# ExoGemS High-Resolution Transmission Spectroscopy of WASP-76b with GRACES

Emily K. Deibert Gemini Observatory, NSF’s NOIRLab, Casilla 603, La Serena,
Chile  Ernst J. W. de Mooij Astrophysics Research Centre, Queen’s University
Belfast, Belfast BT7 1NN, UK  Ray Jayawardhana Department of Astronomy,
Cornell University, Ithaca, New York 14853, USA  Jake D. Turner Department of
Astronomy, Cornell University, Ithaca, New York 14853, USA  NHFP Sagan Fellow
Andrew Ridden-Harper Las Cumbres Observatory, 6740 Cortona Drive, Suite 102,
Goleta, CA 93117, USA  Callie E. Hood Department of Astronomy & Astrophysics,
University of California, Santa Cruz, CA 95064, USA  Jonathan J. Fortney
Department of Astronomy & Astrophysics, University of California, Santa Cruz,
CA 95064, USA  Laura Flagg Department of Astronomy, Cornell University,
Ithaca, New York 14853, USA  Luca Fossati Space Research Institute, Austrian
Academy of Sciences, Schmiedlstrasse 6, A-8042 Graz, Austria  Romain Allart
Department of Physics, and Institute for Research on Exoplanets, Université de
Montréal, Montréal, H3T 1J4, Canada  Matteo Brogi Dipartimento di Fisica,
Università degli Studi di Torino, via Pietro Giuria 1, I-10125, Torino, Italy
INAF-Osservatorio Astrofisico di Torino, Via Osservatorio 20, I-10025 Pino
Torinese, Italy  Ryan J. MacDonald Department of Astronomy, University of
Michigan, 1085 S. University Ave., Ann Arbor, MI 48109, USA  NHFP Sagan Fellow

###### Abstract

We present high-resolution transmission spectroscopy of WASP-76b with
GRACES/Gemini North obtained as part of the ExoGemS survey. With a broad
spectral range of 400–1050 nm and a relatively high resolution of
$\sim$66,000, these observations are particularly well-suited to searching for
atomic and molecular atmospheric species via the Doppler cross-correlation
technique. We recover absorption features due to neutral iron (Fe I), sodium
(Na I), and ionized calcium (Ca II) at high significance ($>$$5\sigma$), and
investigate possible atmospheric temperatures and wind speeds. We also report
tentative ($>$$3\sigma$) detections of Li I, K I, Cr I, and V I in the
atmosphere of WASP-76b. Finally, we report non-detections of a number of other
species, some of which have previously been detected with other instruments.
Through model injection/recovery tests, we demonstrate that many of these
species are not expected to be detected in our observations. These results
allow us to place GRACES and the ExoGemS survey in context with other high-
resolution optical spectrographs.

††facilities: Gemini:Gillett (GRACES), CFHT (ESPaDOnS)††software:  astropy
(Price-Whelan et al., 2018), barycorr (Wright & Eastman, 2014) batman
(Kreidberg, 2015), IPython (Perez & Granger, 2007), Matplotlib (Hunter, 2007),
Numpy (Harris et al., 2020), OPERA (Martioli et al., 2012), SciPy (Virtanen et
al., 2020)

##  1 Introduction

In the two decades since the first detection of an exoplanet’s atmosphere
(Charbonneau et al., 2002), the field of atmospheric characterization has
flourished. Exoplanet atmospheres are now regularly observed from both the
ground and space, and dozens of exoplanets have had their atmospheres detected
and characterized to date. In recent years, high-resolution spectroscopy from
ground-based instruments has been recognized as a particularly promising probe
of exoplanet atmospheres at both optical and near-infrared wavelengths. High-
resolution spectra allow us to resolve features from both atomic and molecular
species, and the broad wavelength coverages of modern Échelle spectrographs
allow us to detect many hundreds or even thousands of these features, boosting
the strength of our detections (see e.g., Birkby, 2018) and allowing us to
place robust constraints on the chemical compositions of a range of alien
worlds.

With a relatively high resolving power (R $\sim$ 66,000) and broad wavelength
coverage across the full optical range, the Gemini Remote Access to CFHT
ESPaDOnS Spectrograph (GRACES; Chene et al., 2014) at the Gemini North
telescope is a robust tool for characterizing exoplanet atmospheres. The
ongoing Gemini Large and Long Program GN-2020B-LP106: “Exploring the Diversity
of Exoplanet Atmospheres at High Spectral Resolution” (Exoplanets with Gemini
Spectroscopy or ExoGemS for short; PI: Jake Turner) aims to take advantage of
these capabilities in order to carry out a systematic, high-resolution,
comparative survey of transiting exoplanet atmospheres ranging from sub-
Neptunes to ultra-hot Jupiters. The survey is expected to target a few dozen
transiting exoplanets, many of which have not previously been observed at high
spectral resolution. The goal of the survey is to compare the atmospheric
properties and compositions of exoplanets across masses, temperatures, and
stellar irradiation levels in order to determine the role that these
properties play in regulating exoplanet atmospheres.

Owing to its high equilibrium temperature, short orbital period ($\sim$1.8
days; Ehrenreich et al. 2020), and relatively bright host star (V = 9.52; Høg
et al. 2000), WASP-76b (West et al., 2016) is an ideal benchmark target for
the ExoGemS survey. We observed WASP-76b in the first semester of the survey
(Gemini semester 2020B; see Section 2 and Table 2) for the purposes of
comparing the detection capabilities of GRACES with other high-resolution
spectrographs (many of which have been used to observe WASP-76b) while
simultaneously furthering our understanding of giant planet atmospheres by
searching for atomic and molecular absorption features across the full optical
range.

Since its discovery in 2016 (West et al., 2016), WASP-76b has quickly become
among the most well-studied ultra-hot Jupiters (i.e., hot Jupiters with
equilibrium temperatures upwards of $\sim$2000 K; Parmentier et al. 2018; Bell
& Cowan 2018; Arcangeli et al. 2018). At these extreme temperatures, molecules
are expected to dissociate and many atoms are expected to ionize, resulting in
optical spectra rich in neutral and ionized atomic features that are amenable
to detection via high-resolution spectroscopy (e.g., Hoeijmakers et al., 2019;
Bello-Arufe et al., 2022).

Indeed, a wide variety of atomic features have been detected in the optical
spectrum of WASP-76b. High-resolution detections of Na I in its atmosphere
were first reported by Seidel et al. (2019) and Žák et al. (2019) using
HARPS/ESO 3.6m spectra. More recently, Ehrenreich et al. (2020) reported a
detection of asymmetric Fe I absorption using observations from ESPRESSO/VLT,
which was verified by Kesseli & Snellen (2021) with HARPS and later
investigated via modelling by Wardenier et al. (2021) and Savel et al. (2022).
Many other atomic species have also been reported in its atmosphere by
Tabernero et al. (2021), Kesseli et al. (2022), and Azevedo Silva et al.
(2022) using the same ESPRESSO spectra analyzed in Ehrenreich et al. (2020).
Seidel et al. (2021) also used these spectra to provide updated measurements
of Na I absorption. Ca II absorption in the form of the near-infrared triplet
was also recently reported by Casasayas-Barris et al. (2021) with
CARMENES/Calar Alto and Deibert et al. (2021b), the latter of which used the
same GRACES spectra which are the focus of the present work. A summary of
previous detections as of the writing of this paper is presented in Table 1.
We note that a number of studies have also characterized WASP-76b’s atmosphere
in the near-infrared; however, we focus the present work on optical
observations in order to place previous work into context with the ExoGemS
survey.

Table 1: Summary of species detected in WASP-76b’s atmosphere at high spectral resolution in the optical. Note that a “detection” or “tentative detection” may be defined differently in different works. Reference | Instrument/Telescope | Detected Species | Tentative | Upper Limits
---|---|---|---|---
Žák et al. (2019) | HARPS/ESO 3.6m | Na I |  |
Seidel et al. (2019) | HARPS/ESO 3.6m | Na I |  |
Ehrenreich et al. (2020) | ESPRESSO/VLT | Fe I |  |
Tabernero et al. (2021) | ESPRESSO/VLT | Li I, Na I, Mg I, Ca II, | H$\alpha$aaThe authors detect H$\alpha$ at a significance of 4$\sigma$ in one transit, but are unable to recover the signal in the second transit. | Ti I, Cr I, Ni I,
|  | Mn I, K I, Fe I |  | TiO, VO, ZrO
Seidel et al. (2021) | ESPRESSO/VLT; | Na I |  |
| HARPS/ESO 3.6m |  |  |
Kesseli & Snellen (2021) | HARPS/ESO 3.6m | Fe I |  |
Casasayas-Barris et al. (2021) | CARMENES/Calar Alto | Ca II |  | Li I, K I, H$\alpha$, Na I
Deibert et al. (2021b) | GRACES/Gemini North | Na I, Ca II | Li I, K I | H$\alpha$
Kesseli et al. (2022) | ESPRESSO/VLT | Li I, Na I, Mg I, Ca II, | H$\alpha$, K I, Co I | Ti I, Ti II, Ca I, Al I,
|  | V I, Cr I, Mn I, Fe I, |  | Sc I, Sc II, Zr IbbThe authors present 4$\sigma$ upper limits for a number of additional species which were not expected to be detectable in their analysis. For the sake of brevity, we have only displayed the 4$\sigma$ upper limits for species which the authors expected to be detectable.
|  | Ni I, Sr II |  |
Azevedo Silva et al. (2022) | ESPRESSO/VLT | Ba II, Li I, Na I, Mg I, |  |
|  | Ca II, V I, Cr I, Mn I, |  |
|  | Fe I, H$\alpha$ |  |

In Deibert et al. (2021b), we demonstrated the efficacy of GRACES in
characterizing exoplanet atmospheres via single-line transmission
spectroscopy, allowing us to detect and resolve individual absorption lines in
WASP-76b’s atmosphere. We showed that GRACES is sensitive to detections of Na
I and the Ca II infrared triplet, the latter of which may be an important
probe of non-local thermodynamic equilibrium (NLTE) effects in exoplanet
atmospheres (e.g., Turner et al., 2020; Fossati et al., 2020, 2021; Deibert et
al., 2021b). We also showed that GRACES is marginally sensitive to a number of
other species using these methods, including Li I, H$\alpha$, and K I.

As in Deibert et al. (2021b), the goal of the present work is to search for
species present in WASP-76b’s atmosphere, allowing us to place GRACES into
context among other high-resolution optical spectrographs and assess our
detection capabilities for the remainder of the ExoGemS survey. Yet while
Deibert et al. (2021b) focused on single-line detections of strong absorbers
such as Na I and Ca II via the creation of transmission spectra, in this work
we turn our focus to detections of additional species via the Doppler cross-
correlation technique (e.g., Snellen et al., 2010), which combines the signals
from weaker absorption lines which cannot be resolved individually. This
technique is well-suited to detecting species with hundreds or even thousands
of spectral features across a broad wavelength range. We thus focus our search
on atoms and molecules with a large number of optical spectral features that
can be resolved with GRACES.

This paper will proceed as follows. In Section 2, we describe the observations
obtained as part of the ExoGemS survey with GRACES/Gemini North. We detail our
data reduction methods in Section 3, and in Section 4 we describe the methods
we use to analyze the data, as well as the atmospheric models and templates
used in this work. Our results are presented and discussed in Section 5, and
we conclude in Section 6.

##  2 Observations

We observed one transit of WASP-76b with GRACES (Chene et al., 2014) at the
Gemini North telescope. The observations were obtained as part of the ExoGemS
survey, which is a Gemini Large and Long Program to observe dozens of
transiting exoplanets with high-resolution spectroscopy through the 2023A
observing semester (GN-2020B-LP-106; PI: Jake Turner). A subset of these data
was previously analyzed in Deibert et al. (2021b), where we derived
transmission spectra around individual lines to search for atmospheric
absorption, and reported detections of Ca II and Na I (among other tentative
detections). In the present work, we analyze the full data set spanning
GRACES’ complete wavelength range of 400 to 1050 nm using the Doppler cross-
correlation technique (e.g., Snellen et al., 2010). The nominal resolving
power of GRACES is $\sim$66,000.

A summary of the observations is presented in Table 2. A total of 169 spectra
were obtained over the course of the transit (as well as a baseline of
observations pre- and post-transit), with approximately 10% of the transit
(lasting 22 minutes) lost when a computer at the observatory crashed and
needed to be rebooted. This technical issue did not affect the data preceding
or following the gap in the observations. In total, the observations lasted
$\sim$5.16 hours. The average signal-to-noise ratio (SNR) ranged from $\sim$22
to $\sim$111 per spectral bin in the orders used in our analysis. The airmass
varied between 1.046 and 1.627, and the seeing throughout the observations was
excellent, with a measured full-width at half-maximum (FWHM) of 0.55
arcseconds. We refer the reader to Deibert et al. (2021b) for additional
figures describing the data quality (their Fig. 3).

Table 2: Summary of GRACES/Gemini North observations of WASP-76b used in this analysis. Date (UT) | Frames (In/Out) | Exposure Time (s) | Avg. SNR (Max.)aaAverage SNR per spectral bin in the 28th order (centered at $\sim$ 807 nm), which had the highest SNR across the full spectrum. | Avg. SNR (Min.)bbAverage SNR per spectral bin in the 50th order (centered at $\sim$ 452 nm), which had the lowest SNR of the orders used in this analysis.
---|---|---|---|---
11 October 2020 | 169 (120/49) | 60 | 111.4 | 22.5

##  3 Data Reduction

The initial steps of our data reduction routine proceeded as follows. We
extracted the spectra from the raw files using OPERA, the Open source Pipeline
for ESPaDOnS Reduction and Analysis (Martioli et al., 2012), which performs an
optimal extraction, bias subtraction, flat-fielding, blaze correction,
continuum normalization, and wavelength calibration. Next, we removed cosmic
rays and other outliers using a median absolute deviation flag which masks
points greater than 5 median absolute deviations. We then flux-scaled each
spectrum (e.g., Allart et al., 2017) by dividing out the first spectrum of
each night and fitting/dividing out a fourth-order polynomial fit. We note
that this is the same process described in Deibert et al. (2021b), albeit
across the full GRACES wavelength range in this work; and as in Deibert et al.
(2021b), the order of the polynomial fit does not significantly affect our
results.

###  3.1 Removal of Telluric and Stellar Features with SysRem

Following the initial data reduction steps described in Section 3, we
corrected for stellar and telluric absorption features using the SysRem
algorithm (Tamuz et al., 2005), which is a PCA-like algorithm that removes
time-stationary features in a set of spectra. Because the radial velocity of
the exoplanet varies significantly throughout the course of its transit (from
approximately -52 km/s to +52 km/s in the case of WASP-76b), absorption
features from the exoplanet’s atmosphere remain intact while essentially time-
stationary features from the Earth and the host star are removed by the SysRem
algorithm.

Before running SysRem, we interpolated the spectra to a common wavelength grid
in the telluric rest frame. We then used the airmass throughout the
observations as an initial guess for the first component to be removed by the
algorithm. To determine the optimum number of iterations of SysRem to apply to
our observations, we ran between 1 and 20 iterations of the algorithm on each
order of our spectra. We then repeated our cross-correlation analysis (see
Section 4.2) with a high-resolution 1D transmission spectrum generated to
match WASP-76b’s atmosphere (see Section 4.1) for each number of iterations,
and chose the number which maximized the significance of our detection of all
species included in the high-resolution transmission spectrum simultaneously
(see Fig. 2).

We found that 7 iterations resulted in the strongest detection, but beyond 2
iterations, the detections were within 1$\sigma$ of each other regardless of
the number of iterations. We therefore chose to apply 7 iterations of SysRem
to each order of our data. We note that this is one more iteration than used
in Deibert et al. (2021b), where we optimized for the Ca II detection in
particular. In the present work, we optimized the algorithm based on a
synthetic transmission spectrum which contained absorption features from a
number of atoms/molecules across the full GRACES wavelength range. This
allowed us to apply the algorithm consistently across every order of the data.

The results of applying 7 iterations of the SysRem algorithm to each order are
presented in Appendix A.

##  4 Methods

We followed a similar methodology to previous analyses using the Doppler
cross-correlation technique (e.g., Snellen et al., 2010; Deibert et al.,
2021a). This first involves creating atmospheric models and templates with
which to cross-correlate our spectra, and then carrying out the Doppler cross-
correlation process on each of these templates.

###  4.1 Atmospheric Models and Templates

To search for atomic and molecular features in WASP-76b’s optical spectrum, we
turned to a range of modelling efforts. These are described in further detail
below. In particular, we opted for both a custom high-resolution, one-
dimensional transmission spectrum created for WASP-76b’s atmosphere, as well
as a publicly available set of atmospheric templates generated for a generic
ultra-hot Jupiter atmosphere.

In all cases, we prepared the models for cross-correlation with our data by
first converting the wavelength grids to air wavelengths, interpolating the
wavelength grids to that of GRACES, and convolving the models to the
resolution of GRACES using a Gaussian Kernel. We also applied a Butterworth
filter to each template in order to mimic the effects of the SysRem algorithm
(e.g., Herman et al., 2022).

####  4.1.1 High-Resolution 1D Transmission Spectrum

We first created a one-dimensional transmission spectrum for WASP-76b’s
atmosphere based on the parameters described in Table 3. We generated the
atmospheric pressure-temperature (_P–T_) profile via the one-dimensional
modelling methods described in Fortney et al. (2008) and Fortney et al.
(2020). Planet-wide average conditions were assumed, as well as equilibrium
chemistry at solar metallicity, and the model was iterated to a solution in
radiative-convective equilibrium. The _P–T_ profile is shown in Fig. 1. We
then used the one-dimensional transmission spectrum code described in the
appendix of Morley et al. (2017) to generate a transmission spectrum at high
resolution, based on the calculated _P–T_ profile and equilibrium chemical
abundances, generally following Hood et al. (2020). We performed these
calculations across the wavelength range of GRACES, and included H2, He, H,
H2O, Fe I, Na I, K I, Li I, Mn I, and Ca II. The resulting spectrum in shown
in Fig. 2. We chose these species in particular as they were expected to be
abundant and readily detectable in the atmosphere (e.g., Kesseli et al., 2022)
had been detected at high significances by multiple previous works (e.g.,
Tabernero et al., 2021; Deibert et al., 2021b; Kesseli et al., 2022; Sánchez-
López et al., 2022; Azevedo Silva et al., 2022). Due to memory limitations, we
could not include additional species in this model; instead, a wider grid of
species was explored using the Mantis Network templates (Kitzmann et al.,
2023, see below).

In order to further compare the results we obtained with our custom model with
the generic templates described in the following section, we also generated a
one-dimensional transmission spectrum including only Ca II, H2, and He. This
model is displayed in the left subplot of Fig. 4.

Figure 1: The _P–T_ profile generated for WASP-76b, as described in Section 4.1.1. Table 3: Orbital and physical parameters of the WASP-76 system used in this analysis. Parameter | Symbol (Unit) | Value | Reference
---|---|---|---
Stellar radius |  $R_{*}$ ($R_{\sun}$) | $1.756\pm 0.071$ | E20aaEhrenreich et al. (2020)
Stellar mass |  $M_{*}$ ($M_{\sun}$) | $1.458\pm 0.02$ | E20 footnotemark:
Magnitude |  $V$ (mag) | $9.52\pm 0.03$ | Høg et al. (2000)
System scale | $a/R_{*}$ | $4.08{}^{+0.02}_{-0.06}$ | E20 footnotemark:
Orbital period |  $P$ (days) | $1.80988198{}^{+0.00000064}_{-0.00000056}$ | E20 footnotemark:
Transit duration |  $T_{14}$ (min.) | $230$ | E20 footnotemark:
Epoch of mid-transit |  $T_{c}$ (BJD) | $2458080.626165{}^{+0.000418}_{-0.000367}$ | E20 footnotemark:
Radius ratio | $R_{\mathrm{p}}/R_{*}$ | $0.10852{}^{+0.00096}_{-0.00072}$ | E20 footnotemark:
Planetary radius |  $R_{\mathrm{p}}$ ($R_{\mathrm{J}}$) | $1.854{}^{+0.077}_{-0.076}$ | Tabernero et al. (2021)
Planetary mass |  $M_{\mathrm{p}}$ ($M_{\mathrm{J}}$) | $0.894{}^{+0.014}_{-0.013}$ | E20 footnotemark:
Inclination |  $i$ (degrees) | $89.623{}^{+0.005}_{-0.034}$ | E20 footnotemark:
Systemic velocity |  $\gamma_{\mathrm{sys}}$ (km/s) | $-1.0733\pm 0.0002$ | West et al. (2016)
Stellar radial velocity semi-amplitude | K∗ (m/s) | $116.02{}^{+1.29}_{-1.35}$ | E20 footnotemark:
Planetary radial velocity semi-amplitude | Kp (km/s) | $196.52\pm 0.94$ | E20 footnotemark:
Quadratic limb darkening coefficient | $u_{1}$ | $0.393$ | E20 footnotemark:
Quadratic limb darkening coefficient | $u_{2}$ | $0.219$ | E20 footnotemark:
Projected equatorial rotational velocity |  $v\sin i$ (km/s) | 1.48 $\pm$ 0.28 | E20 footnotemark:
Figure 2: A high-resolution, one-dimensional synthetic transmission spectrum
generated for WASP-76b’s atmosphere using the methods described in Section
4.1.1. A number of spectral features can be seen, including a band of strong
Fe I features at the blue end of the spectrum, strong absorption features due
to Na I at $\sim$589 nm, and many absorption lines due to H2O at the red end
of the spectrum.

####  4.1.2 Mantis Network Templates

In addition to the model described above, we also searched for atmospheric
absorption using a standard grid of templates from the Mantis Network
(Kitzmann et al., 2023). As described in Kitzmann et al. (2023), the grid
includes high-resolution templates for more than 140 atmospheric species
across a range of atmospheric temperatures. While the public database
currently only includes templates generated for ultra-hot (i.e., $>$ 2000 K)
atmospheres observed in transmission, the full database will eventually
include templates for lower temperatures as well (Kitzmann et al., 2023). The
goal of the Mantis Network database is to offer a standardized set of
atmospheric templates which can be used with a range of different
spectrographs in order to make analyses using different instruments more
consistent. We therefore chose to use these templates as a way to better
compare our work to recent analyses of WASP-76b using data from ESPRESSO.

The atmospheric templates from the Mantis Network were recently used by
Azevedo Silva et al. (2022) to analyze transmission spectra of WASP-76b from
ESPRESSO, resulting in a new detection of Ba II, among other previously
detected species (Azevedo Silva et al., 2022). Azevedo Silva et al. (2022)
also used these same templates to detect a number of species in the atmosphere
of WASP-121b, while Borsato et al. (2023) used the Mantis templates with
archival observations of KELT-9b from HARPS-N and CARMENES. With the present
work, our aim is to both compare our analysis with that of Azevedo Silva et
al. (2022) while also demonstrating the efficacy of the Mantis templates in
detecting atmospheric species with GRACES spectra.

We refer the reader to Kitzmann et al. (2023) for a full description of the
template generation. Briefly, the templates are created assuming a generic
ultra-hot Jupiter with a surface gravity of $g=2000$ cm s-1, a planetary
radius of $R_{p}=1.5$ $R_{J}$ at a pressure of 10 bar, and an isothermal
pressure-temperature profile throughout the atmosphere at temperatures of 2000
K, 2500 K, 3000 K, 4000 K or 5000 K. As described in Kitzmann et al. (2023),
the fact that the cross-correlation template is normalized means that it is
largely insensitive to the choices of $g$ and $R_{p}$, assuming that the
atmospheric scale height $H$ is much smaller than $R_{p}$. Furthermore,
Kitzmann et al. (2023) demonstrated that varying the surface gravity $g$ does
not affect the final detection SNR at greater than the 0.5%-level.

The templates used in this work included continuum-forming species and a
single line-forming species. The continuum opacity sources considered in the
calculation of these templates included collision-induced absorption (CIA) of
H2-H2, H2-He, and H-He collisions; free-free and bound-free absorption of H-
and H${}^{-}_{2}$; and Rayleigh scattering cross-sections for H2, H, and He
(Kitzmann et al., 2023). The templates were calculated assuming equilibrium
chemistry and solar elemental abundances.

For the present work, we downloaded the templates generated for 2000 K, 2500
K, 3000 K, and 4000 K atmospheres. While the 2000 K atmosphere is closest to
WASP-76b’s expected equilibrium temperature of $\sim$2200 K (West et al.,
2016), Deibert et al. (2021b) demonstrated that the atmospheric layers probed
by these GRACES observations may well be much hotter than the equilibrium
temperature. Furthermore, a number of recent studies of WASP-76b have found
temperatures ranging from $\sim$2000 K to $\sim$4000 K. For example, Landman
et al. (2021) retrieve a temperature of between 2700 K and 3700 K, while
Seidel et al. (2021) retrieve a temperature of 3389 K (though they note that
this is unusually high). Yet analyses of HST data have yielded temperatures of
2300 K (von Essen et al., 2020) and 2231 K (Edwards et al., 2020). Kesseli et
al. (2022) and Casasayas-Barris et al. (2021) also found that temperatures
varying between $\sim$2000 K and $\sim$4000 K yielded similar final results in
their analyses. We thus carried out our analysis for a range of atmospheric
temperatures. Note that in their analysis of WASP-76b, Azevedo Silva et al.
(2022) made use of the 2500 K atmospheric templates.

We ran a search to determine which of the templates contained absorption lines
within the wavelength ranges of each GRACES order. We did this by dividing the
templates into wavelength ranges corresponding to each GRACES order, and
eliminating wavelength ranges for which the corresponding transit depth was
zero everywhere. We fully eliminated models which had zero transit depth
throughout the full GRACES wavelength range. This yielded a total of 81
templates. While we carried out our analysis for all these species, for the
sake of brevity we only present detailed discussions for species which (i)
yielded a detection in WASP-76b’s atmosphere in the present work, or (ii) had
previously been detected in WASP-76b’s atmosphere.

###  4.2 Doppler Cross-Correlation

To search for atmospheric absorption features in our data, we made use of the
Doppler cross-correlation technique (e.g., Deibert et al., 2021a; Snellen et
al., 2010, among many others). Briefly, this method involves Doppler-shifting
atmospheric models or templates to a range of radial velocities (RVs), and
then cross-correlating the shifted models with each spectrum, in order to
extract the planetary signal from the data as the planet transits the host
star. While a very strong signal can be seen by eye in this correlation map,
it’s often necessary to boost the strength of this signal by then phase-
folding to a range of Keplerian velocities, $K_{p}$. The planetary signal is
then visible as a correlation peak in the 2D $K_{p}$-RV map.

We ran an automated search on each template used in our analysis to determine
whether the template contained spectral features in each GRACES order. Orders
which did not include any spectral features for a given template were excluded
from the cross-correlation analysis for that template. As an example of this,
see Fig. 6, which displays a Ca II atmospheric templates used in one of our
cross-correlations. The template only contains absorption features in a small
region of the full GRACES wavelength range, and orders which did not contain
absorption features were therefore not included in that template’s cross-
correlation analysis.

To estimate the detection significance, we followed e.g., Boucher et al.
(2021) in dividing out the standard deviation of the $K_{p}$-RV map calculated
by excluding a region of $\pm$30 km/s in both $K_{p}$ and RV around the peak
correlation. Boucher et al. (2021) demonstrated that this is a robust,
computationally efficient method of determining the significance of a cross-
correlation detection. Note that we assume that the distribution of the cross-
correlation function is Gaussian (e.g., Brogi et al., 2012; Birkby, 2018).

We chose 30 km/s as a threshold for calculating the standard deviation because
a visual inspection of the results indicated that this would sufficiently
cover even the broadest detected signals. However, to confirm that the chosen
threshold does not impact our final results, we tested the effects of varying
this threshold from 1 km/s to 50 km/s and recalculating the final SNR. We
found that in almost all cases, the final SNR does not vary by more than
1$\sigma$ regardless of the threshold used. The exception is Ca II, which
varied by $\sim$1.5$\sigma$ when the threshold was increased. Due to the very
broad nature of the Ca II signal, however, much of this variation came from
smaller thresholds which include a large portion of the cross-correlation peak
in the standard deviation calculation. The variation in the final SNR for
thresholds which fully encompass the Ca II peak was $<$ 1$\sigma$, as was the
case for the other detected signals. We therefore conclude that a threshold of
30 km/s is sufficient and does not affect our final results.

##  5 Results and Discussion

###  5.1 Detections

####  5.1.1 Detection of WASP-76b’s Atmosphere with the 1D Transmission
Spectra

We began by carrying out the Doppler cross-correlation technique with the one-
dimensional transmission spectrum created for WASP-76b’s atmosphere. Given
that the spectrum contained a number of species which had previously been
detected in WASP-76b’s atmosphere (e.g., Fe I and Ca II; Ehrenreich et al.,
2020; Deibert et al., 2021b), we expected the synthetic transmission spectrum
to correlate strongly with our data. The model contains absorption features
across the full wavelength range of GRACES; however, we excluded orders with
particularly low quality data from our analysis. We determined these low
quality regions by excluding orders for which the average SNR per order across
all spectra was below 20. At these low SNRs, the spectra extracted by the
OPERA pipeline contained unphysical negative values, which in turn resulted in
nan values in the final SysRem-reduced spectra. In total, this threshold
resulted in the exclusion of 6 orders at the blue end of the spectrum for
which the average SNR was below 20.

The results of this cross-correlation are presented in Fig. 3. When
correlating our data with this model, we are able to detect WASP-76b’s
atmosphere at a significance of 6.0$\sigma$. The peak SNR of the cross-
correlation function is located at a Keplerian velocity of
$K_{p}=182^{+12}_{-15}$ km/s, where we have taken as error the point at which
the peak SNR in the cross-correlation function drops by 1$\sigma$. This is
lower than (though within error of) the value reported by Ehrenreich et al.
(2020), but consistent with those determined in Deibert et al. (2021b), using
the same data but a different methodology. The peak SNR is also located at a
$V_{\text{center}}$ value of $-4.6\pm 2.1$ km/s. This value could be
interpreted as the exoplanet’s atmospheric wind speed, and is consistent with
those derived for various atmospheric species in Deibert et al. (2021b),
although we note that the errors are large and we therefore caution against
interpreting this as a true representation of the planet’s atmospheric wind.
As before, we have taken as error the point at which the peak SNR drops by
1$\sigma$.

Figure 3: The results of cross-correlating the one-dimensional synthetic
transmission spectrum generated for WASP-76b’s atmosphere with our
observations. The plot on the left shows the 2D $K_{p}$-RV map, with the peak
correlation identified by the dotted white lines, and the SNR indicated by the
colorbar. The plot on the right shows a slice of the 2D map at the $K_{p}$
value corresponding to the peak correlation. The atmosphere is detected at a
significance of 6.0$\sigma$, with a measured $K_{p}$ of $182^{+12}_{-15}$ km/s
and a measured $V_{\text{center}}$ of $-4.6\pm 2.1$ km/s. The latter could be
interpreted as atmospheric winds.

The species used to create the synthetic transmission spectrum have previously
been detected in the atmosphere of WASP-76b (H2O, Fe I, Na I, K I, Li I, Mn I,
Ca II; Sánchez-López et al., 2022; Ehrenreich et al., 2020; Seidel et al.,
2019; Tabernero et al., 2021; Kesseli et al., 2022; Deibert et al., 2021b),
though we note that H2O has only been detected at near-infrared wavelengths.
It is thus likely that all of these species are contributing to the cross-
correlation signal.

In order to better compare our custom models with results from the more
generic Mantis templates (see the following section), we also created a one-
dimensional transmission spectrum containing only Ca II, H2, and He, and
repeated the cross-correlation process described above. The results of this
are presented in Fig. 4. We detect Ca II in the atmosphere with this model at
a significance of 4.5$\sigma$, with a measured $K_{p}$ of 204${}^{+35}_{-46}$
km/s and a measured $V_{\mathrm{center}}$ of ${-1.0}_{-4.8}^{+4.5}$ km/s.
These results are discussed and compared to the Mantis results in more detail
in Section 5.4.1.

Figure 4: The results of cross-correlating the one-dimensional synthetic
transmission spectrum containing only Ca II, H2, and He generated for
WASP-76b’s atmosphere with our observations. The plot on the left shows the
high-resolution, one-dimensional synthetic transmission spectrum generated
using the methods described in Section 4.1.1. The plot on the top right shows
the 2D $K_{p}$-RV map, with the peak correlation identified by the dotted
white lines and the SNR indicated by the colorbar. The plot on the bottom
right shows a slice of the 2D map at the peak $K_{p}$ value. We detect Ca II
in the atmosphere with this model at a significance of 4.5$\sigma$, with a
measured $K_{p}$ of 204${}^{+35}_{-46}$ km/s and a measured
$V_{\mathrm{center}}$ of ${-1.0}_{-4.8}^{+4.5}$ km/s.

In the following section, we look at individual species separately through
cross-correlations with atmospheric templates from the Mantis Network
(Kitzmann et al., 2023).

####  5.1.2 Detections of Individual Species with the Mantis Network Templates

Using the Mantis Network templates (Kitzmann et al., 2023), we detect Fe I, Ca
II, and Na I at high significance ($>$5$\sigma$) in the atmosphere of
WASP-76b. These detections, along with the Mantis templates cross-correlated
with our spectra, are presented in Figs. 5, 6, and 7. As discussed earlier,
these species have all previously been detected in the atmosphere of WASP-76b.
We briefly discuss each of these detections below. Note that while the
template with the temperature corresponding to the strongest detection is
presented in each figure, we provide all detection significances (which in
most cases are within $<$1$\sigma$ of each other) in Appendix B. We caution
that while we have chosen to display different temperature templates in these
figures, our analysis does not include a true retrieval of the atmospheric
temperature and should not be interpreted as such.

Figure 5: A detection of Fe I absorption in WASP-76b’s atmosphere. Left: the
Mantis Network template cross-correlated with our spectra. The region plotted
in grey was excluded due to the low quality of the data at the edge of GRACES’
wavelength range. The 2500 K template is used. Top Right: The 2D cross-
correlation map. The white lines indicate the peak SNR, which corresponds to a
$>5$$\sigma$ detection of Fe I in WASP-76b’s atmosphere. Bottom Right: A slice
of the 2D cross-correlation map at the $K_{p}$ corresponding to the peak SNR.
The signal is slightly offset from RV = 0 km/s, indicative of winds in the
exoplanet’s atmosphere. Figure 6: A detection of Ca II absorption in
WASP-76b’s atmosphere. The plots are as described in the caption of Fig. 5.
The 2000 K template is used. Only orders containing Ca II lines were used in
the analysis, meaning that no orders were excluded due to low data quality.
Figure 7: A detection of Na I absorption in WASP-76b’s atmosphere. The plots
are as described in the caption of Fig. 5. The 2000 K template is used. Due to
the small number of lines present in the model, we opted to also include lines
from the blue end of the spectrum. When these lines are excluded, the
detection significance falls below 5$\sigma$.

Fe I absorption was first reported by Ehrenreich et al. (2020), and later
confirmed by Tabernero et al. (2021), Kesseli & Snellen (2021), Kesseli et al.
(2022), and Azevedo Silva et al. (2022). In the present work, we detect Fe I
absorption via cross-correlation with the 2500 K Mantis Network template at a
significance of 6.9$\sigma$. When the 2000 K template is used, this
significance falls to 6.6$\sigma$, while the 3000 K template yields a
significance of 6.8$\sigma$ and the 4000 K template yields a significance of
6.0$\sigma$. While this could indicate that the atmospheric layers probed by
Fe I are hotter than the equilibrium temperature, and fall somewhere between
2500 and 3000 K, we caution against reading too much into this result. More
sophisticated modelling will be necessary in order to accurately account for
all factors which may impact the temperature (for e.g., NLTE effects; Fossati
et al., 2020, 2021; Deibert et al., 2021b) and place constraints on the
temperature of the layers probed.

In their initial analysis of the Fe I signal in WASP-76b’s atmosphere,
Ehrenreich et al. (2020) reported asymmetry in the signal between the first
and second halves of the transit (a result which has been interpreted as
condensation and “iron rain”, though see Wardenier et al. (2021) and Savel et
al. (2022) for further interpretations). Yet due to the lower SNR and
resolution of our data, as well as the fact that 10% of the second half of the
transit was lost due to technical issues at the observatory, we are unable to
draw substantive conclusions about this asymmetric signal in the present work.

Using this same 2500 K Fe I template, we find a Keplerian velocity of
$K_{p}=182^{+8}_{-14}$ km/s, in line with our previous results (Deibert et
al., 2021b) and consistent within error with the value reported by Ehrenreich
et al. (2020). We also find a wind speed of
$V{}_{\text{center}}=-4.4^{+0.9}_{-2.1}$ km/s which, again, is consistent with
our previous results (Deibert et al., 2021b) and matches well with the value
we find for the one-dimensional synthetic transmission spectrum above.

We note that we also searched for Fe II absorption (as the exoplanet’s high
atmospheric temperatures could ionize Fe I) but did not detect it with any of
the templates. This is discussed in further detail in Section 5.3.

Ca II was previously detected in WASP-76b’s atmosphere by Casasayas-Barris et
al. (2021) and Deibert et al. (2021b). While we resolved the individual lines
of the Ca II triplet via transmission spectroscopy in Deibert et al. (2021b),
we have now shown that Ca II is also readily detectable via Doppler cross-
correlation with GRACES spectra, even when only a few lines are present in the
atmospheric template (see the left side of Fig. 6).

Using this technique, we detect atmospheric Ca II at a significance of
5.3$\sigma$ when correlated with the 2000 K template. The significance drops
to 4$\sigma$ when we use the 2500 K template, and atmospheric Ca II is not
detectable with the 3000 K template. Interestingly, the significance rises
again with the 4000 K template, to 4.2$\sigma$. Fig. 6 displays the 2000 K
template and results. While this could indicate that the temperature of the
atmospheric layer probed by the Ca II lines falls somewhere between 2000 and
2500 K, we again caution against reading too much into this result. In
particular, we note that Casasayas-Barris et al. (2021) found the greatest
correlation strength with CARMENES spectra for a 4000 K Ca II model, rather
than a 2200 K model matching the planet’s equilibrium temperature. However,
their model was created to match the specific parameters of the WASP-76b
system (unlike the generic Mantis templates used in this work), and also
included the effects of tidally-locked rotation. Even so, the differences in
correlation strengths between their four models (2200 K and 4000 K with and
without tidally-locked rotation) were not significant, and varied between
$\sim$6$\sigma$ and $\sim$8$\sigma$. We conclude that more sophisticated
modelling will be necessary in order to truly constrain the atmospheric
temperature.

Using this 2000 K template, we find a Keplerian velocity of
$K_{p}=193^{+27}_{-17}$ km/s, which is consistent with what we found in
Deibert et al. (2021b), though we note that the errors in this case are
particularly large due to how broad the signal is in the $K_{p}$-RV map. We
also recover a wind speed of $V_{\text{center}}=-7.1^{+5.1}_{-2.7}$ km/s. We
note that this is a greater blueshift than reported in Deibert et al. (2021b);
however, the results are consistent within error (though again, the errors in
this case are particularly large). The large errors in our recovered values
are likely due to the fact that very few lines were used in this cross-
correlation. Nevertheless, we have shown that GRACES is adept at detecting
atmospheric Ca II through cross-correlation, if not at providing stringent
constraints on the Keplerian velocity and atmospheric winds. This could be due
to the fact that we searched for the Ca II lines directly in Deibert et al.
(2021b), whereas in the present work we cross-correlated with a generic
template which may not match the true line widths/depths of the Ca II triplet.
Additionally, because we are effectively averaging the three lines of the Ca
II triplet with the cross-correlation method and searching for all three lines
simultaneously, errors from the noisiest line (at $\sim$850 nm, located close
to the edge of its spectral order) may increase the overall errors in our
detection as compared to the method presented in Deibert et al. (2021b), which
resolves the three lines individually.

Na I was the first species to be detected in WASP-76b’s atmosphere (Žák et
al., 2019; Seidel et al., 2019), and has been recovered in a number of later
studies (Tabernero et al., 2021; Seidel et al., 2021; Deibert et al., 2021b;
Kesseli et al., 2022; Azevedo Silva et al., 2022). In this work, we detect Na
I at a significance of 5.0$\sigma$ when using a 2000 K template. With the 2500
K template, this drops to 4.2$\sigma$. Interestingly, the significance rises
slightly with the 3000 K template, yielding a 4.7$\sigma$ detection; the 4000
K template yields a 4.1$\sigma$ detection. We display the 2000 K template in
Fig. 7. With this template, we find $K_{p}=201^{+11}_{-12}$ km/s. Again, the
errors are particularly large; this may be due to the small number of lines
used in the cross-correlation. We also determine a wind speed of
$V_{\text{center}}=-2.6^{+1.5}_{-1.8}$ km/s. This is consistent within error
with the results from Deibert et al. (2021b).

The results from this section are summarized in Table 4.

Table 4: Summary of detected ($>$5$\sigma$) and tentatively detected
(5$>$$\sigma$$>$3) species.

Species | Significance ($\sigma$) | Temperature (K) |  $K_{p}$ (km/s) |  $V_{\text{center}}$ (km/s)
---|---|---|---|---
Fe I | 6.9 | 2500 | $182^{+8}_{-14}$ | $-4.4^{+0.9}_{-2.1}$
Ca II | 5.3 | 2000 | $193^{+27}_{-17}$ | $-7.1^{+5.1}_{-2.7}$
Na I | 5.0 | 2000 | $201^{+11}_{-12}$ | $-2.6^{+1.5}_{-1.8}$
Li I | 4.2 | 2500 | $221^{+17}_{-14}$ | $0.7\pm 2.4$
K I | 4.4 | 3000 | $209^{+29}_{-6}$ | $-5.6\pm 1.2$
Cr I | 4.0 | 3000 | $208^{+8}_{-11}$ | $-3.2^{+1.8}_{-1.2}$
V I | 4.6 | 4000 | $140^{+13}_{-16}$ | $-7.4^{+1.8}_{-2.1}$

Note. — Column 1: species detected. Column 2: significance of detection.
Column 3: temperature of atmospheric template which yields the highest
significance. N.B. we do not claim that this is indeed the atmospheric
temperature at the layers probed. Column 4: Keplerian velocity. Column 5:
offset from expected line location, assuming a Gaussian profile. In some
cases, this could be attributed to atmospheric winds.

###  5.2 Tentative Detections

In addition to the results presented above, a number of Mantis Network
templates yielded detections with significances below 5$\sigma$ yet above
3$\sigma$. We classify these results as tentative detections warranting
follow-up studies (although we note that all of these species have previously
been detected in the atmosphere of WASP-76b, meaning that in this case a
follow-up study with GRACES is not necessary in order to confirm their
presence). Note again that while the template corresponding to the strongest
tentative detection is presented in each figure, we provide all detection
significances in Appendix B.

The species tentatively detected in WASP-76b’s atmosphere include Li I (Fig.
8), K I (Fig. 9), Cr I (Fig. 10), and V I (Fig. 11). The former two species
were also tentatively detected in Deibert et al. (2021b) using this same
dataset, albeit different methodology, and tentatively detected by Casasayas-
Barris et al. (2021) using CARMENES/Calar Alto. Li I was detected by Tabernero
et al. (2021), Kesseli et al. (2022), and Azevedo Silva et al. (2022) using
different instruments, while K I was detected by Tabernero et al. (2021) but
only tentatively detected by Kesseli et al. (2022). On the other hand, V I and
Cr I were not considered in Deibert et al. (2021b), but were previously
detected by Kesseli et al. (2022) and Azevedo Silva et al. (2022).

In the case of Li I, the 2500 K template yields the highest significance,
corresponding to a 4.2$\sigma$ tentative detection. However, we note that
there are a number of additional peaks present at high significances. The
Keplerian velocity is higher than those recovered for other species, with
$K_{p}=221^{+17}_{-14}$ km/s, while the wind speed is
$V_{\text{center}}=0.7\pm 2.4$ km/s.

Figure 8: A tentative detection of Li I absorption in WASP-76b’s atmosphere.
The plots are as described in the caption of Fig. 5. While we do see a peak at
4.2$\sigma$ near the expected location of the exoplanet’s atmosphere, the
noise in the cross-correlation map prevents us from confidently labelling this
as a detection. The 2500 K template was used, and 6 orders with low data
quality containing only weak Li I lines at the blue end of the spectrum were
excluded (shown in grey).

In the case of K I, we find the highest significance for the 3000 K template,
which is detected at 4.4$\sigma$. However, as can be seen in Fig. 9, there are
a number of peaks approaching 3$\sigma$ throughout the $K_{p}$-RV map, which
calls this result into question. Nevertheless, we are able to extract a
Keplerian velocity of $K_{p}=209^{+29}_{-6}$ km/s and a wind speed of
$V_{\text{center}}=-5.6\pm 1.2$ km/s. While K I has already been detected or
tentatively detected by several other studies (Tabernero et al., 2021;
Casasayas-Barris et al., 2021; Deibert et al., 2021a; Kesseli et al., 2022),
the results presented here have likely been affected by an imperfect telluric
correction (note that the strongest K I lines fall within a forest of dense O2
absorption; see also Appendix A for a visualization of the efficacy of our
telluric removal) and should be treated with particular scrutiny. We note as
well that both the 2500 K and 4000 K templates yield very similar
significances of 4.3$\sigma$.

Figure 9: A tentative detection of K I absorption in WASP-76b’s atmosphere.
The plots are as described in the caption of Fig. 5. While we do see a peak at
4.4$\sigma$ at roughly the expected location of the exoplanet’s atmosphere,
the noise in the cross-correlation map prevents us from confidently labelling
this as a detection. The 3000 K template was used. The K I line at the blue
end of the spectrum was excluded due to the low quality of the data (shown in
grey).

For Cr I, we find the highest significance using the 3000 K model, which we
detect at 4.0$\sigma$. Yet similarly to K I, there are many additional peaks
at the 3$\sigma$ level in the $K_{p}$-RV map, meaning that this result should
also be treated with scrutiny. The peak significance is located at a Keplerian
velocity of $K_{p}=208^{+8}_{-11}$ km/s and a positive (i.e., redshifted) wind
speed of $V_{\text{center}}=3.2^{+1.8}_{-1.2}$ km/s. This is different from
the other $V_{\text{center}}$ results presented in this work, and further
indicates that this tentative detection should be considered with particular
scrutiny.

Figure 10: A tentative detection of Cr I absorption in WASP-76b’s atmosphere.
The plots are as described in the caption of Fig. 5. While we do see a peak at
4.0$\sigma$ at roughly the expected location of the exoplanet’s atmosphere,
the noise in the cross-correlation map prevents us from confidently labelling
this as a detection. The 3000 K template was used. Six orders at the blue end
of the spectrum were excluded from the analysis (indicated in grey), similar
to the 1D high-resolution synthetic transmission spectrum and the Fe I model.

Finally, we detect V I at a significance of 4.6$\sigma$ using the 4000 K
template. The Keplerian velocity is much lower than that detected for other
species, with $K_{p}=140^{+13}_{-16}$ km/s, while the atmospheric wind speed
is $V_{\text{center}}=-7.4^{+1.8}_{-2.1}$ km/s. Again, we caution that this
result is tentative. We also note that this is the only detected (or
tentatively detected) species which has the strongest correlation with the
4000 K template. This could indicate that our V I observations are probing a
hotter region of the atmosphere; however, the differences between the
calculated significances for the four templates are small (4.2$\sigma$ for the
3000 K template, 4.0$\sigma$ for the 2500 K template, and 3.6$\sigma$ for the
2000 K template) and likely not significant enough to determine the
temperature concretely.

Figure 11: A tentative detection of V I absorption in WASP-76b’s atmosphere.
The plots are as described in the caption of Fig. 5. The 4000 K template was
used. Six orders at the blue end of the spectrum were excluded from the
analysis (indicated in grey), similar to the 1D high-resolution synthetic
transmission spectrum and the Fe I model.

The tentative detections described in this section are outlined in Table 4. As
can be seen in the figures presented in this section, there are a number of
spurious peaks at $K_{p}$ and $V_{\mathrm{center}}$ values away from the peak
correlation which are largely limiting our ability to classify these as
definite detections. As demonstrated in Esteves et al. (2017), spurious peaks
$>$1$\sigma$ can arise in cross-correlations, particularly in cases where the
templates contain many closely spaced lines. Combining our observations with
additional observations from ESPRESSO or HARPS would help reduce the
contribution of these spurious peaks; however, such an analysis is beyond the
scope of this work.

###  5.3 Non-Detections and Model Injection/Recovery Tests

The remaining Mantis Network templates analyzed in this work did not result in
significant ($>5\sigma$) or even tentative ($3<\sigma<5$) detections. For the
sake of brevity, we have only included detailed plots for a subset of these
species. The 2D cross-correlation maps for the rest are presented in Appendix
C.

In some cases, there were species detected (or tentatively detected) by
previous studies that we were not able to recover with our analysis. These
include Mg I, Mn I, Ni I, Sr II, Ba II, and Co I. Mn I and Mg I were detected
by Tabernero et al. (2021), Kesseli et al. (2022), and Azevedo Silva et al.
(2022); Ni I and Sr II were detected by Kesseli et al. (2022); Ba II was
detected by Azevedo Silva et al. (2022); and Co I was tentatively detected by
Kesseli et al. (2022). Notably, the detections in Azevedo Silva et al. (2022)
were made using the same Mantis Network templates that we employed in the
present work (Kitzmann et al., 2023).

To investigate these non-detections further, we carried out model
injection/recovery tests for each of the above species. We also included Ti I,
Ti II, Ca I, Al I, Sc I, Sc II, and Zr I, which Kesseli et al. (2022) note
should be readily observable in the atmosphere of WASP-76b (at the wavelength
range covered by ESPRESSO) but which we did not detect in our analysis; H2O,
which has been detected in the near-infrared in the atmosphere of WASP-76b
(Sánchez-López et al., 2022) but which we did not detect in the optical; and
Fe II, to investigate whether or not ionized Fe I would be detectable in our
observations given that Fe I was detected.

To carry out these tests, we injected each atmospheric template into our data
with a Keplerian velocity equivalent to the negative of the planet’s Keplerian
velocity. We injected the templates at this negative value, rather than at the
planet’s true velocity, in order to avoid boosting any weak absorption that
may be present at the planet’s true velocity. We then repeated the Doppler
cross-correlation process described in Section 4.2, albeit searching for
signals at $-K_{p}$. For each species, we carried out this injection/recovery
process using the 2000 K, 2500 K, 3000 K, and 4000 K templates. We note that
because we are cross-correlating with the same templates that have been
injected into the data, and it is unlikely that the true atmosphere is
identical to these templates, our model injection/recovery tests are likely
overestimating our detection sensitivities.

In the cases of Sr II and Al I, we were unable to recover any of the injected
models. This suggests that even if these species were present in the
atmosphere of WASP-76b, our GRACES spectra would not be sensitive enough to
detect them. Notably, this explains why we were unable to detect Sr II, which
was previously detected in the atmosphere of WASP-76b (Kesseli et al., 2022).

In the case of Ni I, which was previously detected by Kesseli et al. (2022),
we are able to recover the 2500 K template at 5.7$\sigma$ but unable to
significantly detect the injected 2000 K template (although we do tentatively
recover it, at a significance of 4.5$\sigma$). We note that there are no lines
present in the 3000 K or 4000 K Mantis Network templates at the GRACES
wavelength range. In their analysis, Kesseli et al. (2022) used an isothermal
_P–T_ profile of 3000 K, though they also tested the effects of varying the
temperature to 2000 K and 4000 K. With the 3000 K model, they detected Ni I at
a significance of 5.01$\sigma$. Together, these results suggest that Ni I is
present in the atmosphere, and that the layer probed by Ni I may be hotter
than $\sim$2500 K. In the present work, we are unable to investigate the
possibility of atmospheric Ni I at a temperature of 3000 K. The results of
this injection/recovery test are shown in Fig. 12.

Figure 12: The model injection/recovery process for Ni I. Left: the Mantis
Network templates injected and cross-correlated with our data. The 2000 K
template is shown in blue, and the 2500 K in orange. The 3000 K and 4000 K
templates are omitted because there are no lines present at the GRACES
wavelength range. Top Right: The 2D cross-correlation map for the template
recovered at the highest significance, which in this case is the 2500 K
template. The white lines indicate the peak SNR, which is also the velocity at
which the template was injected into our data. Bottom Right: Slices of the 2D
cross-correlation maps for each of the templates, with the 2000 K template
shown in blue and the 2500 K template shown in orange as in the plot on the
left. The 2500 K template is recovered at a significance of $>$5$\sigma$,
while the 2000 K template is only tentatively recovered.

In the case of Ba II, which was detected by Azevedo Silva et al. (2022) using
the 2500 K Mantis Network template, only the 3000 K and 4000 K injected
templates resulted in significant recovered detections of 6.1 and 8.1$\sigma$
respectively. On the other hand, we are unable to significantly detect the
2000 K or 2500 K templates. This could indicate that the atmospheric layer
probed by Ba II is cooler than 3000 K, and that our GRACES spectra are not
sensitive to Ba II at these cooler atmospheric temperatures (thus explaining
why we did not detect the model that Azevedo Silva et al. (2022) detects). The
results of this injection/recovery test are shown in Fig. 13.

Figure 13: The model injection/recovery process for Ba II. The plots are as
described in the caption of Fig. 12, however in this case a 3000 K template is
also displayed in green, and a 4000 K template (which resulted in the
strongest recovered detection) is displayed in pink.

We are able to recover the 4000 K Mg I model at a significance of 7.2$\sigma$,
but do not recover any of the other Mg I models. The results are shown in Fig.
14. This is not particularly surprising; as can be seen in Fig. 14, the
absorption lines present across the full GRACES wavelength range in the 4000 K
template are in general stronger than those in the lower temperature
templates. Mg I was previously detected by Tabernero et al. (2021), Kesseli et
al. (2022), and Azevedo Silva et al. (2022), all using ESPRESSO data. Azevedo
Silva et al. (2022) used the 2500 K Mantis Network template to make 4.4 and
9.5$\sigma$ detections (depending on the night), whereas Kesseli et al. (2022)
used a 3000 K model to detect Mg I at a significance of 6.94$\sigma$ (though
as with Ni I, their detection strength doesn’t vary significantly when 2000 K
or 4000 K templates are used instead). On the other hand, Tabernero et al.
(2021) detected Mg I through directly resolving absorption lines at $\sim$457
and $\sim$517nm; their detection strengths ranged from 2.8 to 7.5$\sigma$.
Together, these results suggest that Mg I would be detectable in GRACES
spectra at a high ($\sim$4000 K) temperature, but that it is likely present at
a lower temperature in the atmosphere of WASP-76b.

Figure 14: The model injection/recovery process for Mg I. The plots are as
described in the captions of Figs. 12 and 13.

Likewise, we are only able to recover the 4000 K Mn I model at a $>$5$\sigma$
significance. This is shown in Fig. 15. Mn I was detected in ESPRESSO data by
Tabernero et al. (2021), Kesseli et al. (2022), and Azevedo Silva et al.
(2022) (the latter using the 2500 K Mantis Network template); as with Mg I, we
conclude that Mn I is likely present in the atmosphere at a temperature below
4000 K, which would not be detectable in our GRACES spectra.

Figure 15: The model injection/recovery process for Mn I. The plots are as
described in the captions of Figs. 12 and 13.

We can recover the injected 3000 K and 4000 K Co I templates at high
significance (6.4 and 6.7$\sigma$ respectively) but are unable to recover the
2000 K or 2500 K templates at $>$5$\sigma$. Co I was only tentatively detected
by Kesseli et al. (2022) at a significance of 4.03$\sigma$; our results
indicate that the atmospheric layer probed by Co I may be cooler than 3000 K,
at a temperature to which our GRACES spectra are not sensitive. The results of
this injection/recovery test are displayed in Fig. 16.

Figure 16: The model injection/recovery process for Co I. The plots are as
described in the captions of Figs. 12 and 13.

The Ti I injections result in strong detections for all temperatures, with the
3000 K template recovered at the highest significance (23.1$\sigma$). As was
discussed in Kesseli et al. (2022), Ti I should be readily detectable in the
atmosphere of WASP-76b, yet they were unable to detect it in their ESPRESSO
observations. The fact that we are also unable to detect it in our original
analysis indicates that Ti I may be trapped in condensates via titanium cold-
trapping (e.g., Spiegel et al., 2009; Parmentier et al., 2013). The results of
this injection/recovery test are shown in Fig. 17.

Figure 17: The model injection/recovery process for Ti I. The plots are as
described in the captions of Figs. 12 and 13.

Ti II, on the other hand, can only be recovered with the 4000 K template; this
is shown in Fig. 18. Note that the 2000 K template contains no lines in the
GRACES wavelength range. Combined with our Ti I results, it’s likely that any
titanium present in the atmosphere is trapped in condensates.

Figure 18: The model injection/recovery process for Ti II. The plots are as
described in the captions of Figs. 12 and 13.

We are able to recover all of the Ca I templates at a high ($>$5$\sigma$)
significance. However given the strong Ca II signals reported in the present
work and Deibert et al. (2021b), it’s likely that at the atmospheric layers
probed by our observations, the majority of Ca I has been ionized. This
explains our non-detection of Ca I, as well as the strong Ca II signal
detected in this work and Deibert et al. (2021b). The results of this
injection/recovery test are displayed in Fig. 19.

Figure 19: The model injection/recovery process for Ca I. The plots are as
described in the captions of Figs. 12 and 13.

We can recover the 2000 K, 2500 K, and 3000 K injected Sc I templates, as well
as the 3000 K Zr I template, at high significances. Similarly, we can recover
the 4000 K Sc II model at a $>$5$\sigma$ significance, but do not recover the
other models. Sc I and Sc II have not been detected in the atmosphere of
WASP-76b; Kesseli et al. (2022) show that both Sc I and Sc II should be
marginally detectable (but were not detected) in ESPRESSO data. Combined with
our model injection/recovery test, these results could indicate that Sc I is
not present in the atmosphere, or that it is ionized and present at a
temperature $<$4000 K (as Sc II has only a few lines in the optical at these
cooler temperatures). Likewise, Kesseli et al. (2022) could not detect Zr I.
They suggest that Zr I may be ionized (and that Zr II is not readily
detectable in the atmosphere); our analysis also suggests that Zr I could be
present at a temperature cooler than $\sim$3000 K, which would not be
detectable in our spectra. These results are shown in Fig. 20 for Sc I, Fig.
21 for Sc II, and 22 for Zr I.

Figure 20: The model injection/recovery process for Sc I. The plots are as
described in the captions of Figs. 12 and 13. Figure 21: The model
injection/recovery process for Sc II. The plots are as described in the
captions of Figs. 12 and 13. Figure 22: The model injection/recovery process
for Zr I. The plots are as described in the captions of Figs. 12 and 13.

The 4000 K Fe II template is recovered at a $>$5$\sigma$ significance, while
we are unable to recover the 3000 K template. We do not include the 2000 K or
2500 K templates in our analysis as they do not contain any lines in the
GRACES wavelength range. These results are shown in Fig. 23; they indicate
that any Fe II present in the regions probed is likely at a temperature lower
than 4000 K, or that the Fe I has mostly not ionized in the regions we’re
probing.

Figure 23: The model injection/recovery process for Fe II. The plots are as
described in the captions of Figs. 12 and 13.

Finally, we are able to detect the injected 2000 K H2O template at a
significance of 8.3$\sigma$, but are unable to detect the 2500 K or 3000 K
templates. There are no lines present in the 4000 K template at the GRACES
wavelength range. We note that Sánchez-López et al. (2022) previously detected
H2O at a significance of 5.5$\sigma$ in the atmosphere of WASP-76b, albeit
with near-infrared spectra, using a pressure-temperature profile
representative of the terminator region. Our results suggest that either H2O
is present at an atmospheric layer hotter than 2000 K, which we are not
sensitive to with our GRACES spectra, or that our telluric correction routine
(see Section 3.1 and Appendix A) was unable to fully remove the telluric H2O
absorption, which could have impacted our ability to detect water in the
planet’s atmosphere. The results of this injection/recovery test are shown in
Fig. 24.

Figure 24: The model injection/recovery process for H2O. The plots are as
described in the captions of Figs. 12 and 13.

###  5.4 Discussion

We have recovered detections of Fe I, Na I, and Ca II in the atmosphere of
WASP-76b, and reported tentative detections of Li I, K I, Cr I, and V I. All
of these species have previously been detected in WASP-76b’s atmosphere; here
we demonstrate that they are readily detectable with GRACES/Gemini North, and
should be targets of interest in future ExoGemS analyses of other planets.

Interestingly, we also reported a number of non-detections, including for
species which were previously detected with other instruments. There are
several potential explanations for these discrepancies, and we investigated
them further using model injection/recovery tests.

In particular, Mg I and Mn I were previously detected by Tabernero et al.
(2021), Kesseli et al. (2022), and Azevedo Silva et al. (2022) using ESPRESSO,
while Kesseli et al. (2022) also detected Sr II. We were unable to detect any
of these species in our data; however, we were also unable to recover injected
models of these species at temperatures cooler than 4000 K with our
injection/recovery tests. This suggests that our observations are not
sensitive to these species at cooler temperatures, but that they may well be
present in WASP-76b’s atmosphere (as indicated by Tabernero et al. 2021;
Kesseli et al. 2022; Azevedo Silva et al. 2022). These results are not
particularly surprising given the fact that ESPRESSO extends to bluer
wavelengths than GRACES, and all of these species exhibit strong absorption
lines at the blue end of the optical regime. Furthermore, the higher spectral
resolution of ESPRESSO (R $>$ 100,000) compared to GRACES (R $\sim$ 66,000)
means that ESPRESSO can resolve a greater number of individual lines, likely
boosting the instrument’s detection capabilities.

In some cases, our non-detections can provide hints as to the atmospheric
temperatures probed by various species. For example, while Azevedo Silva et
al. (2022) used a 2500 K template to detect Ba II in their ESPRESSO
observations, our model injection/recovery test demonstrated that Ba II is not
detectable in our GRACES data at a temperature of 2500 K, but would have been
detected if it were present at a temperature of 3000 K. We find similar
results for Co I, suggesting that both of these species may be present at
atmospheric layers with temperatures cooler than $\sim$3000 K.

In other cases, our non-detections can help shed light on the atmospheric
chemistry of WASP-76b. As in Kesseli et al. (2022), we find that Ca I would
have been readily detected if it were present in the atmosphere. Yet our
inability to detect Ca I, combined with our strong detection of Ca II,
indicates that the majority of calcium present in the region of the atmosphere
we’re probing has been ionized. This is consistent with other recent analyses
of ultra-hot Jupiter atmospheres, in which a number of species are seen to be
ionized as well (e.g., Azevedo Silva et al., 2022; Zhang et al., 2022; Merritt
et al., 2021; Borsa et al., 2021).

Likewise, our non-detection of Ti I in the atmosphere of WASP-76b provides
further insight into its atmospheric chemistry. Through our model
injection/recovery test, we showed that the high-resolution and broad
wavelength coverage of GRACES make Ti I readily detectable at a range of
temperatures. Yet the fact that we are unable to detect Ti I could indicate
that titanium is depleted at the terminator region, perhaps because it has
condensed on the cooler night-side of the planet and is trapped in condensates
(for e.g., CaTiO3; i.e., a titanium cold-trap; Spiegel et al. 2009; Parmentier
et al. 2013). Alternatively, titanium may condense at the terminator region
only, yet still be present in the gas phase elsewhere in the atmosphere.
Future work investigating the day-side emission spectrum of WASP-76b (as in
e.g., Hoeijmakers et al. 2022) could help shed light on whether titanium is
depleted locally or globally.

In either case, this result adds to the growing body of work indicating that
titanium is depleted in certain ultra-hot Jupiter transmission spectra (e.g.,
Merritt et al., 2021; Hoeijmakers et al., 2022; Kesseli et al., 2022).
Interestingly, Ti I was recently detected in the transmission spectrum of
WASP-189b (Stangret et al., 2022), which has a slightly higher equilibrium
temperature than WASP-76b (T${}_{\mathrm{eq}}\sim 2600$ K; Anderson et al.
2018). TiO was also detected in WASP-189b’s transmission spectrum by Prinoth
et al. 2022; likewise, Ti II was detected in the transmission spectra of
KELT-9b (Teq $\sim$ 4000 K; Hoeijmakers et al., 2019). Together, these results
suggest that Ti I is depleted and potentially cold-trapped in “cooler” ultra-
hot Jupiter atmospheres (i.e., T${}_{\mathrm{eq}}<\sim 2400$ K), while the
hottest ultra-hot Jupiters do appear to exhibit titanium absorption in their
atmospheres. Future analyses of ultra-hot Jupiters across a range of
equilibrium temperatures will help shed light on these different atmospheric
regimes. Our present study has demonstrated that GRACES is well-suited to
investigating Ti I depletion and cold-trapping in ultra-hot Jupiter
atmospheres.

####  5.4.1 Comparison Between Custom Models and Mantis Network Templates

While a full comparison between the results obtained with custom models and
the Mantis Network templates for all species included here is beyond the scope
of this work, we generated a Ca II-only model using the methodology described
in Section 4.1.1 in order to better compare the two methods. We are able to
detect Ca II with both models, as can be seen in Figs. 4 and 6. The 2000 K
Mantis Network template is detected at a slightly higher significance of
5.3$\sigma$, whereas we detect the custom Ca II model at a significance of
4.5$\sigma$.

The cross-correlations signals are broad for both models, which means the
associated $K_{p}$ and $V_{\mathrm{center}}$ values have large errors.
Nevertheless, we we find a Keplerian velocity of $K_{p}=193^{+27}_{-17}$ km/s
and wind speed of $V_{\mathrm{center}}=-7.1^{+5.1}_{-2.7}$ km/s for the Mantis
template, while our custom model results in a Keplerian velocity of
$K_{p}=204^{+35}_{-46}$ km/s and a measured $V_{\mathrm{center}}$ of
$-1.0{}^{+4.5}_{-4.8}$ km/s. While the wind speed values in particular are
somewhat different from one another (though still within error), we note that
the broad nature of these signals makes it difficult to accurately determine
these parameters.

Overall, we conclude that both methods allow us to detect Ca II, and that the
Mantis Network templates can be useful in quickly exploring the effects of
different temperatures in isothermal profiles on our detection capabilities.

##  6 Conclusion

In this work, we presented the results of a cross-correlation analysis on
spectra from one transit of the ultra-hot Jupiter WASP-76b. The observations
were obtained with GRACES at the Gemini North telescope as part of the ongoing
ExoGemS survey. Using both a custom one-dimensional transmission spectrum
generated for WASP-76b’s atmosphere as well as a grid of generic ultra-hot
Jupiter atmospheric templates from the Mantis Network (Kitzmann et al., 2023),
we searched for absorption due to a suite of atomic and molecular features. We
recover previous detections of Fe I, Na I, and Ca II via cross-correlations
with model templates, and report tentative detections as well as non-
detections of a range of species, some of which had previously been detected
with other instruments. These results allow us to assess the capabilities of
GRACES compared to other high-resolution optical spectrographs while also
validating our methodology for use in future ExoGemS analyses.

## Acknowledgments

We thank the referee for a thoughtful and constructive review which has
greatly helped improve the quality of our work.

We thank D. Kitzmann, H.J. Hoeijmakers, and collaborators for making their
standard grid of masks and templates publicly available via the Mantis Network
(Kitzmann et al., 2023).

We also thank the staff of the Gemini North Observatory for their help in
obtaining these observations. We extend a particular thank you to Teo Mocnik,
the Contact Scientist for this program and observer for the data obtained in
this work; Siyi Xu, the secondary Contact Scientist for this program; and
Brittney Cooper, the telescope operator on duty during these observations.

EKD acknowledges support from an NSERC Vanier Canada Graduate Scholarship and
an NSERC Postdoctoral Fellowship.

RJ acknowledges support of a Rockefeller Foundation Bellagio Center residency.

These observations were obtained through the Gemini Remote Access to CFHT
ESPaDOnS Spectrograph (GRACES). ESPaDOnS is located at the Canada-France-
Hawaii Telescope (CFHT), which is operated by the National Research Council of
Canada, the Institut National des Sciences de l’Univers of the Centre National
de la Recherche Scientifique of France, and the University of Hawai’i.
ESPaDOnS is a collaborative project funded by France (CNRS, MENESR, OMP,
LATT), Canada (NSERC), CFHT and ESA. ESPaDOnS was remotely controlled from the
international Gemini Observatory, a program of NSF’s NOIRLab, which is managed
by the Association of Universities for Research in Astronomy (AURA) under a
cooperative agreement with the National Science Foundation on behalf of the
Gemini partnership: the National Science Foundation (United States), the
National Research Council (Canada), Agencia Nacional de Investigación y
Desarrollo (Chile), Ministerio de Ciencia, Tecnología e Innovación
(Argentina), Ministério da Ciência, Tecnologia, Inovações e Comunicações
(Brazil), and Korea Astronomy and Space Science Institute (Republic of Korea).

This work was enabled by observations made from the Gemini North telescope,
located within the Maunakea Science Reserve and adjacent to the summit of
Maunakea. We are grateful for the privilege of observing the Universe from a
place that is unique in both its astronomical quality and its cultural
significance.

##  Appendix A SysRem Results

Figs. 25 to 29 present the results of applying the SysRem algorithm to all
orders of the data, as described in Section 3.1. As can be seen in the
figures, the standard deviation is much higher at the blue end of the spectrum
(where the SNR of the raw data is lower, and the SysRem algorithm performed
poorly). It rises again in regions that contain greater telluric
contamination.

Figure 25: The results of applying the SysRem algorithm to 5 orders of the
data at the blue end of the spectrum. Top: The raw data after being extracted
from the telescope and normalized. Middle: The results of applying 7
iterations of the SysRem algorithm to the data. Bottom: The standard deviation
of the SysRem-reduced data along each wavelength channel. As described in
Section 5.1, all of these orders were excluded from our analysis. Figure 26:
The results of applying the SysRem algorithm to 5 orders of the data. The
panels are as described in the caption of Fig. 25. One order at the blue end
of this plot was excluded from our analysis. Note that the y-axis scale in the
bottom plot differs from that in Fig. 25. Figure 27: The results of applying
the SysRem algorithm to 5 orders of the data. The panels are as described in
the caption of Fig. 25. Note that the y-axis scale in the bottom plot differs
from that in Fig. 25. Figure 28: The results of applying the SysRem algorithm
to 5 orders of the data. The panels are as described in the caption of Fig.
25. Note that the y-axis scale in the bottom plot differs from that in Fig.
25. Note as well the rise in the standard deviation around 760 nm due to
greater telluric contamination. Figure 29: The results of applying the SysRem
algorithm to 5 orders of the data at the red end of the spectrum. The panels
are as described in the caption of Fig. 25. Note that the y-axis scale in the
bottom plot differs from that in Fig. 25. Note as well the rise in the
standard deviation around 940 nm due to greater telluric contamination.

##  Appendix B Detection Significances for All Templates

Table 5 presents the detection significances for all templates corresponding
to the species detected or tentatively detected in this work. We note that
while the figures in Sections 5.1 and 5.2 only display the template resulting
in the highest SNR detection, the differences between different templates are
in many cases small.

Table 5: A summary of all detection significances and associated parameters
for all temperatures for the detected ($>5\sigma$) and tentatively detected
($>3\sigma$) species. The columns are as described in the Table Notes of Table
4.

Species | Temperature (K) | Significance ($\sigma$) |  $K_{p}$ (km/s) |  $V_{\mathrm{center}}$ (km/s)
---|---|---|---|---
| 2000 | 6.6 | $183^{+7}_{-16}$ | $-4.6^{+1.2}_{-2.1}$
Fe I | 2500 | 6.9 | $182^{+8}_{-14}$ | $-4.4^{+0.9}_{-2.1}$
| 3000 | 6.8 | $181^{+9}_{-13}$ | $-4.4^{+1.5}_{-1.8}$
| 4000 | 6.0 | $183^{+10}_{-14}$ | $-3.8^{+1.8}_{-2.1}$
| 2000 | 5.3 | $193^{+27}_{-17}$ | $-7.1^{+5.1}_{-2.7}$
Ca II | 2500 | 4.0 | $217^{+14}_{-37}$ | $-3.5^{+4.5}_{-3.3}$
| 3000 | 2.3 | N/A | N/A
| 4000 | 4.2 | $171^{+10}_{-12}$ | $-9.4^{+1.5}_{-3.3}$
| 2000 | 5.0 | $201^{+11}_{-12}$ | $-2.5^{+1.5}_{-1.8}$
Na I | 2500 | 4.2 | $200^{+14}_{-15}$ | $-2.5\pm 1.8$
| 3000 | 4.7 | $203^{+10}_{-12}$ | $-2.3^{+1.5}_{-1.8}$
| 4000 | 4.1 | $201^{+11}_{-13}$ | $-2.8^{+1.8}_{-1.5}$
| 2000 | 3.9 | $222^{+18}_{-13}$ | $0.4\pm 2.4$
Li I | 2500 | 4.2 | $221^{+17}_{-14}$ | $0.7\pm 2.4$
| 3000 | 4.0 | $221^{+19}_{-13}$ | $0.7^{+2.4}_{-2.1}$
| 4000 | 3.8 | $225^{+18}_{-16}$ | $1.0^{+2.7}_{-2.4}$
| 2000 | 3.9 | $244^{+9}_{-40}$ | $-4.1\pm 1.5$
K I | 2500 | 4.3 | $211^{+35}_{-8}$ | $-5.3^{+1.2}_{-1.5}$
| 3000 | 4.4 | $209^{+29}_{-6}$ | $-5.6\pm 1.2$
| 4000 | 4.3 | $209^{+28}_{-7}$ | $-5.6\pm 1.2$
| 2000 | 0.7 | N/A | N/A
Cr I | 2500 | 4.0 | $209^{+8}_{-10}$ | $3.5^{+1.5}_{-1.2}$
| 3000 | 4.0 | $208^{+8}_{-11}$ | $3.2^{+1.8}_{-1.2}$
| 4000 | 3.8 | $206\pm 10$ | $3.2^{+1.5}_{-13.8}$
| 2000 | 3.6 | $142^{+81}_{-17}$ | $-8.0^{+2.1}_{-1.8}$
V I | 2500 | 4.0 | $143^{+78}_{-18}$ | $-7.7^{+1.8}_{-2.1}$
| 3000 | 4.2 | $140^{+14}_{-16}$ | $-7.7^{+1.8}_{-2.1}$
| 4000 | 4.6 | $140^{+13}_{-16}$ | $-7.4^{+1.8}_{-2.1}$

Note. — For templates which were neither detected nor tentatively detected, we
cannot extract a $K_{p}$ or $V_{\mathrm{center}}$ value; thus, we have marked
those values as N/A.

##  Appendix C Cross-Correlation Maps for Non-Detections

Figs. 30 and 31 present the 2D $K_{p}$-RV maps for the species which were not
detected in this work. For the sake of brevity, we have only included the 2000
K models. We define a non-detection as being under 3$\sigma$.

Figure 30: The 2D $K_{p}$-RV maps for species which were not detected in this
analysis. All plots were made using the 2000 K template; higher-temperature
templates also resulted in non-detections. The species is indicated in the top
right corner. The white lines indicate the expected $K_{p}$ and RV of the
signal. Figure 31: The 2D $K_{p}$-RV maps for species which were not detected
in this analysis. The figures are as described in the caption of Fig. 30.

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