVIS G280 transmission spectrum of WASP-178b (with 1-$\sigma$ uncertainties) compared to the contribution of various important opacity sources in the retrieved best fit spectrum. SiO dominates the contribution at short wavelengths. b. The 1-$\sigma$ constraint on the pressure-temperature profile (shaded region) with the median retrieved profile (solid line) on the same radius scale as the left plot, indicating the minimum pressures probed by our observations are less than a microbar.  Table 1: Retrieval Results Summary Scenario | $N_{\textrm{params}}$ | Max. ln($\mathcal{L}$) |  $\chi^{2}_{\nu}$ (K) |  $\Delta$BIC
---|---|---|---|---
Full | 14 | 353.41 | 1.44 | –
No Mg II | 13 | 352.13 | 1.47 | -1.447
No Fe II | 13 | 351.13 | 1.51 | 0.56
No SiO | 13 | 351.10 | 1.52 | 0.61
No SiO or Mg I | 12 | 345.21 | 1.75 | 8.39
No SiO or Fe II | 12 | 343.92 | 1.81 | 10.965
Full w/ Haze | 16 | 352.15 | 1.58 | -10.53
Fig. 2: Comparison of NUV-Optical Transmission Spectra. WFC3/UVIS G280
transmission spectrum of WASP-178b (with 1-$\sigma$ uncertainties) compared to
the UV and optical spectra of similar giant planets HAT-P-41b 22 and WASP-121b
33, 34, normalized by each planets equilibrium temperature scale height.
Significant UV absorption is seen at the shortest wavelengths in WASP-121b and
WASP-178b.  Fig. 3: Atmospheric structures and Condensation Curves. Pressure-
temperature profiles of three ultra-hot Jupiters from atmosphere models (see
Methods) compared to the condensation curve of Fe and Mg2SiO4 in a
1-10$\times$ solar metallicity atmosphere 23. Where the profile of the planets
intersects the condensation curve, as in the case of HAT-P-41b, is where
clouds are expected to form in equilibrium. We also show the retrieved median
and 1-$\sigma$ confidence interval for the 1D pressure-temperature profile of
WASP-178b for comparison, demonstrating agreement with self-consistent
atmosphere model expectation.

## Methods

HST/WFC3 observations One transit was observed of WASP-178b with the
HST/WFC3/UVIS instrument using the G280 grism (0.2-0.8 $\mu$m). The transit is
covered over five HST spacecraft orbits, with the transit approximately
centered in the third orbit. Exposure times of 40 seconds were used, along
with a 590$\times$2250 pixel detector sub-array which reduced the readout
overheads providing 123 total exposures, with 23 to 25 exposures per HST
orbit. The spectrograph is slitless, and we centered the subarray such that
both the +1 order and -1 order spectra were recorded and could both be fully
analysed. Utilizing both orders provides two independent transmission spectra
of the same transit event, though the +1 order provides higher signal-to-noise
(SNR) given a higher throughput (see Extended Data Fig. 4). Also see ref. 22
for more information on the instrument mode and analysis.

Data Reduction The raw data was processed with the STScI CALWF3 pipeline (v
3.5.1) which applies reduction steps including bias subtraction, dark
correction, and flat fielding. The target flux was subsequently extracted
starting from the pipeline FLT files. From each image we used the mode to
measure and subtract the background flux. We then removed cosmic rays
following a two step process. First, we identified and removed cosmic rays
utilizing the time series counts of each pixel. Outlier cosmic rays were
flagged and replaced with a 5-$\sigma$ clipping algorithm. We then removed
cosmic rays spatially, using a Laplacian edge detection algorithm on each
image separately 35. We then extracted the 1D spectral flux for each image on
both the -1 and +1 orders separately using IRAF APALL with an 8th order
Legendre polynomial fit to the spectral trace. A large range of aperture sizes
were extracted, between 10 and 28 pixels, with a 14 pixel aperture found to be
optimal in the subsequent light curve fitting stage. The wavelength solution
was determined from the spectral trace detector position following ref. 36.

UVIS Light Curve Analysis The general light curve fitting followed the
procedures detailed in Sing et al. (2019) 17 and previously used on WFC3/G280
observations in Wakeford et al. (2020)22, which we refer the reader to for
subsequent details. The flux measurements over time, $f(t)$, were modeled as a
combination of a theoretical transit model37, $T(t,\mathbf{\theta})$ (which
depends upon the transit parameters $\mathbf{\theta}$), the total baseline
flux of the star, $F_{0}$, and a instrument systematics model $S(\mathbf{x})$
giving,

$f(t)=T(t,\theta)\times F_{0}\times S(\mathbf{x}).$ (1)

As in ref. 17, we explored a wide range of models for $S(\mathbf{x})$,
exploring detrending variables including a fourth order polynomial in HST
orbital phase and linear terms in spectral position as measured from the
spectral extraction, wavelength shift measured from cross-correlation of each
spectra, and the spacecraft Jitter Detrending vectors which are products of
HST’s Engineering Data Processing System. For each both the +1 and -1 orders,
we used the Akaike information criterion (AICc) with a correction for small
sample sizes to determine the optimal detrending variable parameters to
include from the full set without overfitting the data and while minimizing
the rednoise. The light curve error bars were derived from the residual
scatter of the best fit. In addition, residual systematic noise, $\sigma_{r}$,
was measured along with the white noise, $\sigma_{w}$, using the binning
technique38, with the final fit parameter errors inflated by a factor $\beta$
if rednoise was present39 (see Extended Data Table 1). Overall, the effect of
rednoise was minimal as the noise was comparable to the binned photon noise at
typically several hundred ppm, and the errors in only 5 of 124 light curves
required an increased scaling by more than 10%.

To model the effects of limb-darkening and center-to-limb differences in the
star during transit, we calculated a custom PHOENIX stellar model using the
parameters of WASP-178A. For each wavelength bin of interest, we then used the
stellar intensity profile to fit for limb-darkening coefficients using the
non-linear 4-parameter limb-darkening as described in ref. 40 which were
subsequently used in the light curve transit fit. As a test of the stellar
models, we additionally fit for the limb-darkening assuming a linear law
between the wavelengths of 0.255 and 0.285$\mu$m. At these NUV wavelengths,
the stellar limb-darkening is strong, but also predicted by models to be
nearly linear in intensity across the limb, allowing for a direct comparison
largely free of complex degeneracies between transit-fit coefficients. We
found the transit data fit with a linear coefficient of $u=0.778\pm 0.028$,
which matches very well to the PHOENIX model prediction of $u=0.7758$. The
limb-darkening was subsequently fixed to the PHOENIX model values for all the
transit light-curve fits.

We first fit the white light curve, which integrates the entire spectra (see
Extended Data Fig. 5). The planet’s orbital system parameters including
inclination, $i$, semi-major axis in units of stellar radii, $a/R_{star}$, and
time of transit $T_{0}$ were fit along with the planet-to-star radius ratio,
$R_{pl}/R_{star}$, $F_{0}$, and systematics model using the +1 order. Given
the good phase coverage, these system parameters were generally more accurate
over previous literature values finding $i=84.41\pm 0.20$ degrees,
$a/R_{star}=6.588\pm 0.091$, and $T_{0}=2459097.869279\pm 0.00014$ days. We
kept the period fixed to the literature value of 3.3448285$\pm$0.0000012
days7.

To derive the planetary transmission spectrum, we fixed the system parameters
to the white-light curve best-fit values and used the optimal systematics
model $S(\mathbf{x})$ as determined by the white-light curve fit. While the
white-light curve did not require a term to model wavelength shifts in the
time-series spectra, this term was found to be needed in the spectral light
curve fits with 10 fit parameters overall for each light curve. The residual
fit scatter in the time-series spectral bins achieved a level that was on
average 1.2$\times$ theoretical photon-noise limit scatter and typically
ranged between 1.1$\times$ and 1.4$\times$ (see Extended Data Fig. 6). A
variety of spectral bin locations and resolutions were measured, with the
adopted spectra chosen to balance the resolution and SNR. In each case, the
overall shape of the transmission spectrum was consistent between different
resolutions. We measured the transmission spectrum of both the +1 and -1
orders, finding good agreement between both orders (see Extended Data Fig. 4).
We calculated the weighted-mean value of the spectra to report our final
derived spectrum (see Extended Data Table 1) as seen in Fig. 1.

We also independently verified the transmission spectrum using the
marginalization method described in 22. This method resulted in a spectrum
that was consistent with the spectrum analyzed with Jitter Detrending, both
showing large NUV absorption. This method used limb darkening coefficients
from the Kurucz stellar model grid 41, again suggesting our results are robust
against the details of limb darkening.

STIS E320M Light Curve Analysis To help resolve possible Fe II and Mg II
features in the NUV spectrum of WASP-178b, we also analysed a transit observed
on Jul 30, 2020 by HST with the STIS E230M instrument. As with the UVIS data,
these observations were also taken as part of program 16086. The STIS
observations were observed with the NUV-MAMA detector using the Echelle E230M
STIS grating and a square 0.2${}^{\prime\prime}\times 0.2^{\prime\prime}$
aperture. The E230M spectra has a resolving power of
R=$\lambda$/(2$\Delta\lambda$)=30,000 and we set the grating to 2707Å to cover
the wavelength ranges from 2280 to 3070 Å across 23 orders.

Our analysis closely follows Sing et al. (2019)17, which we refer for further
method details. We used the Jitter Detrending method to correct for time
variable slit losses seen in the white light curve photometry, and fit the
light curves using the system parameters given in Extended Data Table 2. We
find a band integrated white light curve $R_{p}/R_{s}$ of 0.1244$\pm$0.0050
which matches well (0.6-$\sigma$ significant difference) when compared to the
same wavelength region as measured by UVIS ($R_{p}/R_{s}$=0.12133$\pm$
0.00054). The main difference in our methods with ref 17 was the use of a
common-mode analysis when analysing the spectroscopic channels, where the
best-fit transit model was removed from the white light curve raw photometry,
and used to remove common instrument trends. In this case, large slit losses
repeating every spacecraft orbit are seen in the photometry. The common-mode
analysis removes the majority of the instrument trends seen, with the
remaining modeled with a second order polynomial in HST orbital phase. The
spectroscopic channels each reach a residual scatter that is consistent with
the photon noise level. As done for WASP-121b, we divided the E230M spectra
into 196 spectroscopic channels each with a 4Å bandpass. The resulting
spectrum can be seen in Extended Data Fig. 7. Compared to WASP-121b, WASP-178b
does not show strong Fe II or Mg II absorption features, with the high
resolution E230M spectrum consistent with the broadband NUV spectrum of UVIS.

Atmosphere Models Self-consistent 1-D PHOENIX atmosphere models of HAT-P-41b,
WASP-121b, and WASP-178b were computed to compare the expected atmospheric
temperatures in each planet to refractory species condensation curves. The
model setup was similar to past ultra-hot Jupiter studies with PHOENIX 42, 43,
12 that are computed on a 64-layer optical-depth grid from $\tau=$1e-10 to
1e2, which corresponds to similar magnitudes in pressure. We ran models for
two internal temperatures, 200 K and 700 K, which correspond to the lowest and
highest internal temperatures expected for a hot Jupiter 27. We further assume
full planet-wide heat redistribution to approximate temperatures at the
terminator, consistent with similar investigations 4. The temperature
structure from the self-consistent model of WASP-178b is quite similar to the
retrieved temperature profile from PETRA (see Fig. 3), indicating the full
heat redistribution assumption appears to be a good approximation of the
average conditions at the terminator.

The model includes opacity from 130 molecular species and neutral and ionized
atomic species up to uranium. TiO and VO are important visible-wavelength
opacity sources44, 45, but observations suggest they do not always appear to
be present in the atmosphere46. Consistent with retrievals of observations
from these planets 47, 33, the HAT-P-41b model did not include TiO or VO, the
WASP-121b model only included VO, and the WASP-178b model only included TiO
but at a reduced abundance (see Extended Data Table 2 and Extended Data Fig.
8). All other abundances, including SiO and Fe, were treated in local chemical
equilibrium. We further used the modelled HAT-P-41b transmission spectrum to
rule out the presence of gaseous refractories on one or both limbs, further
supporting the fact that these elements have rained out.

Atmosphere Retrievals We used PETRA 48 to retrieve atmospheric properties from
the observations. PETRA uses a Differential-Evolution Markov Chain statistical
framework 49 to sample the posterior distribution of the parameter space. Our
retrieval setup was similar to previous transmission retrievals with PETRA 50,
51. We parameterized the temperature structure using the 5-parameter approach
of Parmentier & Guillot (2014)52. We also included a necessary reference
radius parameter. The abundances of major UV and optical opacity sources were
treated as free parameters with uniform vertical abundance. These included Fe,
Fe II, Mg, Mg II, TiO, VO, and SiO. We also included a free parameter for the
metallicity ([Fe/H]) of the rest of the atmosphere, which was treated in
chemical equilibrium. This allowed the effect of other potential absorbers
expected to be of lesser importance (e.g., H-, Ca, Ni, FeH) to be taken into
account while reducing the number of free parameters to explore. Continuous
opacity from H- and scattering from hydrogen and helium were also included.

Uniform priors between volume mixing ratios of 10-12 and 10-1 were placed on
each of the opacity sources. Priors were also placed on the temperature
structure to avoid extremely low ($<500$ K) and extremely high ($>8,000$ K)
temperatures. We ran a total of 120,000 iterations among 30 chains reaching a
Gelman-Rubin $<$ 1.025. Extended Data Fig. 8 shows 2-D cross-sections of the
retrieved posterior distribution along with the 1-D marginalized distribution
for each of the retrieved parameters. A summary of the retrieved atmospheric
properties is included in Extended Data Table 2.

We also ran a series of retrievals without certain opacity sources in order to
compare different atmospheric species’ ability to fit the observed data. The
scenarios we tested are listed in Table 1. We computed the Bayesian
Information Criteria for each scenario, taking the retrieval with all opacity
sources included as our fiducial scenario (“Full”) to calculate a $\Delta$BIC
that quantifies whether there is statistical evidence to include a given
parameter, in this case an opacity source, in the retrieval. Generally, a
$\Delta$BIC between 2 and 6 indicates positive evidence for the inclusion of a
given parameter, while $\Delta$BIC above 6 indicates strong evidence. Our
retrieval analysis indicates there is strong evidence for the inclusion of SiO
or Mg I, and thus the gaseous precursor species to silicate condensates. We
also ran a retrieval that included a haze parameterization 53 to account for
photochemical or other high-temperature aerosols, but found that they did not
improve the fit.

In our fiducial scenario, the retrieval did find a highly super-solar
abundance of Mg II. This result is being driven by the single data point at
0.28 microns (see Fig. 1). A retrieval without Mg II provides an similarly
good fit to the data (see Table 1), demonstrating that the inclusion of Mg II
is not necessary to fit the data. We therefore do not choose to interpret the
retrieved Mg II abundance as unambiguously physical. This is supported by the
lack of any Mg II signal in the HST/STIS/E230M observations (see Extended Data
Fig. 7).

Stellar Activity Starspots or faculae cause stellar inhomogeneities which can
potentially contaminate transmission spectra 54, 55. While magnetic activity
(and thus starspots and facuale) are most relevant for low-mass stars, higher-
mass stars may also show some degree of activity 56 and some transmission
spectra of hot Jupiters around early-type host stars may be consistent with
unocculted stellar inhomogeneities 57. The problem is most acute at the
shortest wavelengths where the flux contrast between the nominal stellar
photosphere and the active region is the greatest.

We examined whether the transit spectrum of WASP-178b could be caused by
unocculted stellar activity. We found that because of the magnitude of the
spectral feature, extreme spot covering fractions and temperatures would be
required. To fit the magnitude of the NUV feature, a starspot 1,500 K cooler
than the nominal photosphere would require a spot covering fraction of 60%.
For a starspot 2,500 K cooler than the photosphere, a spot covering fraction
of 50% is required. Towards longer wavelengths, where the observed spectrum is
flatter, the contaminated model spectrum continue sloping to small transit
depths which is not seen in the data. In the end, these factors, combined with
the satisfactory fit to the stellar SED without activity and low activity
levels found in the star (see below and 7), suggest that stellar activity
cannot be responsible for the large feature in WASP-178b’s transit spectrum.

The 2019 TESS light curve of WASP-178 shows a consistent 0.115% variable
photometric signal with a 0.185 day period8, which is also easily visible in
2021 high cadence TESS photometry. This variability was speculated to be from
$\delta$ Scuti pulations in WASP-178 and possible gravity-darkening light
curve asymmetries were reported from the TESS data as well 8. However, our HST
transit light curves show no evidence of any variability at the 0.115% level,
with the raw UVIS photometry showing variations less than 0.02% over a 0.3 day
window. Upon further inspection of the TESS field of view and near-by faint
contaminant stars, from the ASAS-SN photometry database 58, 59, we determine
the origin of the photometric variations to be ASASSN-V J150908.07-424253.6
which is a nearby 14.5 magnitude W Ursae Majoris-type binary star with a
reported period of 0.369526 days, which is an alias of the reported 0.185 day
period. Both the period and magnitude of variations match that of the signal
seen as diluted in the TESS data by the brighter WASP-178b. As such, we
conclude there is no evidence for WASP-178 to have any photometric variations
larger than 0.02%. In addition, we find no evidence for reported transit
asymmetries due to possible gravity-darkening effects8 in the HST data either.
As a transit asymmetry signal in the TESS data could have also been influenced
by the binary star, we analysed the 2021 TESS photometry taken at a higher
cadence. When removing the binary star contaminating variables, the TESS light
curve shows no transit asymmetries in agreement with the HST data. Thus, there
is no evidence that either gravity darkening nor significant photometric
stellar activity are an issue with WASP-178.

Scattering An alternative mechanism for producing large short-wavelength
transit depths is through scattering. Small particles tend to scattering
short-wavelength light more effectively than longer-wavelength light, leading
to slopes towards greater transit depths at shorter wavelengths in
transmission spectra 60. If we describe the scattering cross-section as:

$\sigma=\sigma_{0}(\lambda/\lambda_{0})^{\alpha}$ (2)

the slope in the transmission spectrum can be expressed as:

$\frac{1}{H}\frac{\textrm{d}R_{p}}{\textrm{dln}(\lambda)}=\alpha$ (3)

Rayleigh scattering, the limit that the particle is smaller than the
wavelength of light, has a characteristic $\alpha=-4$. Given our observed
feature magnitude of approximately 20 scale heights over 0.2 $\mu$m, we
calculate $\alpha=-28.99$ is required to match the data. While super-Rayleigh
slopes in transmission spectrum are possible due to a vertical gradient in
opacity 61, a slope with $\alpha=-28.99$ would still be difficult to create,
especially with non-purely scattering particles like a photochemical haze.
Additionally, we do not expect aerosols to survive to the pressures or
temperatures that we probe with our observations ($\sim 1$ microbar, $\sim$
4000 K).

Limb Asymmetries Limb asymmetries can potentially complicate the
interpretation of a transmission spectrum. In particular, because of
atmospheric advection from the hotter day side to cooler night side, the
morning terminator can potentially be cooler with increased condensate
‘clouds’ while the hotter evening terminator can be cloud-free. This effect
may be evident in WASP-76b15, and theoretical models have investigated the
effect by coupling cloud formation to atmospheric dynamics62, 26, 24, 25. For
WASP-178b, if the limb asymmetries were prevalent, we would expect the NUV
transmission spectrum to be strongly affected, as features such as SiO could
be in gaseous form on one limb, but condensed into aerosols on the other. The
combined effect would be to potentially bias the interpretation toward the
hotter-clearer limb albeit with a reduced signal.

As our data covers some of both ingress and egress, where limb asymmetries
have large observable effects, we searched the UVIS data between 0.18 and 0.28
$\mu$m for terminator asymmetries using catwoman 63. In a scenario where Mg
and SiO are condensed on the leading morning terminator and has an effective
radius consistent with the optical ($R_{p}/R_{s}$=0.11133$\pm$0.0005), the
trailing evening terminator would require a radius of $R_{p}/R_{s}$=0.12924 in
order to match the transit radius ratio of $R_{p}/R_{s}$=0.12062$\pm$0.00067
measured in the NUV with the +1 order. The NUV +1 order light curve and
magnitude of limb asymmetries are shown in Extended Data Fig. 1. In
ingress/egress, such asymmetries are detectable in the data as they are found
to have a $\sim$500 ppm effect on the transit light curve, which is comparable
to the 1-$\sigma$ error bars (450 ppm). This simplified model is ruled out at
the 5-$\sigma$ level by the +1 order alone (see Extended Data Fig. 1). To
place further constraints, we used catwoman to fit the +1 and -1 order NUV
data (0.18 to 0.28 $\mu$m) for the two hemisphere planetary radii, $R_{p,1}$
and $R_{p,2}$, as well as terminator inclination angle $\phi$. We found $\phi$
to be unconstrained and $R_{p,1}$ and $R_{p,2}$ were consistent at 1-$\sigma$,
favoring a scenario without limb asymmetry. We also fixed $\phi$ to strictly
assume an east/west limb asymmetry. In this case, we also find both
hemispheres fit to nearly the same radii,
$R_{p,1}/R_{s}$=0.1195${}^{+0.0020}_{-0.0021}$ and
$R_{p,2}/R_{s}$=0.1211${}^{+0.0019}_{-0.0020}$, which are both larger than the
optical radius at $>$3-$\sigma$ confidence.

This indicates that the NUV transmission spectral features (SiO/Mg) occur on
both the leading and trailing limbs. With no indications either limb being
cloudy, potential silicate condensates are confined to the night-side of the
planet on WASP-178b. However, WFC3 phase-curve observations of the similar
planet WASP-121b 64 show the night-side temperatures do not generally drop low
enough to be conducive of silicate material condensation as significant heat
is transported.

We also note that the fact that both hemispheres are the same radius to within
1-$\sigma$ could point to implications for the atmospheric circulation and
heat transport at the low pressures probed in transit at NUV wavelengths. If
the atmospheric circulation was dominated by super-rotation at these
pressures, one would expect the morning terminator to be much colder, and thus
have a smaller radius at a given optical depth, than the evening terminator.
Because this does not seem to be the case, our observations might be an
indication that the circulation at microbar and less pressures is dominated by
a day-to-night flow, whereby the morning and evening terminators would be more
similar in temperature, and thus radius. This behavior is in line with
theoretical expectations 65.

Data Availability The raw data from this study is publicly available via the
Space Science Telescope Insitute’s Mikulski Archive for Space Telescopes
(https://archive.stsci.edu/).

Code Availability The raw data was reduced with the available STScI CALWF3
pipeline and spectra were extracted with the public IRAF APALL routines. The
light curve fitting used custom routines that we opt not to make public due to
undocumented intricacies. Model and retrievals were generated using PHOENIX,
which is a proprietary code but described in many publications e.g., 66, 67.

Acknowledgements We thank the reviewers for their helpful report which
improved the paper. We thank the UV-SCOPE team for relevant discussion. We
thank T. Barman for the use of a computing resources used in the calculation
of the atmospheric retrievals. Support for this work was provided by NASA
through grant number HST-GO-16086 from the Space Telescope Science Institute,
which is operated by AURA, Inc., under NASA contract NAS 5-26555. This
research has made use of the NASA Astrophysics Data System and the NASA
Exoplanet Archive, which is operated by the California Institute of
Technology, under contract with the National Aeronautics and Space
Administration under the Exoplanet Exploration Program.

Author Contributions J.D.L. and D.K.S. contributed equally to this work. J.D.L
led the observing proposal and retrieval analysis. D.K.S. led the data
analysis with contributions from Z.R., H.R.W., J.J.S., and A.T.W. All authors
discussed the data analysis and interpretation and commented on the
manuscript.

Competing Interests The authors declare no competing interests.

Extended Data Fig. 1: WASP-178b Transit Asymmetry Analysis. The 0.18-0.28
$\mu$m NUV light curve of WASP-178 b, with the best-fitting symmetric light
curve, and an asymmetric light curve representing a scenario with a
hotter/larger trailing terminator, and a colder/smaller leading terminator.
The radius of the leading terminator was set to the optical value, and the
trailing terminator was fixed to the value that fits the NUV transit depth.
The inset shows the RMS scatter of the residuals as a function of number of
points per bin, N.

Extended Data Fig. 2: WASP-178b NUV-Optical Transmission Spectrum (No SiO)
Same as Fig. 1, but for the retrieval without SiO. Note the combined ability
of Mg I and Fe II absorption to generate the large short-wavelength transit
depths.

Extended Data Fig. 3: Chemical Equilibrium of Si and Fe. Partial pressures of
important silicon-bearing species (left) and iron-bearing species (right) at 1
mbar as a function of temperature. Equilibrium chemical abundances were
calculated using GGchem 68.

Extended Data Fig. 4: WASP-178b Spectral Order Comparison. WFC3/UVIS G280
transmission spectrum of WASP-178b (with 1-$\sigma$ uncertainties) from the +1
(blue) and -1 order (red). The -1 order shows larger uncertainties due to a
reduced throughput, but the transmission spectra show good agreement including
an enhanced NUV absorption between 0.2 and 0.3 $\mu$m.

Extended Data Table 1: WASP-178 HST/WFC3/UVIS transmission spectrum and noise properties. |  |  Combined |  +1 order |  -1 order
---|---|---|---|---
$\lambda_{c}$ | $\Delta\lambda$ | $(R_{P}/R_{*})^{2}$ | $\sigma_{(R_{P}/R_{*})^{2}}$ | $\sigma_{w}$ | $\sigma_{r}$ | $\beta$ | $\sigma_{w}$ | $\sigma_{r}$ | $\beta$
($\mu$m) |  ($\mu$m) | (ppm) | (ppm) | (ppm) | (ppm) |  | (ppm) | (ppm) |
0.1963 | 0.0113 | 15587 | 490 | 1490 | 0. | 1.00 | 4344 | 0 | 1.00
0.2113 | 0.0037 | 14106 | 575 | 1809 | 287 | 1.06 | 4445 | 0 | 1.00
0.2188 | 0.0037 | 14775 | 538 | 1751 | 0. | 1.00 | 3355 | 0 | 1.00
0.2262 | 0.0037 | 14098 | 426 | 1376 | 0. | 1.00 | 2968 | 0 | 1.00
0.2338 | 0.0037 | 14962 | 405 | 1167 | 0. | 1.00 | 2937 | 0 | 1.00
0.2412 | 0.0037 | 14828 | 422 | 1333 | 0. | 1.00 | 2487 | 0 | 1.00
0.2488 | 0.0037 | 15155 | 417 | 1244 | 0. | 1.00 | 2697 | 0 | 1.00
0.2562 | 0.0037 | 14728 | 391 | 1202 | 0. | 1.00 | 2308 | 0 | 1.00
0.2637 | 0.0037 | 14714 | 430 | 1317 | 0. | 1.00 | 2692 | 0 | 1.00
0.2713 | 0.0037 | 14320 | 376 | 1116 | 0. | 1.00 | 2536 | 48 | 1.06
0.2788 | 0.0037 | 14768 | 469 | 1419 | 0. | 1.00 | 2555 | 0 | 1.00
0.2862 | 0.0037 | 13969 | 434 | 1314 | 0. | 1.00 | 2750 | 0 | 1.00
0.2937 | 0.0037 | 13703 | 394 | 1242 | 0. | 1.00 | 2275 | 0 | 1.00
0.3013 | 0.0037 | 13702 | 385 | 1215 | 0. | 1.00 | 2120 | 0 | 1.00
0.3088 | 0.0037 | 13360 | 381 | 1243 | 0. | 1.00 | 1943 | 0 | 1.00
0.3162 | 0.0037 | 12652 | 400 | 1263 | 0. | 1.00 | 2112 | 0 | 1.00
0.3237 | 0.0037 | 12646 | 408 | 1323 | 0. | 1.00 | 2089 | 0 | 1.00
0.3313 | 0.0037 | 12647 | 377 | 1169 | 0. | 1.00 | 2042 | 0 | 1.00
0.3388 | 0.0037 | 12396 | 425 | 1447 | 0. | 1.00 | 1944 | 0 | 1.00
0.3462 | 0.0037 | 13322 | 418 | 1308 | 0. | 1.00 | 2108 | 0 | 1.00
0.3537 | 0.0037 | 12112 | 416 | 1373 | 0. | 1.00 | 2247 | 0 | 1.00
0.3613 | 0.0037 | 12064 | 428 | 1361 | 0. | 1.00 | 2336 | 0 | 1.00
0.3700 | 0.0050 | 11918 | 379 | 1239 | 0. | 1.00 | 1991 | 0 | 1.00
0.3800 | 0.0050 | 12490 | 307 | 1155 | 0. | 1.00 | 1432 | 0 | 1.00
0.3900 | 0.0050 | 11817 | 291 | 985 | 0. | 1.00 | 1562 | 0 | 1.00
0.4000 | 0.0050 | 12047 | 299 | 930 | 0. | 1.00 | 2841 | 1142 | 1.31
0.4100 | 0.0050 | 12597 | 229 | 725 | 0. | 1.00 | 1255 | 0 | 1.00
0.4200 | 0.0050 | 12540 | 230 | 762 | 147 | 1.09 | 1103 | 0 | 1.00
0.4300 | 0.0050 | 12363 | 217 | 836 | 274 | 1.22 | 1163 | 0 | 1.00
0.4400 | 0.0050 | 12073 | 261 | 822 | 0. | 1.00 | 1268 | 0 | 1.00
0.4500 | 0.0050 | 11741 | 242 | 889 | 0. | 1.00 | 1110 | 0 | 1.00
0.4600 | 0.0050 | 12500 | 270 | 786 | 264 | 1.23 | 1115 | 0 | 1.00
0.4700 | 0.0050 | 12616 | 283 | 972 | 0. | 1.00 | 1309 | 220 | 1.07
0.4800 | 0.0050 | 12335 | 277 | 1076 | 172 | 1.06 | 1350 | 0 | 1.00
0.4900 | 0.0050 | 12361 | 338 | 1094 | 234 | 1.10 | 1833 | 0 | 1.00
0.5000 | 0.0050 | 12683 | 299 | 1010 | 0. | 1.00 | 1380 | 0 | 1.00
0.5100 | 0.0050 | 12645 | 292 | 956 | 0. | 1.00 | 1373 | 0 | 1.00
0.5200 | 0.0050 | 12620 | 329 | 1159 | 0. | 1.00 | 1382 | 0 | 1.00
0.5300 | 0.0050 | 12022 | 355 | 1219 | 0. | 1.00 | 1580 | 0 | 1.00
0.5400 | 0.0050 | 12322 | 371 | 1166 | 297 | 1.14 | 1472 | 291 | 1.09
0.5500 | 0.0050 | 11795 | 332 | 1187 | 0. | 1.00 | 1418 | 0 | 1.00
0.5600 | 0.0050 | 11316 | 316 | 1079 | 49. | 1.01 | 1464 | 0 | 1.00
0.5725 | 0.0075 | 11747 | 297 | 996 | 0. | 1.00 | 1440 | 0 | 1.00
0.5875 | 0.0075 | 11615 | 291 | 1020 | 132 | 1.04 | 1262 | 0 | 1.00
0.6025 | 0.0075 | 12680 | 363 | 1378 | 0. | 1.00 | 1471 | 0 | 1.00
0.6175 | 0.0075 | 12253 | 363 | 1221 | 165 | 1.04 | 1552 | 0 | 1.00
0.6325 | 0.0075 | 12527 | 364 | 1306 | 0. | 1.00 | 1512 | 0 | 1.00
0.6475 | 0.0075 | 11772 | 451 | 1575 | 0. | 1.00 | 1941 | 63 | 1.00
0.6625 | 0.0075 | 11818 | 407 | 1383 | 0. | 1.00 | 1778 | 0 | 1.00
0.6825 | 0.0125 | 12021 | 343 | 1136 | 0. | 1.00 | 1439 | 0 | 1.00
0.7075 | 0.0125 | 12566 | 423 | 1425 | 0. | 1.00 | 1739 | 0 | 1.00
0.7325 | 0.0125 | 11859 | 462 | 1735 | 336 | 1.09 | 1724 | 0 | 1.00
0.7575 | 0.0125 | 12333 | 553 | 1927 | 0. | 1.00 | 2299 | 260 | 1.03

Extended Data Fig. 5: White light curves of the WASP-178b HST/WFC3-UVIS/G280
transit. Error bars show the 1-$\sigma$ uncertainties. The left column shows
the +1 spectral order, while the right column shows the -1 spectral order. The
top row are the raw light curves the middle row are the light curves with
systematics removed and a transit fit, and the bottom row are the residuals
with the standard deviation of the residuals also shown (dotted lines). Plots
of the binned residual RMS are also shown.

Extended Data Fig. 6: WASP-178b NUV-Optical Light Curve Comparison. Two
example fitted light curves from the +1 spectral order order from
spectroscopic bins covering 0.2412 and 0.5875, with transit depths of 1.48
$\pm 0.04$% and 1.16 $\pm 0.03$%, respectively. The rows are the same as in
Extended Data Fig. 5.

Extended Data Fig. 7: High-resolution HST/STIS/E230M Transmission Spectrum of
WASP-178b. NUV high resolution transit spectra of WASP-178b (with 1-$\sigma$
uncertainties) compared to WASP-121b around the Fe II (left) and Mg II lines.
Shown are the spectra from STIS E230M for WASP-178b (red), WASP-121b17 (grey),
and the low resolution UVIS spectra (blue). While WASP-121b shows strong Fe II
and Mg II absorption features, the WASP-178b E230M spectra is consistent with
the broadband NUV continuum with no Fe II or Mg II.

Extended Data Table 2: WASP-178b Fitted and Retrieved Orbital and Atmosphere
Parameters
*Equilibrium mixing ratios are shown in brackets and are calculated at WASP-178b’s equilibrium temperature (2,450 K) and 0.1 mbar pressure. Orbital Parameters
---
Inclination ($i$) | $84.41\pm 0.20^{\circ}$
$a/R_{s}$ | $6.588\pm 0.091$
Transit Center ($T_{0}$) |  $2459097.869279\pm 0.00014$ days
Period 7 | 3.3448285$\pm$0.0000012 days
Planet Radius ($R_{p}/R_{s}$) | $0.11295150\pm 0.00041$
Retrieved and Equilibrium Atmospheric Log Mixing Ratios
SiO |  $-4.68\pm^{0.65}_{0.59}$ [-4.46]
Fe |  $-9.51\pm^{1.64}_{1.49}$ [-4.47]
Fe II |  $-3.76\pm^{1.35}_{4.15}$ [-9.44]
Mg |  $-7.44\pm^{2.67}_{2.73}$ [-4.37]
Mg II |  $-2.22\pm^{0.33}_{0.52}$ [-8.67]
TiO |  $-10.01\pm^{0.59}_{0.72}$ [-7.07]
VO |  $-10.76\pm^{1.01}_{0.79}$ [-8.56]
[Fe/H] |  $-1.39\pm^{0.50}_{0.37}$ [0.00]

Extended Data Fig. 8: WASP-178b Atmospheric Retrieval Posterior Distribution.
2-D cross-sections of the retrieved posterior distribution with 1-D
marginalized distribution for the fitted parameters. The quoted quantities are
the mean and 1-$\sigma$ retrieved values. The first five parameters are the
temperature structure parameterization from Parmentier & Guillot 2014 52, the
sixth is the reference radius, and the final eight are the various atomic and
molecular abundances.

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