diff --git "a/2dE2T4oBgHgl3EQf5gh4/content/tmp_files/2301.04191v1.pdf.txt" "b/2dE2T4oBgHgl3EQf5gh4/content/tmp_files/2301.04191v1.pdf.txt"
new file mode 100644--- /dev/null
+++ "b/2dE2T4oBgHgl3EQf5gh4/content/tmp_files/2301.04191v1.pdf.txt"
@@ -0,0 +1,2493 @@
+Springer Nature 2021 LATEX template
+A JWST transmission spectrum of a nearby
+Earth-sized exoplanet
+Jacob Lustig-Yaeger1*, Guangwei Fu2*, E. M. May1, Kevin N.
+Ortiz Ceballos3, Sarah E. Moran4, Sarah Peacock5,6, Kevin
+B. Stevenson1, Mercedes L´opez-Morales3, Ryan J.
+MacDonald7,8, L. C. Mayorga1, David K. Sing2,9, Kristin S.
+Sotzen1, Jeff A. Valenti10, Jea Adams3, Munazza K.
+Alam, Natasha E. Batalha12, Katherine A. Bennett9, Junellie
+Gonzalez-Quiles9, James Kirk13, Ethan Kruse5,6, Joshua D.
+Lothringer14, Zafar Rustamkulov9 and Hannah R. Wakeford15
+1Johns Hopkins APL, Laurel, MD, 20723, USA.
+2Department of Physics & Astronomy, Johns Hopkins University,
+Baltimore, MD, USA.
+3Center for Astrophysics | Harvard & Smithsonian, 60 Garden St,
+Cambridge, MA 02138, USA.
+4Lunar and Planetary Laboratory, University of Arizona, Tucson,
+AZ, 85721, USA.
+5University of Maryland, Baltimore County, MD 21250, USA.
+6NASA Goddard Space Flight Center, Greenbelt, MD 20771,
+USA.
+7Department of Astronomy, University of Michigan, Ann Arbor,
+MI, USA.
+8NHFP Sagan Fellow.
+9Department of Earth & Planetary Sciences, Johns Hopkins
+University, Baltimore, MD, USA.
+10Space Telescope Science Institute, Baltimore, MD 21218, USA.
+11Carnegie Earth & Planets Laboratory, Washington, DC, 20015,
+USA.
+12NASA Ames Research Center, Moffett Field, CA, USA.
+13Department of Physics, Imperial College London, Prince
+Consort Road, London, SW7 2AZ, UK.
+1
+arXiv:2301.04191v1  [astro-ph.EP]  10 Jan 2023
+
+Springer Nature 2021 LATEX template
+2
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+14Department of Physics, Utah Valley University, Orem, UT,
+84058 USA.
+15School of Physics, HH Wills Physics Laboratory, University of
+Bristol, Bristol, UK.
+*Corresponding author(s). E-mail(s):
+jacob.lustig-yaeger@jhuapl.edu; guangweifu@gmail.com;
+Abstract
+The critical first step in the search for life on exoplanets over the next
+decade [1, 2] is to determine whether rocky planets transiting small M-
+dwarf stars possess atmospheres [3, 4] and, if so, what processes sculpt
+them over time [5–7]. Because of its broad wavelength coverage and
+improved resolution compared to previous methods, spectroscopy with
+JWST offers a new capability to detect and characterize the atmo-
+spheres of Earth-sized, M-dwarf planets [8, 9]. Here we use JWST to
+independently validate the discovery of LHS 475b [10], a warm (586
+K), 0.99 Earth-radius exoplanet, interior to the habitable zone, and
+report a precise 2.9 − 5.3 µm transmission spectrum. With two transit
+observations, we rule out primordial hydrogen-dominated and cloudless
+pure methane atmospheres. Thus far, the featureless transmission spec-
+trum remains consistent with a planet that has a high-altitude cloud
+deck (similar to Venus), a tenuous atmosphere (similar to Mars), or no
+appreciable atmosphere at all (akin to Mercury). There are no signs
+of stellar contamination due to spots or faculae [11]. Our observations
+demonstrate that JWST has the requisite sensitivity to constrain the
+secondary atmospheres of terrestrial exoplanets with absorption fea-
+tures < 50 ppm, and that our current atmospheric constraints speak
+to the nature of the planet itself, rather than instrumental limits.
+Keywords: JWST, Terrestrial Exoplanet Atmospheres, Transmission
+Spectroscopy
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+3
+The search for atmospheres on rocky exoplanets has only just begun. Prior
+constraints on the presence of terrestrial exoplanet atmospheres using the Hub-
+ble Space Telescope (HST) and the Spitzer Space Telescope (Spitzer) have
+succeeded in ruling out primordial H2/He atmospheres [12–16] that would pro-
+duce large and detectable absorption features in a transmission spectrum; thick
+atmospheres that would produce shallow infrared secondary eclipse depths
+[17]; and a tentative detection of a terrestrial atmosphere [18] that remains
+controversial [19, 20]. JWST is expected to break new ground in the search
+for atmospheres on rocky exoplanets that transit nearby M dwarfs [9, 21].
+However, theoretical modeling work predicts a tumultuous stellar environment
+in these compact M-dwarf systems [22, 23] that raises the critical question
+of whether or not small, rocky exoplanets can maintain thick and detectable
+atmospheres in the face of significant atmospheric loss processes.
+We observed two transits of LHS 475b (previously the planet candidate
+TOI 910.01) on 31 August 2022 and 4 September 2022 with JWST’s Near
+InfraRed Spectrograph (NIRSpec) [24, 25] G395H instrument mode as part
+of the JWST Cycle 1 Guest Observing (GO) Program 1981 (PI: K. Steven-
+son). This mode covers wavelengths 2.87 − 5.27 µm and has a native spectral
+resolving power of R = λ/∆λ ≈ 2700. We used the Bright Object Time Series
+(BOTS) mode with the NRSRAPID readout pattern, S1600A1 slit, and the
+SUB2048 subarray. Each time-series observation lasted a total of 2.9 hours,
+which captured the 39.98 ± 4.04 minute transit that occurred during this
+window. This resulted in approximately 1.75 hours and 0.5 hours of stellar
+baseline before and after transit, respectively. The Methods contains additional
+information on the observations.
+We selected the LHS 475 system as one of several nearby M-dwarf systems
+with known or candidate rocky planets. Prior to validation, LHS 475b was
+classified as a planet candidate first identified in Sector 12 by the Transiting
+Exoplanet Survey Satellite (TESS) [26]. TESS observed subsequent transits of
+the planet in Sectors 13, 27, and 39. LHS 475b transits a 3300 K, 0.2789 R⊙
+M3.5V dwarf star on a 2.029-day orbital period [27]. This planet is likely to
+be tidally locked, with a permanent dayside facing its host star [28], and an
+equilibrium temperature of 586 K.
+We validated the discovery of LHS 475b by eliminating both instrumental
+and astrophysical false positives. JWST detected two transit signals at the
+predicted times that are consistent in depth and duration with the 45 TESS
+transits (978 ± 73 ppm, 42 ± 13 minutes). Archival DSS images from 1999
+rule out the possibility of a background transiting star-planet system or an
+eclipsing binary. LHS 475 is a high-proper-motion star (1.28 arcsec/year) and
+no flux sources were identified in the archival data along its path from 1999 to
+2022. See the Methods for more details about the archival imagery. In parallel
+with this work, Ment et al. (in prep) performed an independent validation of
+LHS 475b using ground-based follow-up observations.
+We reduced the JWST data using three independent pipelines—Eureka!
+[29], FIREFLy [30], and Tiberius [31–33]—that yielded consistent results
+
+Springer Nature 2021 LATEX template
+4
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+Fig. 1 White light curves from both LHS 475b visits using the FIREFLy reduction (see
+Methods). For each visit, we combined data from both the NRS1 and NRS2 detectors into
+a single white light curve and applied a vertical offset for clarity. A transit model and visit-
+long linear trend are sufficient to fit the raw white light curves (panel a). Residuals from the
+best fit (panel b) highlight a small, ∼15-minute ramp at the start of each visit. Residuals
+are shown on the same y-scale as panel a. Both histograms of the residuals (panel c) are
+Gaussian distributed.
+(within 1.1σ, see Methods for details on each analysis). For our final inter-
+pretation, we utilize results from the FIREFLy pipeline as it is the most
+representative of the three reductions. We generated white light curves across
+the full G395H wavelength range covered by the two detectors, NRS1 from
+2.884 - 3.720 µm and NRS2 from 3.820 - 5.177 µm. The planet transits are
+clearly visible in the raw white light curves (see Figure 1). We note the presence
+of a small ramp at the start of the observation; no additional structure is seen
+in the residuals. There is also no evidence of starspot crossings during the tran-
+sits. Our joint fit to the white light curves gives a planet-to-star radius ratio
+of Rp/Rs = 0.03257 ± 0.00014, a mid-transit time of T0 = 59822.8762593 ±
+0.000026 BMJDTDB, an orbital period of P = 2.029088 ± 0.000006 days, a
+ratio of the semi-major axis to the stellar radius of a/Rs = 15.87235 ± 0.472,
+and an inclination of i = 87.194◦ ± 1.39◦. Therefore, LHS 475b has a radius
+of Rp = 0.99 ± 0.05 R⊕ (6319 ± 318 km). Although LHS 475b’s mass has not
+been measured, assuming an interior composition that is consistent with the
+small, rocky M-dwarf exoplanet population [34], we estimate a planet mass of
+Mp = 0.914 ± 0.187 M⊕.
+We fitted the spectroscopic light curves at the detector’s pixel resolution
+to derive wavelength-dependent transit depths independently for the first and
+second visit. The orbital parameters were fixed to the values from the joint
+white light curve analysis, leaving the planet-to-star radius ratio, linear tem-
+poral slope, and a constant offset as free parameters. We adopted stellar limb
+darkening from a 3D stellar model grid [35]. We then performed a weighted
+average of spectra from the two visits and binned the combined native-pixel-
+resolution transit depths into 56 points (R ≈ 100). Our co-added and binned
+transmission spectrum is shown in Figure 2.
+
+Data + Model
+Residuals
+ offset
+1.002
+Visit 
++
+1.001
+relative flux
+1.000
+Visit 2
+0.999
+(a)
+(b)
+-2.0 -1.5 -1.0 -0.5 0.0
+0.5
+2.0
+-1.5-1.0
+-0.5
+0.0
+0.5
+time from mid-transit fhoursSpringer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+5
+Fig. 2
+Final, binned spectrum (black points) compared to models (coloured lines). Top:
+Our data strongly (> 10σ) rule out hydrogen-dominated atmospheres with compositions
+from 1× – 100× solar metallicity, with reduced-χ2s reported in the legend for each model.
+The blue shaded bar highlights the region detailed in the bottom panel. Bottom: Our data
+also rule out, though to lower (2–5σ) significance, high mean molecular weight compositions
+of 1000× solar metallicity or a pure methane atmosphere. We weakly disfavor a pure water
+atmosphere or an Earth composition atmosphere. The data are consistent with a pure carbon
+dioxide atmosphere or that of an airless body. Each model is plotted relative to the mean
+transit depth.
+The observed transmission spectrum is featureless. A flat line, representa-
+tive of an airless-body or high mean molecular weight (MMW) atmosphere,
+fitted to the binned data produces a reduced χ2 = 0.91. No evidence is seen for
+stellar contamination from unocculted cool spots or hot faculae on the stellar
+disk [e.g., 11, 15, see Methods]. Despite the featureless spectrum, the precision
+is sufficiently high to rule out (> 5σ) several archetypal atmospheric composi-
+tions, including primordial hydrogen-helium atmospheres with less than 100 ×
+solar metallicity, as well as pure CH4 atmospheres ≥ 1 bar. We can specifically
+rule out this pure CH4 atmospheres due to the low mass of the CH4 molecule
+and the presence of the strong 3.3 µm CH4 band in the G395H bandpass. Other
+
+Springer Nature 2021 LATEX template
+6
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+secondary atmospheres are more challenging to rule out and distinguish from
+one another, however. We only weakly disfavor (at ≳1σ; [36]) 1000 × solar
+metallicity, pure steam, or warm Earth-like atmospheric compositions. Both
+a pure ≥ 1 bar carbon dioxide atmosphere or no atmosphere are favored yet
+are statistically indistinguishable from each other. In the context of Solar Sys-
+tem terrestrial archetype atmospheres (see Methods Fig. 11), we also weakly
+disfavor (≳1σ) clear, warm Venus-like and Titan-like atmospheres. We cannot
+statistically distinguish between a thin Mars-like atmosphere, a hazy Titan-like
+atmosphere, and a cloudy Venus, which are all consistent with the data.
+Following previous analyses [37], we performed Bayesian retrievals to better
+explore the range of atmospheres that remain consistent with our spectro-
+scopic measurements. We assumed a five component atmospheric composition
+consisting of the four most common and spectroscopically active molecules
+(H2O, CO2, CH4, and CO) in the Solar System terrestrial atmospheres, plus
+an unspecified gas that constitutes the bulk atmospheric composition but is
+spectroscopically inactive at these wavelengths [e.g. 38]. We allow the mean
+molecular weight of the bulk gas to vary between 2.5 g/mol and 50 g/mol.
+Since a solid planetary surface and an optically thick gray cloud deck are
+indistinguishable in the transit spectrum, we fit for the apparent surface pres-
+sure (the pressure of an opaque surface above which the atmosphere extends).
+We marginalize over the aforementioned planet mass, which is assumed to be
+consistent with a rocky interior composition. The vertical extent of the atmo-
+sphere is dictated by the scale height, which is implicitly controlled by varying
+the atmospheric temperature, mean molecular weight, and planet gravity. See
+Figure 3 for the retrieval results summarizing the range of allowed atmo-
+spheres given our data and highlighting the degeneracies that persist among
+the remaining atmospheric possibilities.
+If the planet has an atmosphere, it is likely to be a high mean molecu-
+lar weight secondary atmosphere that is tenuous (Mars-like) or cloudy/hazy
+(Venus-like or Titan-like). Compact atmospheres with small scale heights are
+preferred across the full range of apparent surface pressures. High mean molec-
+ular weight atmospheres dominated by species heavier than 40 g/mol, like CO2
+or Argon, can be thicker while maintaining relatively flat spectra. Atmospheric
+characteristics that increase the scale height, including high temperatures and
+low mean molecular weight bulk atmospheric compositions, tend to be dis-
+favored, particularly for apparent surface pressures ≳10 mbar. Models with
+scale heights larger than 20 km strongly skew towards the low mean molecular
+weight atmospheres (µ < 10 g/mol), make up ∼50% of the lowest apparent
+surface pressure samples, and tend to have low abundances of all absorbing
+molecules. These extended atmospheres with low apparent surface pressures
+are unlikely to form clouds or hazes at such high altitudes and are the most sus-
+ceptible to atmospheric loss, making them less physically plausible scenarios.
+Although LHS 475 is typical of low-activity M dwarfs in the solar neighbor-
+hood [39], atmospheric escape processes are still a concern for a primordial
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+7
+Fig. 3 Retrieval results showing preferred atmospheric properties for models containing
+H2O, CO2, CH4, and CO, plus a variable bulk gas composition for LHS 475b given the trans-
+mission spectrum measurements. Darker color shading indicates higher relative posterior
+probability density as a function of the apparent surface pressure (P0), molecular weight (µ)
+of the bulk atmospheric composition (left), and isothermal scale height (H, right). Dashed
+contours denote the 1σ (white), 2σ (gray), and 3σ (black) Bayesian credible regions. The
+red arrow depicts how the Jeans escape flux depends on the scale height and emphasizes the
+region of the parameter space that is more susceptible to atmospheric escape. If the planet
+possesses an atmosphere with at least 1 ppm CO2 or CH4, then the models prefer high mean
+molecular weight, compact atmospheres (µ > 20 g/mol at 1.2σ; H < 25 km at 1.2σ) with
+low apparent surface pressures (P0 < 0.01 bar at 1.3σ; P0 < 1 bar at 2σ). These scenarios
+correspond to either a tenuous or cloudy secondary atmosphere.
+extended atmosphere, and if LHS 475 b is indeed airless, such processes would
+likely constitute the primary reason for this.
+Our two transit observations demonstrate that JWST has the sensitivity
+to detect and constrain the secondary atmospheres of terrestrial exoplanets,
+and therefore our atmospheric non-detection reflects the nature of the target
+itself. We place a 3σ constraint on the maximum size of absorption features
+in our spectrum at 61 ppm for H2O at 2.8 µm, 38 ppm for CH4 at 3.3 µm,
+49 ppm for CO2 at 4.3 µm, and 62 ppm for CO at 4.6 µm. These constraints
+demonstrate JWST’s sensitivity to absorption features smaller than 50 ppm
+for an Earth-sized exoplanet. We find no indication of a noise floor down to
+5 ppm (See Methods Figure 8). These are critical benchmarks for forthcom-
+ing rocky exoplanet observations with JWST. Furthermore, our non-detection
+of starspot crossings during transit and the lack of stellar contamination in
+the transmission spectrum are promising signs in this initial reconnaissance
+of LHS 475b. These findings indicate that additional transit observations of
+LHS 475b with JWST are likely to tighten the constraints on a possible atmo-
+sphere. A third transit of LHS 475b is scheduled as part of this program (GO
+1981) in 2023. An alternative path to break the degeneracy between a cloudy
+planet and an airless body is to obtain thermal emission measurements of
+LHS 475b during secondary eclipse because an airless body is expected to be
+several hundred Kelvin hotter than a cloudy world and will therefore produce
+
+10-6
+Titan (haze-top)
+increasing
+atmospheric
+10
+escape
+)-4
+Venus (cloud-top)
+10
+100
+Farth (clear)
+Titan (clear)
+O
+a
+Venus (clear)
+10
+20
+30
+40
+0
+20
+40
+60
+80
+atmospheric mmw [g/mol]
+scale height [km]Springer Nature 2021 LATEX template
+8
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+large and detectable eclipse depths at JWST’s MIRI wavelengths [4, 40]. Our
+findings only skim the surface of what is possible with JWST.
+Acknowledgements
+This work is based in part on observations made with the NASA/ESA/CSA
+JWST. The data were obtained from the Mikulski Archive for Space Telescopes
+at the Space Telescope Science Institute, which is operated by the Association
+of Universities for Research in Astronomy, Inc., under NASA contract NAS
+5-03127 for JWST. These observations are associated with program #1981.
+Support for program #1981 was provided by NASA through a grant from
+the Space Telescope Science Institute, which is operated by the Association
+of Universities for Research in Astronomy, Inc., under NASA contract NAS
+5-03127.
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+9
+Fig. 4
+2D light curves of LHS 475b as a function of time and wavelength for the first
+visit, measured with NIRSpec/G395H. The horizontal stripe down the middle of each panel
+corresponds to the gap between the NRS1 and NRS2 detectors. Left: data normalized by
+the median stellar spectrum. Middle: Maximum probability transit models. Right: Residuals
+from the model fit. Note, the Eureka! and FIREFLy reductions trim more blue columns from
+NRS1 where there is minimal throughput than the Tiberius pipeline, which accounts for the
+regions without data in those reductions. Similarly, the Eureka! reduction also trims off the
+initial ramp that can be seen in Figure 1.
+Methods.
+1 Data Analysis
+1.1 Observations
+We observed two transits of LHS 475b with the NIRSpec G395H grating
+covering the 2.87–5.14 µm wavelength range split over the NRS1 and NRS2
+detectors, with a detector gap between 3.72 and 3.82 µm. The first transit was
+observed on the 31 August 2022 18:48 UTC and the second on 4 September
+2022 20:09 UTC. Each visit lasted 4.4 hours in total with 2.9 hours of expo-
+sure time. Both transits were executed with the same observing settings, using
+the Bright Object Time Series (BOTS) mode with the NRSRAPID readout
+pattern, S1600A1 slit, and the SUB2048 subarray from NIRSpec. We obtained
+a total of 1158 integrations per visit, with 9 groups per integration and 0.902
+seconds per group.
+We extracted and analyzed the data from each visit independently with the
+Eureka!, FIREFLy and Tiberius pipelines as described below. 2D lightcurves,
+models, and residuals from the three reductions are shown in Figure 4.
+
+Data
+Model
+Residuals
+0.0015
+Eureka!
+4.5
+4.0
+0.0010
+3.5
+3.0 -
++
+0.0005
+5.0
+FIREFLY
+wavelength
+residuals
+4.0
++ 0.0000
+3.5
+3.0
++-0.0005
+5.0
+Tiberius
+4.5
+4.0
+-0.0010
+3.5
+3.0
+-0.0015
+-2.0 -1.5 -1.0 -0.5 0.0 0.5-2.0 -1.5 -1.0 -0.5 0.0 0.5-2.0 -1.5 -1.0 -0.5 0.0 0.5
+time from mid-transit [hours]Springer Nature 2021 LATEX template
+10
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+1.2 Spectral Extraction
+1.2.1 Eureka!
+Eureka! [29] is an end-to-end analysis pipeline for time series observations
+(TSOs) of exoplanets. Eureka! serves as a wrapper for stages 1 and 2 of the
+jwst pipeline [41], allowing the user to specify which steps are run in addition
+to custom modules. In later stages, Eureka! performs spectroscopic extraction,
+light curve generation, and light curve fitting.
+In this work, we apply Eureka!’s custom group-level background subtrac-
+tion (GLBS) in stage 1 prior to ramp fitting to remove 1/f noise which has
+been found to impact the accuracy of ramp fits for data with a small numbers
+of groups up the ramp [30, 42]. Due to G395H’s curved trace we first identify
+the center of the trace, then mask all pixels within an aperture of 8 pixels. All
+remaining pixels in a given column (cross-dispersion direction) were used to
+calculate a median background/noise level for that column. We skip the jump
+step detection, otherwise running all standard stage 1 steps for TSOs.
+In stage 2, we skip the flat field step (at the time of writing, only pre-flight
+flat fields were available, which are insufficient for the precision we require
+and adds significant noise to the data) and the photom step. Because we are
+interested in relative flux measurements, we do not require the absolute flux
+calibration provided by these two steps.
+A second round of background subtraction is done in stage 3 to capture
+any remaining background or 1/f noise, using pixels more than 9 pixels away
+from the center of the trace. The spectrum is extracted with an aperture of 5
+pixels for NRS1 and 4 pixels for NRS2 using median frame optimal spectral
+extraction. To convert from DN/s to electrons, we apply a median of the gain
+files. At the time of writing only pre-flight gain files were available, which are
+insufficient for the precision we require and adds significant noise to the data
+if applied on a per-pixel basis. For NRS1 we extract only columns 800 − 2047
+due to the negligible throughput outside of that region of the detector. For
+NRS2 we extract the full dispersion direction, but note that the edges are less
+reliable due to the trace approaching the top or bottom of the subarray.
+White light curves are generated across the full wavelength range of the
+extracted data: 2.884 - 3.720 µm for NRS1 and 3.820 - 5.177 µm for NRS2.
+For transit 1 we reach a white light precision of 112 ppm and 162 ppm for
+NRS1 and NRS2, respectively. For transit 2 we reach a white light precision
+of 116 ppm and 149 ppm for NRS1 and NRS2, respectively. For each transit,
+NRS1 and NRS2 are combined into a single white light curve prior to light
+curve fitting. We extract spectroscopic light curves at the pixel-resolution fol-
+lowing recommendations from [43], however we find that our GLBS routine
+sufficiently removes the 1/f noise in our data set, with no improvement on the
+final transmission spectrum precision between fitting light curves at the native
+pixel resolution and then binning, or binning prior to fitting (see Section 1.3.1).
+Figure 5 shows our spectroscopic precision compared to expected noise lev-
+els. Bad columns are denoted by squares (flagged in both transits) or darker
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+11
+Fig. 5 Eureka! spectrophotometric precision at the native pixel resolution, compared to
+expected noise levels for both events. The expected noise level, as well as 1.25× and 2× the
+expected noise are shown as grey lines, these have been smoothed to the resolution of the
+final transit spectrum for visualization purposes. Squares denote columns which are greater
+than 1.5× the expected noise level in both transits, dark blue circles denote columns which
+are greater than 1.5× the expected noise level in only one transit. These columns are flagged
+and not used to generate the final transmission spectrum.
+circles (flagged in only one transit). This corresponds to 1.13% and 1.56% of
+columns in transit 1 NRS1 and NRS2, respectively, and 1.05% and 2.10% of
+columns in transit 2 NRS1 and NRS2, respectively. Excluding these columns,
+for transit 1 we achieve a median precision of 1.19× and 1.23× the expected
+noise level for NRS1 and NRS2, respectively, while for transit 2 we achieve
+1.19× and 1.24× the expected noise level for NRS1 and NRS2, respectively.
+1.2.2 FIREFLy
+We used the FIREFLy [Fast InfraRed Exoplanet Fitting for Lightcurves, 30, 44]
+to analyse the JWST data. We started with the uncal.fits files and ran the
+jwst pipeline for stage 1 and 2 with modified steps including group-level 1/f
+and background subtraction and skipping the jump-step. Both changes were
+shown to decrease the scattering in the extracted lightcurves. After obtaining
+the rateints.fits files from the stage 2 output, we performed custom cosmic
+rays and bad/hot pixels corrections. The spectral traces are then masked in
+the cleaned 2D images before applying 1/f correction, which subtracts the
+median value of the unmasked background pixels at each column. Next, we
+measured the shifts of the spectral trace in x and y directions by using cross
+correlation in the selected 2D spectral region. The measured shifts are less
+than one hundredth of a pixel which illustrates the excellent pointing stability
+
+10000+
+Transit 1
+NRS1
+NRS2
+9000
+Native Pixel Resolution
+[wdd]
+8000
+7000
+precision [
+6000
+2x Expected Limit
+5000
+4000
+3000
+2000
+Expected Precision Limit
+10000
+Transit 2
+NRS1
+NRS2
+9000
+Native Pixel Resolution
+precision [ppm]
+8000
+7000
+6000
+ 2x Expected Limit
+5000
+4000
+3000
+Expected Precision Limit
+2000
+3.0
+3.2
+3.4
+3.8
+4.0
+4.2
+4.4
+4.6
+5.0
+3.6
+4.8
+5.2
+wavelength [um]Springer Nature 2021 LATEX template
+12
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+of JWST. After aligning each 2D spectrum, we determine the spectral trace by
+first cross correlating a Gaussian profile at each column to obtain the spectrum
+location in the y direction, and then fit a 4th order polynomial as a function of
+the x direction. The spectrum is then extracted for each integration centered
+at the fitted spectral trace to form the light curves.
+1.2.3 Tiberius
+The Tiberius pipeline is a spectral extraction and light-curve fitting code based
+on the LRG-BEASTS pipeline [31–33]. We used Tiberius on the Eureka! stage
+1 group-level background-subtracted product, which had 1/f noise removed,
+to produce white and spectroscopic transit light curves. First we created bad-
+pixel masks for NRS1 and NRS2 by manually selecting hot pixels in the data.
+These hot pixels were combined with all pixels flagged as 3σ outliers from the
+background, and were interpolated over using their nearest neighboring pixels.
+We also interpolate the spatial dimension of the data on a 10x grid, which
+improves flux extraction at the sub-pixel level, reducing noise. The spectra
+were then traced by fitting Gaussian functions for each column of the detectors,
+and then using a running median to smooth the trace centers. These centers
+were fit with a 4th-order polynomial, 3σ outliers were removed, and the centers
+were again refit with a 4th-order polynomial.
+In addition to the background subtraction already performed in the cre-
+ation of the stage 1 product, we perform an additional background subtraction
+step here to remove residual background light or remaining 1/f noise. We
+mask from the detector a defined aperture of 4 pixels plus 6 more pixels off-
+set from it, and clipped 3σ outliers in the background pixels, with respect to
+their specific column and frame. Finally, the background signal for each col-
+umn was subtracted from it, and the spectra were then extracted using a 4
+pixel aperture.
+1.3 Light Curve Fitting
+1.3.1 Eureka!
+We perform a joint fit on both white light curves to constrain the system
+parameters. Limb darkening is calculated with the ExoTic-LD pacakge [45–47]
+using a quadratic limb darkening [48, 49] and the 3D stellar grid from [35].
+Stellar parameters are adopted from [35], assuming Teff = 3312 K, log(g) =
+4.94, Fe/H = 0.0. For all light curve fits both limb darkening parameters are
+held constant. We find that the uncertainty induced in the light curve fits by
+the stellar models is smaller than the uncertainty in individual transit depths,
+with consistent transit spectra regardless of free or fixed limb darkening. We
+trim the first 150 integrations prior to light curve fitting to remove a slight
+ramp at the beginning of the data, which can be seen in Figure 1.
+For all light curve fitting we consider a transit model [batman, 50] and a
+linear ramp in time. We use emcee [51], running each chain to at least 10×
+the auto-correlation time. The joint white light curve fit includes the planet
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+13
+Fig. 6 Comparison of uncertainty on planet radius derived from light curves fit at the native
+pixel resolution and fitting of pre-binned light curves. The y-axis is in parts per thousand. We
+find little to no difference in the uncertainty, suggesting that our 1/f correction is sufficient
+to address the column-column variances.
+radius, orbital period, center of transit, inclination, and scaled semi-major
+axis as shared parameters, and independent temporal ramps for each white
+light curve. Best fit orbital parameters are given in Table 1. The Eureka!
+spectroscopic fits adopt the Eureka! white light best-fit orbital parameters
+and only fit for planet radius and the linear temporal ramp. Following [43] we
+extract and fit our light curves at the native pixel resolution of the detectors,
+and later bin the data to our preferred resolution.
+To test the robustness of our group-level 1/f noise correction, we also fit
+a set of pre-binned light curves and compare the resulting uncertainty on the
+planet radius. Figure 6 shows our uncertainty on planet radius for transit 1 for
+both the native pixel resolution light curve fitting, and our pre-binned light
+curve fitting. We find no significant improvement by fitting the full resolution
+light curves, suggesting the 1/f noise has been sufficiently removed. We suggest
+that this test should be run on all NIRSpec G395H TSOs to ensure that one
+has sufficiently removed the 1/f noise.
+1.3.2 FIREFLy
+The extracted light curves are first summed in the wavelength direction includ-
+ing both NRS1 and NRS2 to form the whitelight light curve for each visit. We
+then used batman [50] and emcee [51] to joint fit the whitelight lightcurves
+from the two visits with six free parameters including Rplanet/Rstar, a/Rstar,
+orbital inclination, mid-transit time for both visits, and linear temporal slope
+for both visits. The best-fit joint white light orbital parameters are listed in
+Table 1. We fixed the limb darkening to the quadratic coefficients from the 3D
+stellar model in the Stagger-grid [35] interpolated at Fe/H=0, Teff=3312K
+and log(g)=4.94.
+The orbital parameters and quadratic limb darkening coefficients are
+then fixed to fit the lightcurve from each wavelength column. We used the
+scipy.optimize.curvefit function with three free parameters including
+linear temporal slope, constant offset and Rplanet/Rstar.
+
+Transit 1
+Native Pixel Light Curve Fitting
+Pre-binned Light Curve Fitting
+O
+NRS1
+● NRS2
+3.0
+3.2
+3.4
+3.6
+3.8
+4.0
+4.2
+4.4
+4.6
+4.8
+5.0
+5.2
+wavelength [um]Springer Nature 2021 LATEX template
+14
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+Parameter
+Eureka!
+FIREFLy
+Tiberius
+Rp/Rs
+[unitless]
+0.032756
++1.44×10−4
+−1.44×10−4
+0.03257
++1.40×10−4
+−1.43×10−4
+0.032226
++4.86×10−4
+−4.86×10−4
+T0
+[BMJDT DB]
+59822.8762805
++2.92×10−5
+−2.91×10−5
+59822.8762593
++2.62×10−5
+−2.62×10−5
+59822.8763396
++5.85×10−5
+−5.85×10−5
+Period
+[days]
+2.02908843
++5.65×10−6
+−5.66×10−6
+2.0290882
+(Fixed)
+2.02909
+(Fixed)
+a/Rs
+[unitless]
+15.223
++4.62×10−1
+−4.37×10−1
+15.87235
++4.88×10−1
+−4.56×10−1
+18.161
++1.79
+−1.79
+i
+[degrees]
+86.991
++1.41×10−1
+−1.39×10−1
+87.194
++1.41×10−1
+−1.37×10−1
+88.237
++4.80×10−1
+−4.80×10−1
+Table 1 Best fit orbital parameters from white light curve fitting. We adopt the FIREFLy
+results as our system parameters. Eureka! and FIREFLy values are derived from joint fits to
+both white light curves. Tiberius parameters are derived from a weighted mean of fits to
+individual light curves.
+1.3.3 Tiberius
+We extracted a white light curve for each detector (NRS1 and NRS2), for
+each transit. These white light curves were fit independently using a Lev-
+enberg–Marquardt damped least squares routine with the Tiberius pipeline.
+Limb darkening parameters were obtained with LDTK [52, 53] from assumed
+stellar parameters of Teff = 3312 K, log(g) = 4.94, Fe/H = 0.0, and a quadratic
+limb darkening law was used. The results of the white light curve fits were
+used to fix the transit parameters for the spectroscopic light curve fits, which
+were performed at pixel-level resolution using the same damped least squares
+routine. Since the white light curves were fit independently, the best-fit param-
+eters in Table 1 were obtained from a weighted average of the results of each
+of the four white light curve fits (weighted by flux received on each detector).
+1.4 Final Transmission Spectrum
+All three independently reduced spectra from above are in agreement, showing
+no atmospheric features and being statistically consistent with a flat line. The
+findings reported in the study do not depend upon which reduction pipeline
+is used. To select the final transmission spectrum for model interpretation, we
+performed two tests. The first test computed the mean absolute deviation of
+each spectrum relative to the averaged spectrum of the three reductions. The
+purpose of this test was to identify the reduction that is the most representative
+of the three reductions. The FIREFLy reduction was favored by this test. The
+second test computed the reduced chi-squared relative to a flat line. This
+test was meant to validate the size of the error bars. The unbinned FIREFLy
+transmission spectrum had a reduced chi-squared of 1.015.
+1.5 Planet Validation
+The JWST detection of a transit at the same period, phase, and depth as the
+TESS TOI eliminates the possibility of a TESS false positive due to a telescope
+or instrument systematic effect. This leaves only astrophysical sources, such
+as a background eclipsing binary, as the remaining false positive mechanism.
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+15
+Fig. 7 A 3.36” × 3.36” DSS image centered on LHS 475 taken 1999 June 20. The red
+circle depicts the star’s J2000 position per Simbad, whereas the blue circle indicates the
+star’s position for the JWST observations in September of 2022. We see no indication of a
+background star at the 2022 position that could be the source of the observed transit signal.
+For reference, NIRSpec’s field of view is 1.6×1.6 pixels on this image.
+Using an archival DSS image of LHS 475, we leverage the star’s high
+proper motion to rule out astrophysical false positives. The star moves 1.28
+arcsec/year [54, 0.3423 arcsec/year in RA, −1.2303 arcsec/year in Dec;], which
+corresponds to ∼29 pixels in Figure 7 from the June 1999 DSS image to our
+Sep 2022 JWST observation. The lack of measurable flux at LHS 475’s 2022
+position enables us to rule out all scenarios involving transits within a poten-
+tial background system. Finally, we rule our a stellar binary companion due to
+the precisely measured Gaia DR3 parallax of 80.1134 mas, which corresponds
+to a distance of only 12.5 pc.
+1.6 Implications for JWST/NIRSpec Noise Floor
+In the interest of exploring the effects of correlated noise and constraining the
+instrument noise floor, we concatenate residuals from both visits and com-
+pute Allan variance plots for the white and spectroscopic light curve fits (see
+Figure 8). Using the Eureka! white light curve data, we find no indication of a
+noise floor down to 5 ppm; however, we identify correlated noise at timescales
+of < 5 minutes. This timescale is consistent with the thermal cycling of heaters
+in the ISIM Electronics Compartment, which induces small forces on the tele-
+scopes backplane structure [55]. The effect is semi-periodic, the result of several
+heaters cycling at different frequencies.
+
+200
+20000
+175 -
+17500
+150 
+15000
+125
+12500
+ Pixel Number
+2000
+10000
+100
+2022
+7500
+75 -
+5000
+50 
+2500
+25 
+0
+ 0
+0
+25
+50
+75
+100
+125
+150
+175
+200
+Pixel NumberSpringer Nature 2021 LATEX template
+16
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+Fig. 8 Allan variance plots from the white and spectroscopic light curve fits. Panel (a) illus-
+trates that the white light curve residuals from two of the analyses exhibit some correlated
+noise at timescales of < 5 minutes (< 35 integrations). This is likely due to uncorrected 1/f
+noise from the thermal cycling of on-board heaters [55, Section 4.5.3]. At longer timescales
+(> 18 minutes), the Eureka! pipeline returns to the expected standard error with RMS val-
+ues below 10 ppm. The Tiberius reduction did not sum the flux across both detectors and
+was not used for this noise floor analysis. The spectroscopic RMS values in panels (b) – (d)
+are more consistent with the standard error, thus confirming that the spectroscopic light
+curves are dominated by white noise.
+2 Modeling
+With the reduced data and coadded transmission spectrum produced in the
+previous section, we now use a variety of models to update the state of knowl-
+edge on the LHS 475 system. We use archival photometry to update the
+LHS 475 stellar parameters and assess the impact of stellar contamination on
+the JWST transmission spectrum; we use empirical mass-radius relations to
+estimate the planet mass given our precise radius measurement; and we fit
+atmospheric models to the transmission spectrum to obtain constraints on the
+possible atmospheric composition of LHS 475b.
+
+100
+Normalized RMS
+10
+Eureka! Median RMS
+Std. Err. (1/V N)
+10-2
+100
+101
+102
+Bin Size [Number of Integrations]100
+Normalized RMS
+10
+Tiberius Median RMS
+Std. Err. (1/V N)
+10-2
+100
+101
+102
+Bin Size [Number of Integrations]102
+RMS [ppm]
+101
+ppm
+Firefly RMS
+Std. Err. (1/VN)
+Eureka! RMS
+Std. Err. (1/VN)
+100
+100
+101
+102
+Bin Size [Number of Integrations]100
+Normalized RMS
+10
+Firefly Median RMS
+Std. Err. (1/V N)
+10-2
+100
+101
+102
+Bin Size [Number of Integrations]Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+17
+2.1 Stellar Modeling and Transit Light Source
+Contamination
+We use PHOENIX spectra guided by archival photometry1 from the VizieR Pho-
+tometry Viewer2 to improve constraints on the stellar parameters. Effective
+temperature (Teff) is a primary driver of spectral shape and so we are able to
+refine estimates by matching models to the observations at visible and near-
+IR wavelengths. To do this, we computed a grid of synthetic spectra following
+similar procedures to those outlined in [53] with Teff = 3200 – 3400 K (∆T
+= 10 K), log(g) = 4.5 – 5.2 dex (∆log(g) = 0.1 dex), and M⋆ = 0.262 M⊙.
+This parameter space was chosen by expanding around the stellar parameters
+published in the Tess Input Catalog [27]. For each model, we computed syn-
+thetic visible and near-IR photometry over the same wavelengths as the filter
+profiles for available measurements for LHS 475 and used a reduced χ2 test to
+identify the model that most closely matched the observations. The reduced
+χ2 test was conducted with both the observations and models normalized to
+the 2MASS J band flux density value to isolate matching the spectral shape.
+The fully explored grid yielded χ2
+ν values between 6.8 – 987.2, with 30 mod-
+els returning similar values less than 50 (Figure 9). These models have Teff =
+3300 (+80, -30) K, log(g) = 5.2 ± 0.5 g/cm3, and M⋆ = 0.262 M⊙. To deter-
+mine the radius of the star we scaled all models with χ2
+ν < 50 by R2
+⋆/dist2
+until FJ2MASS,mod = FJ2MASS,obs,
+R⋆ =
+�
+(FJ2MASS,obs/FJ2MASS,mod) × dist2
+(1)
+We adopted the Gaia EDR3 distance of 12.481 ± 0.0065 pc [54], which
+returned a radius of 0.2789 ± 0.0014 R⊙.
+LHS 475 is typical of low-activity M dwarfs in the solar neighborhood.
+TESS only detected two flares on LHS 475, both with energy below 1031 erg.
+The inferred flare rate and other activity diagnostics are all consistent with the
+general population of relatively inactive M dwarfs in a volume-limited sample
+[39]. Hα and He I D3 are both in absorption, not emission. Ca II 8542 is
+relatively deep.
+Fitting models of the Transit Light Source (TLS) effect to the observed and
+coadded transmission spectrum allows us to assess the degree to which stellar
+contamination may impact and/or explain any characteristics of the planet’s
+transmission spectrum. The TLS effect can impart slopes and features into
+the transmission spectrum due to differences in the spot or faculae coverage
+along the planet’s transit chord relative to the average coverage across the
+visible stellar disk [11]. Following the formalism of [15], we calculate the TLS
+1For NIRSpec observations, the jwst pipeline requires the flat field step be run for absolute flux
+calibration. At the time of writing, only ground or dummy frames were available for the three
+types of NIRSpec flat fields and for the correction applied in the photom step of the jwst Stage 2
+pipeline. These ground and dummy frames do not provide high accuracy absolute flux calibration,
+so we choose to not use our new data for Stellar Modeling at this time.
+2http://vizier.cds.unistra.fr/vizier/sed/
+
+Springer Nature 2021 LATEX template
+18
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+Fig. 9 Comparison of our 30 closest matching PHOENIX models (χ2
+ν < 50) to all available
+archival photometry of LHS 475 from the VizieR Photometry Viewer. These models have
+Teff = 3380 – 3320 K, log(g) = 4.7 – 5.7 g/cm2, M = 0.262 M⊙.
+contamination spectrum
+ϵλ = (1 − fspot − ffac)Sλ,phot + fspotSλ,spot + ffacSλ,fac
+(1 − Fspot − Ffac)Sλ,phot + FspotSλ,spot + FfacSλ,fac
+(2)
+where Sλ,phot, Sλ,spot, and Sλ,fac refer to the spectrum of the stellar photo-
+sphere, spots, and faculae, respectively, fspot and ffac refer to the spot and
+faculae projected area covering fractions along the transit chord, and similarly
+Fspot and Ffac refer to the spot and faculae projected area covering fractions
+across the entire visible stellar disk. Thus, ϵλ is the ratio of the stellar spec-
+trum along the transit chord to the spectrum of the whole disk, and a general
+model for how the TLS effect contaminates the observed transmission spec-
+trum. Given Equation 2 the observed drop in flux that we refer to as the
+transmission spectrum is simply
+∆Fλ,obs = ϵλ
+�Rp
+Rs
+�2
+λ
+(3)
+where the TLS contamination spectrum is multiplied by the wavelength-
+dependent “true” planet transmission spectrum. We use the Dynesty nested
+sampling code [56] to infer posterior distributions for the TLS contamination
+model parameters under the assumption of a wavelength independent planet
+transmission spectrum. We run the standard nested sampling algorithm [57]
+
+PHOENIX Models with x<50
+1.2
+LHS 475 Observations
+1.0
+0.8
+0.6
+0.4
+0.2
+0.0
+5000
+10000
+15000
+20000
+25000
+30000
+Wavelength (A)Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+19
+Fig. 10 Corner plot comparing the prior (orange) and posterior (dark blue) PDFs for
+a subset of the fitting parameters in the TLS contamination retrieval. The flat spectrum
+reveals a consistent spot (and faculae) coverage along the transit chord compared to the full
+stellar disk.
+with 1000 live points until the estimated contribution to the total evidence
+from the remaining prior volume drops below the threshold of dlogz=0.075.
+In general, no evidence of TLS contamination is observed in the flat
+transmission spectrum and the TLS model readily reproduces the featureless
+spectrum. Figure 10 compares the prior and posterior probability distributions
+for a subset of the TLS model parameters. The inferred posterior distribution
+for the TLS contamination model generally reproduce the prior distributions,
+with the exception of the covariance between the spot (faculae) area cover-
+ing fraction along the transit chord compared to the spot (faculae) covering
+fraction on the full disk. These two convariance are constrained along a line
+
+disk spot
+-0.15
+Posterior PDF
+Prior PDF
+disk faculae
+-0.19
+0.8
+disk faculae
+fraction
+0.6
+chord spot
+0.2
+chord spot
+fraction
+chord faculae
+0.2
+-0.21
+chord faculae
+fraction
+0.6
+disk spot
+disk faculae
+chord spot
+chord faculae
+fraction
+fraction
+fraction
+fractionSpringer Nature 2021 LATEX template
+20
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+with a slope of approximately unity, such that the ratio of spot (faculae) cov-
+ering fraction on the full stellar disk to spot (faculae) covering fraction along
+the transit chord is 1.005 ± 0.003 (0.948 ± 0.006). This implies that—although
+the exact area covered by spots (and faculae) is not well constrained—at the
+observed precision there is no evidence of differing spot (or faculae) cover-
+age along the transit chord compared to the average stellar disk. We repeated
+the same TLS contamination retrieval with the addition of the transit depth
+measured by TESS in the optical (978±73 ppm) and obtained the same result.
+2.2 Planet Radius, Mass, and Equilibrium Temperature
+From the constraint on the white light curve transit depth (1060 ± 9 ppm)
+and the stellar radius (Rs = 0.279 ± 0.014 R⊙), we calculate the planet radius
+to be Rp = 0.991 ± 0.050 R⊕ (6319 ± 318 km). The 5% radius precision is
+dominated by uncertainty in the stellar radius. For reference, the preexisting
+radius constraint from TESS sectors 12-39 was 0.93 ± 0.70 R⊕ [10].
+Despite the lack of a mass measurement for LHS 475b, we use three different
+methods to estimate the mass: 1) from the transmission spectrum [13], 2) from
+probabilistic mass-radius-relation [58], and 3) from probabilistic bulk density
+arguments. We use atmospheric models over a range of masses compared to
+the spectroscopic data from NIRSpec/G395H to infer conservative upper and
+lower limits of the possible mass for LHS 475b. To do so, we employ the
+forward model framework discussed in the following section. First, we find the
+uppermost mass limit by finding the densest planet that could stably support
+a hydrogen-helium envelope and fit the data. To obtain a reduced-χ2 ≤ 1, we
+determine that we must consider a mass of 24 M⊕. Combined with the precise
+radius constraint, this upper limit mass results in a planetary density of 119
+g/cm−3, or 6× that of pure uranium. Given this unrealistic density, we can
+clearly reject a hydrogen-helium atmosphere around a very dense planet. On
+the other hand, to find the lowest mass that is consistent with the NIRSpec
+data, we instead consider a planet with a very high mean molecular weight
+atmosphere, but from a reasonably abundant molecule – that of pure CO2
+– and scale the mass down until we obtain a reduced-χ2 ≤ 1. Under this
+atmospheric assumption, we find that masses consistent with the data extend
+down to 0.78 M⊕. Together this method gives us a range of masses consistent
+with the observed atmosphere between 0.78 - 24 M⊕.
+Next, we use the mass-radius relationship gleaned from the existing pop-
+ulation of small M dwarf exoplanets to estimate the planet’s mass given our
+precise radius constraint. Using the Forcaster code’s probabilistic mass-radius
+relationship and mass prediction tool [58], we estimate the mass of LHS 475b
+to be Mp = 0.980+0.632
+−0.359 M⊕.
+Our third mass estimate leverages recent results on the interior bulk densi-
+ties among the M dwarf small planet population. Given the radius constraint
+for LHS 475b, the planet is consistent with the population of M dwarf plan-
+ets having rocky interior compositions (1.21 ± 0.28 R⊕) [34]. Therefore, if we
+assume that LHS 475b is indeed a rocky planet with a mean bulk density
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+21
+consistent with the M dwarf rocky planet population (0.94 ± 0.13 ρ⊕) [34],
+then we find the planet mass to be Mp = 0.914 ± 0.187 M⊕. If we consider
+that instead the planet were in the population of lower density water worlds
+(with 50% water, 50% rock interiors), then this would ultimately have ram-
+ifications for the scale height and water content of the atmosphere [e.g., 59],
+that are inconsistent with the featureless transmission spectrum that we mea-
+sured. Therefore, it is likely that LHS 475b has a mass that is consistent with
+a rocky mean bulk density. In the atmospheric models that follow, we assume
+the planet is consistent with the population with rocky interiors and use the
+corresponding mass Mp = 0.914 ± 0.187 M⊕, which is consistent with our
+previous estimates, albeit with a tighter constraint.
+We update LHS 475b’s zero bond albedo equilibrium temperature to
+586 ± 12 K (assuming uniform heat redistribution). In the limit of instant
+re-radiation expected from a planet with a tenuous or nonexistent atmo-
+sphere, the estimated day side brightness temperature is 748 ± 16 K. These
+updates may aid in the planning of any future secondary eclipse observations
+of LHS 475b.
+2.3 Atmospheric Modeling
+We use atmospheric radiative transfer models to simulate the transmission
+spectrum of LHS 475b for comparison with our JWST observations. In the next
+section, forward models of single-composition end-member atmospheres and
+archetypal atmospheres are used to illustrate the atmospheric compositions
+that are consistent with our observed data. Then, retrieval models are used
+to simulate a broad range of atmospheric compositions to place constraints
+on key atmospheric parameters given the precise, yet featureless transmission
+spectrum.
+2.3.1 Forward Modeling
+We use the forward modeling capabilities of two different open-source atmo-
+spheric radiative transfer codes, PICASO [60] and CHIMERA [61, 62], to explore
+the plausibility of various atmospheric archetypes. We compute each model
+atmosphere for a planet mass consistent with a rocky mean bulk density,
+Mp = 0.914 M⊕, a planetary radius of Rp = 0.991 R⊕, and a stellar radius
+Rs = 0.279 R⊙, and a planetary equilibrium temperature of Teq = 600 K,
+as above. In each case, we compare the modeled transmission spectrum to
+the NIRSpec/G395H data for LHS 475b from 2.9 – 5.3 µm and compute the
+reduced-χ2 between the modeled spectrum and the data.
+For the CHIMERA models, we compute chemically consistent atmospheric
+mixing ratios for 1×, 10×, 100×, and 1000× solar metalicities, with a solar
+C/O ratio. CHIMERA uses a preset grid of atmospheric molecular abundances
+along temperature-pressure profiles, metallicity, and C/O ratio generated from
+the NASA CEA code [63]. For the temperature-pressure profile, the code uses
+the five-parameter, double gray, one-dimensional parametrization of [64], where
+
+Springer Nature 2021 LATEX template
+22
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+we input a planetary equilibrium temperature of 600 K. For these CHIMERA
+models, we include opacity from H2O, CH4, CO, CO2, NH3, N2, HCN, H2S,
+H2/He CIA [65, 66], and Rayleigh scattering from H2. We consider simplistic
+cloudy hydrogen-dominated atmospheric models with CHIMERA by computing
+a cloud-top pressure for a grey absorbing cloud. We generate atmospheric
+transmission models with the correlated-k method of radiative transfer and
+bin the resulting model to the data before calculating our reduced-χ2.
+For the PICASO models, we generate simplified end-member atmospheric
+compositions with isothermal temperature-pressure profiles. We set a pressure
+grid which ranges from 1 µbar to 100 bar, and then set an isothermic tem-
+perature at the equilibrium temperature of 600 K. For the models shown in
+Figure 2, each atmosphere consists solely of either H2O, CO2, CH4, or as in
+the case of the Earth-like atmosphere, follows the atmospheric abundances of
+Earth above the water cold-trap, with 78% N2, 21% O2, 0.9% Ar, 416 ppm
+CO2, 524 ppm He, and 187 ppm CH4. For the models shown in Figure 11,
+we generate individual pressure grids with an upper bound according to the
+terrestrial body’s surface pressure (e.g., the Earth-like model has an upper
+atmospheric pressure bound of 1 bar; the Venus-like model has an upper pres-
+sure bound of 90 bar). We assume isothermal temperature profiles (at 600 K)
+with atmospheric abundances fixed to the composition of each Solar System
+body above any cold trap. For the cloudy Venus and hazy Titan cases, we
+implement a simple grey absorbing cloud at the pressure level according to the
+Venus cloud-top (1 mbar) and the Titan haze-top (0.01 mbar). The opacity
+database is resampled to R=10,000 and is taken from [67]. Models are then
+binned to the data for reduced-χ2 comparison.
+We strongly rule out clear atmospheres of 1× to 100× solar, with reduced-
+χ2s ≥ 9, or over 10σ. Given the mass estimate analysis above, even with
+the uncertain planetary mass, we are able to reject low (≤100× solar) atmo-
+spheres. To obtain a reduced-χ2 ∼ 1 in cloudy low-metallicity atmospheres,
+we must insert an opaque cloud deck with cloud-top pressure between 0.5 and
+1 µbar, which can be discarded as unrealistic given the lack of cloud-forming
+material at such low pressures. Each of these cases represents a hydrogen-rich
+atmosphere around a rocky, 600 K planet, which would not be stable against
+escape over the lifetime of the system, and thus our ability to reject them is
+not unexpected.
+For the 1000× atmosphere, we calculate a reduced-χ2 to the data of 1.5,
+which weakly rules out this scenario to 2.5σ. The pure methane atmosphere
+is rejected with a reduced-χ2=2.3, or 5σ. Both the end-member atmospheric
+compositions of a pure steam or Earth-like atmospheric abundances are weakly
+disfavored at ≳1σ. A pure 1 bar carbon dioxide atmosphere or no atmosphere
+at all are preferred but not statistically distinguishable from each other. For
+the Solar System terrestrial archetype atmospheres shown in Figure 11, we
+also weakly disfavor (≳1σ) clear Venus, Titan, or Earth-like atmospheres, but
+cannot statistically distinguish between a thin Mars-like atmosphere, a hazy
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+23
+3.0
+3.5
+4.0
+4.5
+5.0
+Wavelength ( m)
+200
+150
+100
+50
+0
+50
+100
+150
+200
+Relative Transit Depth (ppm)
+Earth-like: 
+2=1.1
+Mars-like: 
+2=1.0
+Titan-like, clear: 
+2=1.3
+Titan-like, hazy: 
+2=0.95
+Venus-like, clear: 
+2=1.1
+Venus-like, cloudy: 
+2=0.97
+Mercury-like: 
+2=0.91
+JWST/NIRSpec G395H
+Fig. 11
+Final, binned spectrum (black points) compared to atmospheric models with
+compositions of the Solar System terrestrial planets (coloured lines). Our data, to weakly rule
+out Earth composition (blue solid), clear Titan composition (orange solid), and clear Venus
+composition atmospheres (yellow solid). However, the data are all consistent within error to
+that of a hazy Titan composition with a haze-top at 0.01 mbar (dotted orange), a cloudy
+Venus composition with a cloud-top at 1 mbar (dotted yellow), and a Mars composition
+atmosphere (red solid), as well as that of an airless body, like Mercury (grey dotted line).
+Titan-like atmosphere, or a cloudy Venus, as consistent with the retrieval
+modeling shown in Figure 3 and discussed below.
+2.3.2 Retrieval Modeling
+We use two different atmospheric retrieval codes—smarter and POSEIDON—to
+explore the range of atmospheric properties that are consistent with, or ruled
+out, by LHS 475b’s transmission spectrum.
+Retrievals with smarter
+The smarter retrieval code [68, 69] couples line-by-line radiative transfer cal-
+culations from the Spectral Mapping Atmospheric Radiative Transfer forward
+model (smart [70]) to the dynesty nested sampling Bayesian inference code
+[56] to retrieve planetary and atmospheric parameters that are consistent with
+the JWST observations. We assume an isothermal temperature-pressure profile
+and evenly-mixed gas volume mixing ratios. We calculate line absorption coef-
+ficients for gaseous molecules using the lblabc code [70] with inputs from the
+HITRAN2016 line list [71]. To speed up the retrieval calculations, absorption
+coefficients are produced for an isothermal temperature of 550 K and resam-
+pled to a fixed wavenumber resolution of 0.25 cm−1. Our tests that relaxed
+these assumptions on the line absorption coefficients resulted in negligible
+errors relative to the measurement uncertainties.
+Our nominal smarter retrieval setup uses 9 free parameters that include
+the log10volume mixing ratios for the molecules H2O, CH4, CO2, and CO,
+
+Springer Nature 2021 LATEX template
+24
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+along with the reference radius of the planet (Rp,ref) at the spectral con-
+tinuum (which is interpreted as either a cloud-top or the solid-surface), the
+atmospheric pressure at the reference radius (P0), the isothermal temperature
+(T0), the planet mass (Mp), and the mean molecular weight (MMW) of the
+bulk atmospheric composition (µ). We impose uninformative flat priors on the
+gases within the interval U(−12, 0) log10(VMR), the radius within ±10% of
+the white light radius constraint, the apparent surface pressure P0 ∼ U(−6, 1)
+log10(bar), and the isothermal temperature T0 ∼ U(200, 900) K. The total
+atmospheric MMW is calculated self-consistently from the gases included in
+the retrieval plus an unknown, agnostic background gas that fills the remain-
+ing volume of the atmosphere after the other gases are accounted for. The
+agnostic background gas has a molecular weight sampled from a flat prior dis-
+tribution µ ∼ U(2.5, 50.0) g/mol. This covers a range in MMW from a low
+mass solar composition mixture of H2+He to high mass, simple molecules such
+as CO2 and O3. While this model construction is similar to other retrievals
+that assume a known background gas such as H2+He or N2, using a flat prior
+on the molecular weight of the background gas eliminates a strong implicit
+prior on the total atmospheric MMW (which is strongly biased to that of the
+assumed background gas). We assume that the planet possesses a rocky inte-
+rior composition, as previously discussed, and sample planet masses from a
+normal distribution Mp ∼ N(0.914, 0.187) M⊕.
+We run smarter retrievals using the dynesty code with the standard nested
+sampling algorithm [57] and fit the final coadded transmission spectrum from
+the FIREFLy reduction binned to a fixed resolution of ∆λ = 10 nm. We use
+600 live points and run the model until the estimated contribution to the
+total evidence from the remaining prior volume drops below the threshold of
+dlogz=0.075. To obtain additional posterior samples that effectively reduces
+the numerical sampling errors in the final visualization of the posteriors, we
+run an MCMC chain using emcee [51]. The MCMC is run with 135 walkers for
+1000 steps and is initialized using points from the equally weighted dynesty
+posterior. The resulting MCMC chain requires no iterations to be removed
+for the burn-in and the emcee posteriors agree with the dynesty posteriors to
+within the finite sampling uncertainty. Our final posteriors are constructed by
+combining the list of samples obtained with the two inference codes.
+Figure 12 shows the posterior PDFs from our nominal smarter retrieval
+along with an overview of spectral models sampled from the posterior.
+Although a large swath of terrestrial atmospheric parameter space remains
+allowed given the observations, a non-negligible subset of models are disfa-
+vored and provide us with insights into the nature of the planet. Figure 3
+highlights these constraints and includes the isothermal scale height for atmo-
+spheres contained in the posterior distribution. Scale height calculations are
+performed in a post-processing step after running the retrieval to compress the
+degeneracies between planet gravity (fit in terms of planet radius and mass),
+isothermal temperature, and mean molecular weight into a single representa-
+tive value for the atmosphere’s vertical extensiveness. In general, atmospheric
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+25
+Fig. 12 Corner plot showing the 1D and 2D marginalized posterior probability distribution
+for a subset of the smarter model parameters. The upper right axis shows the 1σ and 3σ
+envelope around the median retrieved spectrum, which corresponds to the multidimensional
+posterior PDF projected onto the observed spectrum. Disfavored atmospheres are thick
+(large P0), hot (large T0), and composed primarily of light molecules (low µ).
+characteristics that tend towards increasing the scale height of the atmosphere
+are disfavored, including high temperatures and low mean molecular weight
+bulk atmospheric compositions, particularly for atmospheres with apparent
+surface pressures ≳10 mbar (1000 Pa). Conversely, compact atmospheres with
+small scale heights—due to high mean molecular weight molecules or cool
+temperatures—are allowed across the full range of apparent surface pressures
+explored. These two general characteristics yield a preference for extremely low
+apparent surface pressures of ∼1 µbar. High abundances of CO2 and CH4 can
+be ruled out in the thick and extended atmospheric scenarios. While CH4 can
+be ruled out in a relatively low MMW CH4-dominated atmosphere (16 g/mol),
+
+NIRSpec G395H
+-1.70
+1300
+Atmospheric Model (± lo, 3o)
+ 218.27; x2
+= 0.97
+transit depth [ppm]
+1200
+1100
+1000
+[] L
+900
+095
+800
+3.5
+4.0
+4.5
+5.0
+[g/mol]
+15.86
+wavelength [μm]
+[g/ mol] 
+3.
+-4.79
+H20
+-2.87
+92-
+001
+5.0
+8
+To [K]
+CH4
+Po [Pa]
+μ [g/mol]
+H20
+CO2
+COSpringer Nature 2021 LATEX template
+26
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+CO2 is more difficult to rule out in a heavier CO2-dominated atmosphere (44
+g/mol).
+The H2O marginalized posterior shows a slight uptick towards large VMRs
+due to a small rise in the spectrum at the blue end (<3 µm) where there is
+a H2O band. However, we caution that since a flat line model fit provides a
+χ2 ≈ 1, the retrieval is inherently overfitting and cannot lead to a statistically
+significant detection of molecular absorption from these data. To emphasize
+this point we fit the spectrum with a generalized Gaussian model (plus a flat
+transit depth component) [e.g. 42] as a minimally parametric stand-in model
+for any molecular absorbers not included in the retrieval. This model recognizes
+the same blue end slope in its maximum likelihood solution, but is disfavored
+relative to the best fitting flat line at 3.1σ, further indicating that the “feature”
+is consistent with noise.
+We also run a series of smarter retrieval models with the same setup as
+previously described except with single gas compositions. From the posterior
+distributions, we derive the maximum size of molecular absorption features
+such that any larger and they would have been detected in the spectrum. At
+3σ confidence, we rule out H2O absorption features larger than 61 ppm at 2.8
+µm, CH4 features larger than 38 ppm at 3.3 µm, CO2 features larger than 49
+ppm at 4.3 µm, and CO features larger than 62 ppm at 4.6 µm.
+Retrievals with POSEIDON
+POSEIDON [72] is an atmospheric retrieval code that has been widely applied
+to interpret transmission spectra of giant exoplanets. POSEIDON also supports
+retrievals of terrestrial exoplanets [73, 74], which we here apply to LHS 475b’s
+transmission spectrum. The most up-to-date description of POSEIDON’s radia-
+tive transfer technique, forward atmospheric model, and opacity sources is
+contained in [75]. We explore the range of possible atmospheres for LHS 475b
+using the nested sampling algorithm PyMultiNest [76, 77].
+We employ a 9-parameter POSEIDON retrieval configuration. We compute
+transmission spectra at a spectral resolution of R = 20,000 from 2.6–5.3 µm
+(using cross sections resampled from a high-resolution wavenumber grid with
+0.01 cm−1 spacing). Our model atmospheres cover 10−7–10 bar with 100 layers
+spaced uniformly in log-pressure. We assume 1D plane-parallel atmospheres
+with an isothermal pressure-temperature profile, uniform-in-altitude gas vol-
+ume mixing ratios, and that hydrostatic equilibrium and the ideal gas law hold
+throughout the atmosphere. The stellar radius is fixed to Rs = 0.279 R⊙. The
+atmospheric structure and composition are thus described by 7 quantities: the
+isothermal temperature, T, the atmospheric radius at the 1 bar apparent sur-
+face pressure level, Rp, ref, and the volume mixing ratios of H2, H2O, CH4, CO2,
+and CO. We prescribe N2 as a spectrally inactive filler gas, which allows the
+mean molecular weight to vary in a similar manner to the smarter retrievals,
+except bounded within the simplex of gas weights included in the model. We
+also fit for the pressure of an opaque surface (or cloud), Psurf, and the gravita-
+tional field strength at the pressure level corresponding to the observed planet
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+27
+Fig. 13 Retrieved volume mixing ratios from the POSEIDON retrievals of LHS 475b’s
+transmission spectrum. Two retrievals with different prior treatments for the atmospheric
+composition are overplotted: centered log-ratio (CLR) transformed abundances with a pri-
+ori unknown composition (green); and log-uniform abundances assuming an N2-dominated
+atmosphere (orange). Statistical 2σ upper and lower limits are annotated (or ‘N/A’ if uncon-
+strained). Both retrievals rule out H2-dominated atmospheres. The log-uniform retrieval
+finds upper limits on H2O, CH4, CO2, and CO due to the assumption that N2 dominates
+the atmosphere, while the agnostic CLR treatment does not find upper limits for their abun-
+dances. For clarity in viewing upper limits, we switch from a logarithmic to linear x-axis at a
+mixing ratio of 10%. The probability densities for the linear histogram bins are renormalized
+to match the probability density of the nearest logarithmic bin left of the 10% boundary.
+radius (r = 0.991 R⊕), g. Our priors for the non-mixing ratio parameters are
+as follows: T ∼ U (200 K, 900 K), Rp, ref ∼ U (0.9 Rp, 1.1 Rp), log10 Psurf ∼ U
+(-7, 1) (units of bar), and log10 g ∼ N (2.960, 0.0992) (units of cm s−2). The
+Gaussian prior on log10 g arises from error propagation from the uncertainties
+on Rp and Mp — with the latter uncertainty assuming the same rocky interior
+assumption as the other models. We use 4,000 PyMultiNest live points during
+each retrieval.
+We explore two distinct prior treatments for the atmospheric gas mix-
+ing ratios during our POSEIDON retrievals. Our first approach parameterizes
+the mixing ratios of H2, H2O, CH4, CO2, and CO with priors uniform-in-
+the-logarithm, log10 Xi ∼ U (-12, 0), with the remainder of the atmosphere
+filled with N2 (XN2 = 1 − �
+i Xi). Any samples requiring negative N2 mix-
+ing ratios are rejected. This ‘log-uniform’ mixing ratio prior is the standard
+method used for giant exoplanet retrievals, albeit with H2 + He assumed as
+the filler gas. However, this approach implicitly places a strong prior favouring
+high abundances for the filler gas [78]. For small planets such as LHS 475b,
+where we do not know a priori which gas dominates the atmosphere, one
+
+2α limits
+2o limits
+2o limits
+N/A
+H2 < 27%
+N/A
+N² > 37%
+H0 < 19%
+H2 < 12%
+CLR Prior
+log-uniform Prior
+10-610-410-2 0.2
+1.010-610-410-2 0.20.4
+0.4
+0.6
+0.8
+1.0
+10-610-410-2 0.2　0.4　0.6
+0.8
+0.60.81.0
+N2
+H2
+H20
+2o limits
+2o limits
+2o limits
+Probability density
+N/A
+N/A
+N/A
+CH4 < 9%
+CO2 < 14%
+CO < 44%
+10-610-410-2 0.2
+10-610-410-2 0.2
+10-610-410-2 0.2
+0.4
+0.6
+0.8
+1.0
+0.4
+0.6
+0.8
+1.0
+0.4
+0.6
+0.8
+1.0
+CH4
+CO2
+COSpringer Nature 2021 LATEX template
+28
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+may prefer an agnostic prior that treats all n gases equally. Instead of the
+agnostic background gas employed by smarter to resolve this assumption,
+our second approach with POSEIDON uses the centred log-ratio transformation
+(CLR) [79] of the mixing ratios as free parameters: ξi = ln(Xi/g(X)), where
+g(X) =
+��n
+j=0 Xj
+�1/n
+. For n = 6 gases with a minimum mixing ratio of
+Xmin = 10−12, we ascribe a uniform prior on the 5 CLR variables: ξi ∼ U
+(-20.996, 22.105) — for our POSEIDON model, these correspond to H2, H2O,
+CH4, CO2, and CO. The upper limit corresponds to the ith gas (i = 1...5)
+dominating the atmosphere and all other gases having Xj̸=i = Xmin, while the
+lower limit corresponds to Xi = Xmin and the other gases equally filling the
+remainder of the atmosphere. Since �n
+i=0 ξi = 0 (which automatically ensures
+�n
+i=0 Xi = 1), we use a numerical rejection scheme to ensure that ξ0 (corre-
+sponding here to N2) falls within the allowed prior range for the other ξi. The
+results for the CLR approach are permutation invariant, so switching which
+gas corresponds to i = 0 does not alter the results.
+We find that the derived constraints on LHS 475b’s atmosphere are sen-
+sitive to the choice of mixing ratio prior. Figure 13 compares the retrieved
+abundances from POSEIDON for the CLR and log-uniform mixing ratio pri-
+ors. Both approaches rule out H2 dominated atmospheres: log (H2) < 27% for
+CLR priors vs. log (H2) < 12% for log-uniform priors (both 2σ upper limits).
+However, the log-uniform retrieval also infers upper limits on the abundances
+of H2O, CH4, CO2, and CO — ranging from < 9% to < 44% — which arise
+from the built in prior bias towards N2 being the background gas. The CLR
+prior, in contrast, recognizes that these heavier gases all provide reasonable
+explanations for LHS 475b’s flat transmission spectrum due to their high mean
+molecular weight — consistent with the smarter retrieval which also ruled out
+low mean molecular weights. However, even with the CLR prior, certain atmo-
+spheric scenarios are still disfavored. By examining Figure 14, which shows the
+full POSEIDON posterior for the CLR prior, one can see that CH4 dominated
+atmospheres with surface pressures ≳ 10 mbar are ruled out to 3σ confidence.
+In other words, our retrieval accounting for the a priori unknown background
+gas confirms the result from our forward modelling analysis that thick, pure
+CH4 atmospheres with Psurf ≥ 1 bar are strongly ruled by our LHS 475b
+transmission spectrum.
+Acknowledgments.
+Data Availability:
+The data used in this paper are from the JWST Cycle 1 General Observer
+program 1981 and are publicly available on the Mikulski Archive for Space
+Telescopes (https://mast.stsci.edu). Fully reduced data products from this
+paper will posted on the Zenodo long term public archive upon acceptance.
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+29
+Rp, ref = 0.97+0.01
+−0.02
+2.70
+2.85
+3.00
+3.15
+3.30
+log g
+log g = 2.98+0.09
+−0.09
+6
+4
+2
+0
+log Psurf
+log Psurf = −3.96+2.70
+−2.05
+300
+450
+600
+750
+900
+T
+T = 393+264
+−138
+10.0
+7.5
+5.0
+2.5
+0.0
+log H2
+log H2 = −6.20+3.89
+−3.75
+10.0
+7.5
+5.0
+2.5
+0.0
+log H2O
+log H2O = −5.21+4.67
+−4.46
+10.0
+7.5
+5.0
+2.5
+0.0
+log CH4
+log CH4 = −5.88+4.04
+−3.96
+10.0
+7.5
+5.0
+2.5
+0.0
+log CO2
+log CO2 = −5.85+5.62
+−4.10
+0.90
+0.95
+1.00
+1.05
+Rp, ref
+10.0
+7.5
+5.0
+2.5
+0.0
+log CO
+2.70
+2.85
+3.00
+3.15
+3.30
+log g
+6
+4
+2
+0
+log Psurf
+300
+450
+600
+750
+900
+T
+10.0
+7.5
+5.0
+2.5
+0.0
+log H2
+10.0
+7.5
+5.0
+2.5
+0.0
+log H2O
+10.0
+7.5
+5.0
+2.5
+0.0
+log CH4
+10.0
+7.5
+5.0
+2.5
+0.0
+log CO2
+10.0
+7.5
+5.0
+2.5
+0.0
+log CO
+log CO = −2.00+2.00
+−6.40
+LHS 475b
+Fig. 14 Corner plot showing the 1D and 2D marginalized posterior probability distribu-
+tions from the POSEIDON retrieval using CLR mixing ratio parameters. The units are: Rp, ref
+(R⊕), g (cm s−2), Psurf (bar), and T (K). The inset shows the corresponding retrieved
+transmission spectrum model (1σ and 2σ confidence regions) compared to the NIRSpec
+G395H observations. The solution rules out H2-dominated atmospheres (to > 5σ) and thick
+atmospheres (Psurf ≳ 10 mbar) dominated by CH4 (to 3σ).
+Code Availability:
+The codes used throughout this work for data analysis, atmospheric mod-
+eling, and manuscript preparation are as follows: Astropy [80, 81], Batman
+[50], CHIMERA [61, 62], Dynesty [56], emcee [51], Eureka! [29], ExoCTK [82],
+Forecaster [58], IPython [83], jwst [41], Matplotlib [84], NumPy [85, 86],
+PICASO [60], POSEIDON [72], PyMC3[87], SciPy [88], smarter [69].
+References
+[1] Fujii, Y., Angerhausen, D., Deitrick, R., Domagal-Goldman, S., Grenfell,
+J.L., Hori, Y., Kane, S.R., Pall´e, E., Rauer, H., Siegler, N., Stapelfeldt,
+
+×10-3
+Retrieved Spectrum (Median)
+1.24
+G 4102b
+Retrieved Spectrum (lo)
+Retrieved Spectrum (2o)
+1.20
+Retrieved Spectrum (Binned)
+ JWST NIRSpec G395H
+2
+1.16
+1.12
+.08
+1.04
+1.00
+0.96
+0.92
+2.8
+3
+3.2
+3.4
+3.6
+3.8
+4
+4.2
+4.4
+4.6
+4.8
+5
+5.2
+Wavelength (μm)Springer Nature 2021 LATEX template
+30
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+K., Stevenson, K.B.: Exoplanet Biosignatures: Observational Prospects.
+Astrobiology 18(6), 739–778 (2018) arXiv:1705.07098 [astro-ph.EP].
+https://doi.org/10.1089/ast.2017.1733
+[2] of Sciences Engineering, N.A., Medicine: Exoplanet Science Strategy,
+(2018)
+[3] Seager, S., Deming, D.: On the Method to Infer an Atmosphere on a
+Tidally Locked Super Earth Exoplanet and Upper Limits to GJ 876d.
+ApJ 703(2), 1884–1889 (2009) arXiv:0910.1505 [astro-ph.EP]. https://
+doi.org/10.1088/0004-637X/703/2/1884
+[4] Mansfield, M., Kite, E.S., Hu, R., Koll, D.D.B., Malik, M., Bean,
+J.L., Kempton, E.M.-R.: Identifying Atmospheres on Rocky Exoplanets
+through Inferred High Albedo. ApJ 886(2), 141 (2019) arXiv:1907.13150
+[astro-ph.EP]. https://doi.org/10.3847/1538-4357/ab4c90
+[5] Segura, A., Kasting, J.F., Meadows, V., Cohen, M., Scalo, J., Crisp,
+D., Butler, R.A.H., Tinetti, G.: Biosignatures from Earth-Like Planets
+Around M Dwarfs. Astrobiology 5, 706–725 (2005) astro-ph/0510224.
+https://doi.org/10.1089/ast.2005.5.706
+[6] Tian, F.: Atmospheric escape from solar system terrestrial planets and
+exoplanets. Annual Review of Earth and Planetary Sciences 43, 459–476
+(2015)
+[7] Luger, R., Barnes, R.: Extreme Water Loss and Abiotic O2Buildup on
+Planets Throughout the Habitable Zones of M Dwarfs. Astrobiology 15,
+119–143 (2015) arXiv:1411.7412 [astro-ph.EP]. https://doi.org/10.1089/
+ast.2014.1231
+[8] Batalha, N.E., Lewis, N.K., Line, M.R., Valenti, J., Stevenson, K.: Strate-
+gies for Constraining the Atmospheres of Temperate Terrestrial Planets
+with JWST. ApJL 856(2), 34 (2018) arXiv:1803.07983 [astro-ph.EP].
+https://doi.org/10.3847/2041-8213/aab896
+[9] Lustig-Yaeger, J., Meadows, V.S., Lincowski, A.P.: The Detectability
+and Characterization of the TRAPPIST-1 Exoplanet Atmospheres with
+JWST. AJ 158(1), 27 (2019) arXiv:1905.07070 [astro-ph.EP]. https://
+doi.org/10.3847/1538-3881/ab21e0
+[10] Guerrero, N.M., Seager, S., Huang, C.X., Vanderburg, A., Garcia Soto,
+A., Mireles, I., Hesse, K., Fong, W., Glidden, A., Shporer, A., Latham,
+D.W., Collins, K.A., Quinn, S.N., Burt, J., Dragomir, D., Crossfield,
+I., Vanderspek, R., Fausnaugh, M., Burke, C.J., Ricker, G., Daylan, T.,
+Essack, Z., G¨unther, M.N., Osborn, H.P., Pepper, J., Rowden, P., Sha,
+L., Villanueva, J. Steven, Yahalomi, D.A., Yu, L., Ballard, S., Batalha,
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+31
+N.M., Berardo, D., Chontos, A., Dittmann, J.A., Esquerdo, G.A., Mikal-
+Evans, T., Jayaraman, R., Krishnamurthy, A., Louie, D.R., Mehrle, N.,
+Niraula, P., Rackham, B.V., Rodriguez, J.E., Rowden, S.J.L., Sousa-Silva,
+C., Watanabe, D., Wong, I., Zhan, Z., Zivanovic, G., Christiansen, J.L.,
+Ciardi, D.R., Swain, M.A., Lund, M.B., Mullally, S.E., Fleming, S.W.,
+Rodriguez, D.R., Boyd, P.T., Quintana, E.V., Barclay, T., Col´on, K.D.,
+Rinehart, S.A., Schlieder, J.E., Clampin, M., Jenkins, J.M., Twicken,
+J.D., Caldwell, D.A., Coughlin, J.L., Henze, C., Lissauer, J.J., Morris,
+R.L., Rose, M.E., Smith, J.C., Tenenbaum, P., Ting, E.B., Wohler, B.,
+Bakos, G.´A., Bean, J.L., Berta-Thompson, Z.K., Bieryla, A., Bouma,
+L.G., Buchhave, L.A., Butler, N., Charbonneau, D., Doty, J.P., Ge, J.,
+Holman, M.J., Howard, A.W., Kaltenegger, L., Kane, S.R., Kjeldsen, H.,
+Kreidberg, L., Lin, D.N.C., Minsky, C., Narita, N., Paegert, M., P´al, A.,
+Palle, E., Sasselov, D.D., Spencer, A., Sozzetti, A., Stassun, K.G., Tor-
+res, G., Udry, S., Winn, J.N.: The TESS Objects of Interest Catalog
+from the TESS Prime Mission. ApJS 254(2), 39 (2021) arXiv:2103.12538
+[astro-ph.EP]. https://doi.org/10.3847/1538-4365/abefe1
+[11] Rackham, B.V., Apai, D., Giampapa, M.S.: The Transit Light Source
+Effect: False Spectral Features and Incorrect Densities for M-dwarf Tran-
+siting Planets. ApJ 853(2), 122 (2018) arXiv:1711.05691 [astro-ph.EP].
+https://doi.org/10.3847/1538-4357/aaa08c
+[12] Delrez, L., Gillon, M., Triaud, A.H.M.J., Demory, B.-O., de Wit, J.,
+Ingalls, J.G., Agol, E., Bolmont, E., Burdanov, A., Burgasser, A.J.,
+Carey, S.J., Jehin, E., Leconte, J., Lederer, S., Queloz, D., Selsis, F.,
+Van Grootel, V.: Early 2017 observations of TRAPPIST-1 with Spitzer.
+MNRAS 475(3), 3577–3597 (2018) arXiv:1801.02554 [astro-ph.EP]. https:
+//doi.org/10.1093/mnras/sty051
+[13] de Wit, J., Wakeford, H.R., Gillon, M., Lewis, N.K., Valenti, J.A.,
+Demory, B.-O., Burgasser, A.J., Burdanov, A., Delrez, L., Jehin, E.,
+Lederer, S.M., Queloz, D., Triaud, A.H.M.J., Van Grootel, V.: A com-
+bined transmission spectrum of the Earth-sized exoplanets TRAPPIST-1
+b and c. Nature 537, 69–72 (2016) arXiv:1606.01103 [astro-ph.EP]. https:
+//doi.org/10.1038/nature18641
+[14] de Wit, J., Wakeford, H.R., Lewis, N.K., Delrez, L., Gillon, M., Selsis,
+F., Leconte, J., Demory, B.-O., Bolmont, E., Bourrier, V., Burgasser,
+A.J., Grimm, S., Jehin, E., Lederer, S.M., Owen, J.E., Stamenkovi´c,
+V., Triaud, A.H.M.J.: Atmospheric reconnaissance of the habitable-
+zone Earth-sized planets orbiting TRAPPIST-1. Nature Astronomy 2,
+214–219 (2018) arXiv:1802.02250 [astro-ph.EP]. https://doi.org/10.1038/
+s41550-017-0374-z
+[15] Zhang, Z., Zhou, Y., Rackham, B.V., Apai, D.: The Near-infrared
+
+Springer Nature 2021 LATEX template
+32
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+Transmission Spectra of TRAPPIST-1 Planets b, c, d, e, f, and g
+and Stellar Contamination in Multi-epoch Transit Spectra. AJ 156(4),
+178 (2018) arXiv:1802.02086 [astro-ph.EP]. https://doi.org/10.3847/
+1538-3881/aade4f
+[16] Edwards, B., Changeat, Q., Mori, M., Anisman, L.O., Morvan, M.,
+Yip, K.H., Tsiaras, A., Al-Refaie, A., Waldmann, I., Tinetti, G.: Hub-
+ble WFC3 Spectroscopy of the Habitable-zone Super-Earth LHS 1140 b.
+AJ 161(1), 44 (2021) arXiv:2011.08815 [astro-ph.EP]. https://doi.org/10.
+3847/1538-3881/abc6a5
+[17] Kreidberg, L., Koll, D.D.B., Morley, C., Hu, R., Schaefer, L., Dem-
+ing, D., Stevenson, K.B., Dittmann, J., Vanderburg, A., Berardo, D.,
+Guo, X., Stassun, K., Crossfield, I., Charbonneau, D., Latham, D.W.,
+Loeb, A., Ricker, G., Seager, S., Vanderspek, R.: Absence of a thick
+atmosphere on the terrestrial exoplanet LHS 3844b. Nature 573(7772),
+87–90 (2019) arXiv:1908.06834 [astro-ph.EP]. https://doi.org/10.1038/
+s41586-019-1497-4
+[18] Swain, M.R., Estrela, R., Roudier, G.M., Sotin, C., Rimmer, P.B.,
+Valio, A., West, R., Pearson, K., Huber-Feely, N., Zellem, R.T.:
+Detection of an Atmosphere on a Rocky Exoplanet. AJ 161(5),
+213 (2021) arXiv:2103.05657 [astro-ph.EP]. https://doi.org/10.3847/
+1538-3881/abe879
+[19] Mugnai, L.V., Modirrousta-Galian, D., Edwards, B., Changeat, Q., Bouw-
+man, J., Morello, G., Al-Refaie, A., Baeyens, R., Bieger, M.F., Blain, D.,
+Gressier, A., Guilluy, G., Jaziri, Y., Kiefer, F., Morvan, M., Pluriel, W.,
+Poveda, M., Skaf, N., Whiteford, N., Wright, S., Yip, K.H., Zingales, T.,
+Charnay, B., Drossart, P., Leconte, J., Venot, O., Waldmann, I., Beaulieu,
+J.-P.: ARES. V. No Evidence For Molecular Absorption in the HST
+WFC3 Spectrum of GJ 1132 b. AJ 161(6), 284 (2021) arXiv:2104.01873
+[astro-ph.EP]. https://doi.org/10.3847/1538-3881/abf3c3
+[20] Libby-Roberts, J.E., Berta-Thompson, Z.K., Diamond-Lowe, H., Gully-
+Santiago, M.A., Irwin, J.M., Kempton, E.M.-R., Rackham, B.V., Char-
+bonneau, D., D´esert, J.-M., Dittmann, J.A., Hofmann, R., Morley, C.V.,
+Newton, E.R.: The Featureless HST/WFC3 Transmission Spectrum of
+the Rocky Exoplanet GJ 1132b: No Evidence for a Cloud-free Pri-
+mordial Atmosphere and Constraints on Starspot Contamination. AJ
+164(2), 59 (2022) arXiv:2105.10487 [astro-ph.EP]. https://doi.org/10.
+3847/1538-3881/ac75de
+[21] Morley, C.V., Kreidberg, L., Rustamkulov, Z., Robinson, T., Fortney,
+J.J.: Observing the Atmospheres of Known Temperate Earth-sized Plan-
+ets with JWST. ApJ 850(2), 121 (2017) arXiv:1708.04239 [astro-ph.EP].
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+33
+https://doi.org/10.3847/1538-4357/aa927b
+[22] Garcia-Sage, K., Glocer, A., Drake, J.J., Gronoff, G., Cohen, O.: On the
+Magnetic Protection of the Atmosphere of Proxima Centauri b. ApJL
+844(1), 13 (2017). https://doi.org/10.3847/2041-8213/aa7eca
+[23] Airapetian, V.S., Barnes, R., Cohen, O., Collinson, G.A., Danchi, W.C.,
+Dong, C.F., Del Genio, A.D., France, K., Garcia-Sage, K., Glocer, A.,
+Gopalswamy, N., Grenfell, J.L., Gronoff, G., G¨udel, M., Herbst, K., Hen-
+ning, W.G., Jackman, C.H., Jin, M., Johnstone, C.P., Kaltenegger, L.,
+Kay, C.D., Kobayashi, K., Kuang, W., Li, G., Lynch, B.J., L¨uftinger,
+T., Luhmann, J.G., Maehara, H., Mlynczak, M.G., Notsu, Y., Osten,
+R.A., Ramirez, R.M., Rugheimer, S., Scheucher, M., Schlieder, J.E., Shi-
+bata, K., Sousa-Silva, C., Stamenkovi´c, V., Strangeway, R.J., Usmanov,
+A.V., Vergados, P., Verkhoglyadova, O.P., Vidotto, A.A., Voytek, M.,
+Way, M.J., Zank, G.P., Yamashiki, Y.: Impact of space weather on cli-
+mate and habitability of terrestrial-type exoplanets. International Journal
+of Astrobiology 19(2), 136–194 (2020) arXiv:1905.05093 [astro-ph.EP].
+https://doi.org/10.1017/S1473550419000132
+[24] Jakobsen, P., Ferruit, P., Alves de Oliveira, C., Arribas, S., Bagnasco, G.,
+Barho, R., Beck, T.L., Birkmann, S., B¨oker, T., Bunker, A.J., Charlot, S.,
+de Jong, P., de Marchi, G., Ehrenwinkler, R., Falcolini, M., Fels, R., Franx,
+M., Franz, D., Funke, M., Giardino, G., Gnata, X., Holota, W., Honnen,
+K., Jensen, P.L., Jentsch, M., Johnson, T., Jollet, D., Karl, H., Kling, G.,
+K¨ohler, J., Kolm, M.-G., Kumari, N., Lander, M.E., Lemke, R., L´opez-
+Caniego, M., L¨utzgendorf, N., Maiolino, R., Manjavacas, E., Marston, A.,
+Maschmann, M., Maurer, R., Messerschmidt, B., Moseley, S.H., Mosner,
+P., Mott, D.B., Muzerolle, J., Pirzkal, N., Pittet, J.-F., Plitzke, A., Posselt,
+W., Rapp, B., Rauscher, B.J., Rawle, T., Rix, H.-W., R¨odel, A., Rumler,
+P., Sabbi, E., Salvignol, J.-C., Schmid, T., Sirianni, M., Smith, C., Strada,
+P., te Plate, M., Valenti, J., Wettemann, T., Wiehe, T., Wiesmayer, M.,
+Willott, C.J., Wright, R., Zeidler, P., Zincke, C.: The Near-Infrared Spec-
+trograph (NIRSpec) on the James Webb Space Telescope. I. Overview of
+the instrument and its capabilities. A&A 661, 80 (2022) arXiv:2202.03305
+[astro-ph.IM]. https://doi.org/10.1051/0004-6361/202142663
+[25] Birkmann, S.M., Ferruit, P., Giardino, G., Nielsen, L.D., Garc´ıa Mu˜noz,
+A., Kendrew, S., Rauscher, B.J., Beck, T.L., Keyes, C., Valenti, J.A.,
+Jakobsen, P., Dorner, B., Alves de Oliveira, C., Arribas, S., B¨oker, T.,
+Bunker, A.J., Charlot, S., de Marchi, G., Kumari, N., L´opez-Caniego,
+M., L¨utzgendorf, N., Maiolino, R., Manjavacas, E., Marston, A., Mose-
+ley, S.H., Prizkal, N., Proffitt, C., Rawle, T., Rix, H.-W., te Plate, M.,
+Sabbi, E., Sirianni, M., Willott, C.J., Zeidler, P.: The Near-Infrared
+Spectrograph (NIRSpec) on the James Webb Space Telescope. IV. Capa-
+bilities and predicted performance for exoplanet characterization. A&A
+
+Springer Nature 2021 LATEX template
+34
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+661, 83 (2022) arXiv:2202.03309 [astro-ph.IM]. https://doi.org/10.1051/
+0004-6361/202142592
+[26] Ricker, G.R., Winn, J.N., Vanderspek, R., Latham, D.W., Bakos, G.´A.,
+Bean, J.L., Berta-Thompson, Z.K., Brown, T.M., Buchhave, L., But-
+ler, N.R., Butler, R.P., Chaplin, W.J., Charbonneau, D., Christensen-
+Dalsgaard, J., Clampin, M., Deming, D., Doty, J., De Lee, N., Dressing,
+C., Dunham, E.W., Endl, M., Fressin, F., Ge, J., Henning, T., Holman,
+M.J., Howard, A.W., Ida, S., Jenkins, J.M., Jernigan, G., Johnson, J.A.,
+Kaltenegger, L., Kawai, N., Kjeldsen, H., Laughlin, G., Levine, A.M., Lin,
+D., Lissauer, J.J., MacQueen, P., Marcy, G., McCullough, P.R., Morton,
+T.D., Narita, N., Paegert, M., Palle, E., Pepe, F., Pepper, J., Quirren-
+bach, A., Rinehart, S.A., Sasselov, D., Sato, B., Seager, S., Sozzetti,
+A., Stassun, K.G., Sullivan, P., Szentgyorgyi, A., Torres, G., Udry, S.,
+Villasenor, J.: Transiting Exoplanet Survey Satellite (TESS). Journal of
+Astronomical Telescopes, Instruments, and Systems 1, 014003 (2015).
+https://doi.org/10.1117/1.JATIS.1.1.014003
+[27] Stassun, K.G., Oelkers, R.J., Paegert, M., Torres, G., Pepper, J., De
+Lee, N., Collins, K., Latham, D.W., Muirhead, P.S., Chittidi, J., Rojas-
+Ayala, B., Fleming, S.W., Rose, M.E., Tenenbaum, P., Ting, E.B.,
+Kane, S.R., Barclay, T., Bean, J.L., Brassuer, C.E., Charbonneau, D.,
+Ge, J., Lissauer, J.J., Mann, A.W., McLean, B., Mullally, S., Narita,
+N., Plavchan, P., Ricker, G.R., Sasselov, D., Seager, S., Sharma, S.,
+Shiao, B., Sozzetti, A., Stello, D., Vanderspek, R., Wallace, G., Winn,
+J.N.: The Revised TESS Input Catalog and Candidate Target List. AJ
+158(4), 138 (2019) arXiv:1905.10694 [astro-ph.SR]. https://doi.org/10.
+3847/1538-3881/ab3467
+[28] Kasting, J.F., Whitmire, D.P., Reynolds, R.T.: Habitable Zones around
+Main Sequence Stars. Icarus 101(1), 108–128 (1993). https://doi.org/10.
+1006/icar.1993.1010
+[29] Bell, T.J., Ahrer, E.-M., Brande, J., Carter, A.L., Feinstein, A.D., Guz-
+man Caloca, G., Mansfield, M., Zieba, S., Piaulet, C., Benneke, B.,
+Filippazzo, J., May, E.M., Roy, P.-A., Kreidberg, L., Stevenson, K.B.:
+Eureka!: An End-to-End Pipeline for JWST Time-Series Observations.
+arXiv e-prints, 2207–03585 (2022) arXiv:2207.03585 [astro-ph.IM]
+[30] Rustamkulov, Z., Sing, D.K., Mukherjee, S., May, E.M., Kirk, J.,
+Schlawin, E., Line, M.R., Piaulet, C., Carter, A.L., Batalha, N.E., Goyal,
+J.M., L´opez-Morales, M., Lothringer, J.D., MacDonald, R.J., Moran,
+S.E., Stevenson, K.B., Wakeford, H.R., Espinoza, N., Bean, J.L., Batalha,
+N.M., Benneke, B., Berta-Thompson, Z.K., Crossfield, I.J.M., Gao, P.,
+Kreidberg, L., Powell, D.K., Cubillos, P.E., Gibson, N.P., Leconte, J.,
+Molaverdikhani, K., Nikolov, N.K., Parmentier, V., Roy, P., Taylor, J.,
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+35
+Turner, J.D., Wheatley, P.J., Aggarwal, K., Ahrer, E., Alam, M.K., Alder-
+son, L., Allen, N.H., Banerjee, A., Barat, S., Barrado, D., Barstow, J.K.,
+Bell, T.J., Blecic, J., Brande, J., Casewell, S., Changeat, Q., Chubb, K.L.,
+Crouzet, N., Daylan, T., Decin, L., D´esert, J., Mikal-Evans, T., Fein-
+stein, A.D., Flagg, L., Fortney, J.J., Harrington, J., Heng, K., Hong, Y.,
+Hu, R., Iro, N., Kataria, T., Kempton, E.M.-R., Krick, J., Lendl, M.,
+Lillo-Box, J., Louca, A., Lustig-Yaeger, J., Mancini, L., Mansfield, M.,
+Mayne, N.J., Miguel, Y., Morello, G., Ohno, K., Palle, E., Petit dit de
+la Roche, D.J.M., Rackham, B.V., Radica, M., Ramos-Rosado, L., Red-
+field, S., Rogers, L.K., Shkolnik, E.L., Southworth, J., Teske, J., Tremblin,
+P., Tucker, G.S., Venot, O., Waalkes, W.C., Welbanks, L., Zhang, X.,
+Zieba, S.: Early Release Science of the exoplanet WASP-39b with JWST
+NIRSpec PRISM. arXiv e-prints, 2211–10487 (2022) arXiv:2211.10487
+[astro-ph.EP]
+[31] Kirk, J., Wheatley, P.J., Louden, T., Skillen, I., King, G.W., McCormac,
+J., Irwin, P.G.J.: LRG-BEASTS III: ground-based transmission spec-
+trum of the gas giant orbiting the cool dwarf WASP-80. MNRAS 474(1),
+876–885 (2018) arXiv:1710.10083 [astro-ph.EP]. https://doi.org/10.1093/
+mnras/stx2826
+[32] Kirk, J., L´opez-Morales, M., Wheatley, P.J., Weaver, I.C., Skillen,
+I., Louden, T., McCormac, J., Espinoza, N.: LRG-BEASTS: Trans-
+mission Spectroscopy and Retrieval Analysis of the Highly Inflated
+Saturn-mass Planet WASP-39b. AJ 158(4), 144 (2019) arXiv:1908.02358
+[astro-ph.EP]. https://doi.org/10.3847/1538-3881/ab397d
+[33] Kirk, J., Rackham, B.V., MacDonald, R.J., L´opez-Morales, M., Espinoza,
+N., Lendl, M., Wilson, J., Osip, D.J., Wheatley, P.J., Skillen, I., Apai, D.,
+Bixel, A., Gibson, N.P., Jord´an, A., Lewis, N.K., Louden, T., McGruder,
+C.D., Nikolov, N., Rodler, F., Weaver, I.C.: ACCESS and LRG-BEASTS:
+A Precise New Optical Transmission Spectrum of the Ultrahot Jupiter
+WASP-103b. AJ 162(1), 34 (2021) arXiv:2105.00012 [astro-ph.EP]. https:
+//doi.org/10.3847/1538-3881/abfcd2
+[34] Luque, R., Pall´e, E.: Density, not radius, separates rocky and water-rich
+small planets orbiting M dwarf stars. Science 377(6611), 1211–1214 (2022)
+arXiv:2209.03871 [astro-ph.EP]. https://doi.org/10.1126/science.abl7164
+[35] Magic, Z., Chiavassa, A., Collet, R., Asplund, M.: The Stagger-grid: A
+grid of 3D stellar atmosphere models. IV. Limb darkening coefficients.
+A&A 573, 90 (2015) arXiv:1403.3487 [astro-ph.SR]. https://doi.org/10.
+1051/0004-6361/201423804
+[36] Trotta, R.: Bayes in the sky: Bayesian inference and model selection in
+cosmology. Contemporary Physics 49(2), 71–104 (2008) arXiv:0803.4089
+
+Springer Nature 2021 LATEX template
+36
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+[astro-ph]. https://doi.org/10.1080/00107510802066753
+[37] Kreidberg, L., Bean, J.L., D´esert, J.-M., Benneke, B., Deming, D., Steven-
+son, K.B., Seager, S., Berta-Thompson, Z., Seifahrt, A., Homeier, D.:
+Clouds in the atmosphere of the super-Earth exoplanet GJ1214b. Nature
+505, 69–72 (2014) arXiv:1401.0022 [astro-ph.EP]. https://doi.org/10.
+1038/nature12888
+[38] Tremblay, L., Line, M.R., Stevenson, K., Kataria, T., Zellem, R.T., Fort-
+ney, J.J., Morley, C.: The Detectability and Constraints of Biosignature
+Gases in the Near- and Mid-infrared from Transit Transmission Spec-
+troscopy. AJ 159(3), 117 (2020) arXiv:1912.10939 [astro-ph.EP]. https:
+//doi.org/10.3847/1538-3881/ab64dd
+[39] Medina, A.A., Winters, J.G., Irwin, J.M., Charbonneau, D.: Flare
+Rates, Rotation Periods, and Spectroscopic Activity Indicators of a
+Volume-complete Sample of Mid- to Late-M Dwarfs within 15 pc. ApJ
+905(2), 107 (2020) arXiv:2010.15635 [astro-ph.SR]. https://doi.org/10.
+3847/1538-4357/abc686
+[40] Koll, D.D.B., Malik, M., Mansfield, M., Kempton, E.M.-R., Kite,
+E., Abbot, D., Bean, J.L.: Identifying Candidate Atmospheres on
+Rocky
+M
+Dwarf
+Planets
+via
+Eclipse
+Photometry.
+ApJ
+886(2),
+140 (2019) arXiv:1907.13138 [astro-ph.EP]. https://doi.org/10.3847/
+1538-4357/ab4c91
+[41] Bushouse, H., Eisenhamer, J., Dencheva, N., Davies, J., Greenfield, P.,
+Morrison, J., Hodge, P., Simon, B., Grumm, D., Droettboom, M., Slavich,
+E., Sosey, M., Pauly, T., Miller, T., Jedrzejewski, R., Hack, W., Davis,
+D., Crawford, S., Law, D., Gordon, K., Regan, M., Cara, M., MacDon-
+ald, K., Bradley, L., Shanahan, C., Jamieson, W., Teodoro, M., Williams,
+T.: JWST Calibration Pipeline. https://doi.org/10.5281/zenodo.7325378.
+https://doi.org/10.5281/zenodo.7325378
+[42] The JWST Transiting Exoplanet Community Early Release Science
+Team, Ahrer, E.-M., Alderson, L., Batalha, N.M., Batalha, N.E., Bean,
+J.L., Beatty, T.G., Bell, T.J., Benneke, B., Berta-Thompson, Z.K., Carter,
+A.L., Crossfield, I.J.M., Espinoza, N., Feinstein, A.D., Fortney, J.J.,
+Gibson, N.P., Goyal, J.M., Kempton, E.M.-R., Kirk, J., Kreidberg, L.,
+L´opez-Morales, M., Line, M.R., Lothringer, J.D., Moran, S.E., Mukher-
+jee, S., Ohno, K., Parmentier, V., Piaulet, C., Rustamkulov, Z., Schlawin,
+E., Sing, D.K., Stevenson, K.B., Wakeford, H.R., Allen, N.H., Birkmann,
+S.M., Brande, J., Crouzet, N., Cubillos, P.E., Damiano, M., D´esert, J.-
+M., Gao, P., Harrington, J., Hu, R., Kendrew, S., Knutson, H.A., Lagage,
+P.-O., Leconte, J., Lendl, M., MacDonald, R.J., May, E.M., Miguel, Y.,
+Molaverdikhani, K., Moses, J.I., Murray, C.A., Nehring, M., Nikolov,
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+37
+N.K., Petit dit de la Roche, D.J.M., Radica, M., Roy, P.-A., Stassun,
+K.G., Taylor, J., Waalkes, W.C., Wachiraphan, P., Welbanks, L., Wheat-
+ley, P.J., Aggarwal, K., Alam, M.K., Banerjee, A., Barstow, J.K., Blecic,
+J., Casewell, S.L., Changeat, Q., Chubb, K.L., Col´on, K.D., Coulombe,
+L.-P., Daylan, T., de Val-Borro, M., Decin, L., Dos Santos, L.A., Flagg,
+L., France, K., Fu, G., Garc´ıa Mu˜noz, A., Gizis, J.E., Glidden, A., Grant,
+D., Heng, K., Henning, T., Hong, Y.-C., Inglis, J., Iro, N., Kataria,
+T., Komacek, T.D., Krick, J.E., Lee, E.K.H., Lewis, N.K., Lillo-Box,
+J., Lustig-Yaeger, J., Mancini, L., Mandell, A.M., Mansfield, M., Mar-
+ley, M.S., Mikal-Evans, T., Morello, G., Nixon, M.C., Ortiz Ceballos, K.,
+Piette, A.A.A., Powell, D., Rackham, B.V., Ramos-Rosado, L., Rauscher,
+E., Redfield, S., Rogers, L.K., Roman, M.T., Roudier, G.M., Scarsdale,
+N., Shkolnik, E.L., Southworth, J., Spake, J.J., E Steinrueck, M., Tan, X.,
+Teske, J.K., Tremblin, P., Tsai, S.-M., Tucker, G.S., Turner, J.D., Valenti,
+J.A., Venot, O., Waldmann, I.P., Wallack, N.L., Zhang, X., Zieba, S.: Iden-
+tification of carbon dioxide in an exoplanet atmosphere. arXiv e-prints,
+2208–11692 (2022) arXiv:2208.11692 [astro-ph.EP]
+[43] Espinoza, N., ´Ubeda, L., Birkmann, S.M., Ferruit, P., Valenti, J.A., Sing,
+D.K., Rustamkulov, Z., Regan, M., Kendrew, S., Sabbi, E., Schlawin, E.,
+Beatty, T., Albert, L., Greene, T.P., Nikolov, N., Karakla, D., Keyes,
+C., Kumari, N., Alves de Oliveira, C., B¨oker, T., Pe˜na-Guerrero, M.,
+Giardino, G., Manjavacas, E., Proffitt, C., Rawle, T.: Spectroscopic Time-
+series Performance of JWST/NIRSpec from Commissioning Observations.
+arXiv e-prints, 2211–01459 (2022) arXiv:2211.01459 [astro-ph.EP]
+[44] Rustamkulov, Z., Sing, D.K., Liu, R., Wang, A.: Analysis of a JWST
+NIRSpec Lab Time Series: Characterizing Systematics, Recovering Exo-
+planet Transit Spectroscopy, and Constraining a Noise Floor. ApJL
+928(1), 7 (2022) arXiv:2203.04173 [astro-ph.EP]. https://doi.org/10.
+3847/2041-8213/ac5b6f
+[45] Laginja, I., Wakeford, H.R.: ExoTiC-ISM: A Python package for
+marginalised exoplanet transit parameters across a grid of systematic
+instrument models. Journal of Open Source Software 5(51), 2281 (2020).
+https://doi.org/10.21105/joss.02281
+[46] Laginja, I., Wakeford, H.R.: ExoTiC-ISM V2.0.0. https://doi.org/10.
+5281/zenodo.3923986. https://doi.org/10.5281/zenodo.3923986
+[47] Wakeford, H., Grant, D.: Exo-TiC/ExoTiC-LD: ExoTiC-LD V2.1 Zen-
+odo Release. https://doi.org/10.5281/zenodo.6809899. https://doi.org/
+10.5281/zenodo.6809899
+[48] Claret, A.: A new non-linear limb-darkening law for LTE stellar atmo-
+sphere models. Calculations for -5.0 <= log[M/H] <= +1, 2000 K <=
+
+Springer Nature 2021 LATEX template
+38
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+Teff <= 50000 K at several surface gravities. A&A 363, 1081–1190
+(2000)
+[49] Sing, D.K.: Stellar limb-darkening coefficients for CoRot and Kepler. A&A
+510, 21 (2010) arXiv:0912.2274 [astro-ph.EP]. https://doi.org/10.1051/
+0004-6361/200913675
+[50] Kreidberg, L.: batman: BAsic Transit Model cAlculatioN in Python.
+PASP 127(957), 1161 (2015) arXiv:1507.08285 [astro-ph.EP]. https://doi.
+org/10.1086/683602
+[51] Foreman-Mackey, D., Hogg, D.W., Lang, D., Goodman, J.: emcee: The
+MCMC Hammer. PASP 125(925), 306 (2013) arXiv:1202.3665 [astro-
+ph.IM]. https://doi.org/10.1086/670067
+[52] Parviainen, H., Pall´e, E., Nortmann, L., Nowak, G., Iro, N., Murgas, F.,
+Aigrain, S.: The GTC exoplanet transit spectroscopy survey II: An overly-
+large Rayleigh-like feature for exoplanet TrES-3b. ArXiv e-prints (2015)
+arXiv:1510.04988 [astro-ph.EP]
+[53] Husser, T.-O., Wende-von Berg, S., Dreizler, S., Homeier, D., Rein-
+ers,
+A.,
+Barman,
+T.,
+Hauschildt,
+P.H.:
+A
+new
+extensive
+library
+of
+PHOENIX
+stellar
+atmospheres
+and
+synthetic
+spectra.
+A&A
+553, 6 (2013) arXiv:1303.5632 [astro-ph.SR]. https://doi.org/10.1051/
+0004-6361/201219058
+[54] Gaia Collaboration, Brown, A.G.A., Vallenari, A., Prusti, T., de Brui-
+jne, J.H.J., Babusiaux, C., Biermann, M., Creevey, O.L., Evans, D.W.,
+Eyer, L., Hutton, A., Jansen, F., Jordi, C., Klioner, S.A., Lammers, U.,
+Lindegren, L., Luri, X., Mignard, F., Panem, C., Pourbaix, D., Randich,
+S., Sartoretti, P., Soubiran, C., Walton, N.A., Arenou, F., Bailer-Jones,
+C.A.L., Bastian, U., Cropper, M., Drimmel, R., Katz, D., Lattanzi, M.G.,
+van Leeuwen, F., Bakker, J., Cacciari, C., Casta˜neda, J., De Angeli, F.,
+Ducourant, C., Fabricius, C., Fouesneau, M., Fr´emat, Y., Guerra, R.,
+Guerrier, A., Guiraud, J., Jean-Antoine Piccolo, A., Masana, E., Messi-
+neo, R., Mowlavi, N., Nicolas, C., Nienartowicz, K., Pailler, F., Panuzzo,
+P., Riclet, F., Roux, W., Seabroke, G.M., Sordo, R., Tanga, P., Th´evenin,
+F., Gracia-Abril, G., Portell, J., Teyssier, D., Altmann, M., Andrae, R.,
+Bellas-Velidis, I., Benson, K., Berthier, J., Blomme, R., Brugaletta, E.,
+Burgess, P.W., Busso, G., Carry, B., Cellino, A., Cheek, N., Clementini,
+G., Damerdji, Y., Davidson, M., Delchambre, L., Dell’Oro, A., Fern´andez-
+Hern´andez, J., Galluccio, L., Garc´ıa-Lario, P., Garcia-Reinaldos, M.,
+Gonz´alez-N´u˜nez, J., Gosset, E., Haigron, R., Halbwachs, J.-L., Hambly,
+N.C., Harrison, D.L., Hatzidimitriou, D., Heiter, U., Hern´andez, J., Hes-
+troffer, D., Hodgkin, S.T., Holl, B., Janßen, K., Jevardat de Fombelle,
+G., Jordan, S., Krone-Martins, A., Lanzafame, A.C., L¨offler, W., Lorca,
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+39
+A., Manteiga, M., Marchal, O., Marrese, P.M., Moitinho, A., Mora,
+A., Muinonen, K., Osborne, P., Pancino, E., Pauwels, T., Petit, J.-M.,
+Recio-Blanco, A., Richards, P.J., Riello, M., Rimoldini, L., Robin, A.C.,
+Roegiers, T., Rybizki, J., Sarro, L.M., Siopis, C., Smith, M., Sozzetti, A.,
+Ulla, A., Utrilla, E., van Leeuwen, M., van Reeven, W., Abbas, U., Abreu
+Aramburu, A., Accart, S., Aerts, C., Aguado, J.J., Ajaj, M., Altavilla,
+G., ´Alvarez, M.A., ´Alvarez Cid-Fuentes, J., Alves, J., Anderson, R.I.,
+Anglada Varela, E., Antoja, T., Audard, M., Baines, D., Baker, S.G.,
+Balaguer-N´u˜nez, L., Balbinot, E., Balog, Z., Barache, C., Barbato, D.,
+Barros, M., Barstow, M.A., Bartolom´e, S., Bassilana, J.-L., Bauchet, N.,
+Baudesson-Stella, A., Becciani, U., Bellazzini, M., Bernet, M., Bertone,
+S., Bianchi, L., Blanco-Cuaresma, S., Boch, T., Bombrun, A., Bossini,
+D., Bouquillon, S., Bragaglia, A., Bramante, L., Breedt, E., Bressan, A.,
+Brouillet, N., Bucciarelli, B., Burlacu, A., Busonero, D., Butkevich, A.G.,
+Buzzi, R., Caffau, E., Cancelliere, R., C´anovas, H., Cantat-Gaudin, T.,
+Carballo, R., Carlucci, T., Carnerero, M.I., Carrasco, J.M., Casamiquela,
+L., Castellani, M., Castro-Ginard, A., Castro Sampol, P., Chaoul, L.,
+Charlot, P., Chemin, L., Chiavassa, A., Cioni, M.-R.L., Comoretto, G.,
+Cooper, W.J., Cornez, T., Cowell, S., Crifo, F., Crosta, M., Crowley,
+C., Dafonte, C., Dapergolas, A., David, M., David, P., de Laverny, P.,
+De Luise, F., De March, R., De Ridder, J., de Souza, R., de Teodoro,
+P., de Torres, A., del Peloso, E.F., del Pozo, E., Delbo, M., Delgado,
+A., Delgado, H.E., Delisle, J.-B., Di Matteo, P., Diakite, S., Diener, C.,
+Distefano, E., Dolding, C., Eappachen, D., Edvardsson, B., Enke, H.,
+Esquej, P., Fabre, C., Fabrizio, M., Faigler, S., Fedorets, G., Fernique, P.,
+Fienga, A., Figueras, F., Fouron, C., Fragkoudi, F., Fraile, E., Franke, F.,
+Gai, M., Garabato, D., Garcia-Gutierrez, A., Garc´ıa-Torres, M., Garo-
+falo, A., Gavras, P., Gerlach, E., Geyer, R., Giacobbe, P., Gilmore, G.,
+Girona, S., Giuffrida, G., Gomel, R., Gomez, A., Gonzalez-Santamaria,
+I., Gonz´alez-Vidal, J.J., Granvik, M., Guti´errez-S´anchez, R., Guy, L.P.,
+Hauser, M., Haywood, M., Helmi, A., Hidalgo, S.L., Hilger, T., H�ladczuk,
+N., Hobbs, D., Holland, G., Huckle, H.E., Jasniewicz, G., Jonker, P.G.,
+Juaristi Campillo, J., Julbe, F., Karbevska, L., Kervella, P., Khanna,
+S., Kochoska, A., Kontizas, M., Kordopatis, G., Korn, A.J., Kostrzewa-
+Rutkowska, Z., Kruszy´nska, K., Lambert, S., Lanza, A.F., Lasne, Y., Le
+Campion, J.-F., Le Fustec, Y., Lebreton, Y., Lebzelter, T., Leccia, S.,
+Leclerc, N., Lecoeur-Taibi, I., Liao, S., Licata, E., Lindstrøm, E.P., Lis-
+ter, T.A., Livanou, E., Lobel, A., Madrero Pardo, P., Managau, S., Mann,
+R.G., Marchant, J.M., Marconi, M., Marcos Santos, M.M.S., Marinoni,
+S., Marocco, F., Marshall, D.J., Martin Polo, L., Mart´ın-Fleitas, J.M.,
+Masip, A., Massari, D., Mastrobuono-Battisti, A., Mazeh, T., McMil-
+lan, P.J., Messina, S., Michalik, D., Millar, N.R., Mints, A., Molina,
+D., Molinaro, R., Moln´ar, L., Montegriffo, P., Mor, R., Morbidelli, R.,
+Morel, T., Morris, D., Mulone, A.F., Munoz, D., Muraveva, T., Mur-
+phy, C.P., Musella, I., Noval, L., Ord´enovic, C., Orr`u, G., Osinde, J.,
+
+Springer Nature 2021 LATEX template
+40
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+Pagani, C., Pagano, I., Palaversa, L., Palicio, P.A., Panahi, A., Pawlak,
+M., Pe˜nalosa Esteller, X., Penttil¨a, A., Piersimoni, A.M., Pineau, F.-X.,
+Plachy, E., Plum, G., Poggio, E., Poretti, E., Poujoulet, E., Prˇsa, A.,
+Pulone, L., Racero, E., Ragaini, S., Rainer, M., Raiteri, C.M., Rambaux,
+N., Ramos, P., Ramos-Lerate, M., Re Fiorentin, P., Regibo, S., Reyl´e, C.,
+Ripepi, V., Riva, A., Rixon, G., Robichon, N., Robin, C., Roelens, M.,
+Rohrbasser, L., Romero-G´omez, M., Rowell, N., Royer, F., Rybicki, K.A.,
+Sadowski, G., Sagrist`a Sell´es, A., Sahlmann, J., Salgado, J., Salguero, E.,
+Samaras, N., Sanchez Gimenez, V., Sanna, N., Santove˜na, R., Sarasso,
+M., Schultheis, M., Sciacca, E., Segol, M., Segovia, J.C., S´egransan, D.,
+Semeux, D., Shahaf, S., Siddiqui, H.I., Siebert, A., Siltala, L., Slezak, E.,
+Smart, R.L., Solano, E., Solitro, F., Souami, D., Souchay, J., Spagna,
+A., Spoto, F., Steele, I.A., Steidelm¨uller, H., Stephenson, C.A., S¨uveges,
+M., Szabados, L., Szegedi-Elek, E., Taris, F., Tauran, G., Taylor, M.B.,
+Teixeira, R., Thuillot, W., Tonello, N., Torra, F., Torra, J., Turon, C.,
+Unger, N., Vaillant, M., van Dillen, E., Vanel, O., Vecchiato, A., Viala,
+Y., Vicente, D., Voutsinas, S., Weiler, M., Wevers, T., Wyrzykowski,
+�L., Yoldas, A., Yvard, P., Zhao, H., Zorec, J., Zucker, S., Zurbach, C.,
+Zwitter, T.: Gaia Early Data Release 3. Summary of the contents and
+survey properties. A&A 649, 1 (2021) arXiv:2012.01533 [astro-ph.GA].
+https://doi.org/10.1051/0004-6361/202039657
+[55] Rigby, J., Perrin, M., McElwain, M., Kimble, R., Friedman, S., Lallo,
+M., Doyon, R., Feinberg, L., Ferruit, P., Glasse, A., Rieke, M., Rieke, G.,
+Wright, G., Willott, C., Colon, K., Milam, S., Neff, S., Stark, C., Valenti,
+J., Abell, J., Abney, F., Abul-Huda, Y., Acton, D.S., Adams, E., Adler,
+D., Aguilar, J., Ahmed, N., Albert, L., Alberts, S., Aldridge, D., Allen,
+M., Altenburg, M., Alvarez Marquez, J., Alves de Oliveira, C., Andersen,
+G., Anderson, H., Anderson, S., Argyriou, I., Armstrong, A., Arribas, S.,
+Artigau, E., Arvai, A., Atkinson, C., Bacon, G., Bair, T., Banks, K., Bar-
+rientes, J., Barringer, B., Bartosik, P., Bast, W., Baudoz, P., Beatty, T.,
+Bechtold, K., Beck, T., Bergeron, E., Bergkoetter, M., Bhatawdekar, R.,
+Birkmann, S., Blazek, R., Blome, C., Boccaletti, A., Boeker, T., Boia, J.,
+Bonaventura, N., Bond, N., Bosley, K., Boucarut, R., Bourque, M., Bouw-
+man, J., Bower, G., Bowers, C., Boyer, M., Bradley, L., Brady, G., Braun,
+H., Breda, D., Bresnahan, P., Bright, S., Britt, C., Bromenschenkel, A.,
+Brooks, B., Brooks, K., Brown, B., Brown, M., Brown, P., Bunker, A.,
+Burger, M., Bushouse, H., Cale, S., Cameron, A., Cameron, P., Canipe, A.,
+Caplinger, J., Caputo, F., Cara, M., Carey, L., Carniani, S., Carrasquilla,
+M., Carruthers, M., Case, M., Catherine, R., Chance, D., Chapman, G.,
+Charlot, S., Charlow, B., Chayer, P., Chen, B., Cherinka, B., Chichester,
+S., Chilton, Z., Chonis, T., Clampin, M., Clark, C., Clark, K., Coe, D.,
+Coleman, B., Comber, B., Comeau, T., Connolly, D., Cooper, J., Cooper,
+R., Coppock, E., Correnti, M., Cossou, C., Coulais, A., Coyle, L., Cracraft,
+M., Curti, M., Cuturic, S., Davis, K., Davis, M., Dean, B., DeLisa, A.,
+deMeester, W., Dencheva, N., Dencheva, N., DePasquale, J., Deschenes,
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+41
+J., Hunor Detre, ¨O., Diaz, R., Dicken, D., DiFelice, A., Dillman, M.,
+Dixon, W., Doggett, J., Donaldson, T., Douglas, R., DuPrie, K., Dupuis,
+J., Durning, J., Easmin, N., Eck, W., Edeani, C., Egami, E., Ehrenwin-
+kler, R., Eisenhamer, J., Eisenhower, M., Elie, M., Elliott, J., Elliott, K.,
+Ellis, T., Engesser, M., Espinoza, N., Etienne, O., Etxaluze, M., Falini,
+P., Feeney, M., Ferry, M., Filippazzo, J., Fincham, B., Fix, M., Flagey,
+N., Florian, M., Flynn, J., Fontanella, E., Ford, T., Forshay, P., Fox, O.,
+Franz, D., Fu, H., Fullerton, A., Galkin, S., Galyer, A., Garcia Marin, M.,
+Gardner, J., Gardner, L., Garland, D., Garrett, B., Gasman, D., Gaspar,
+A., Gaudreau, D., Gauthier, P., Geers, V., Geithner, P., Gennaro, M., Gia-
+rdino, G., Girard, J., Giuliano, M., Glassmire, K., Glauser, A., Glazer, S.,
+Godfrey, J., Golimowski, D., Gollnitz, D., Gong, F., Gonzaga, S., Gordon,
+M., Gordon, K., Goudfrooij, P., Greene, T., Greenhouse, M., Grimaldi, S.,
+Groebner, A., Grundy, T., Guillard, P., Gutman, I., Ha, K.Q., Haderlein,
+P., Hagedorn, A., Hainline, K., Haley, C., Hami, M., Hamilton, F., Ham-
+mel, H., Hansen, C., Harkins, T., Harr, M., Hart, J., Hart, Q., Hartig, G.,
+Hashimoto, R., Haskins, S., Hathaway, W., Havey, K., Hayden, B., Hecht,
+K., Heller-Boyer, C., Henriques, C., Henry, A., Hermann, K., Hernandez,
+S., Hesman, B., Hicks, B., Hilbert, B., Hines, D., Hoffman, M., Holfeltz,
+S., Holler, B.J., Hoppa, J., Hott, K., Howard, J., Howard, R., Hunter, A.,
+Hunter, D., Hurst, B., Husemann, B., Hustak, L., Ilinca Ignat, L., Illing-
+worth, G., Irish, S., Jackson, W., Jahromi, A., Jakobsen, P., James, L.,
+James, B., Januszewski, W., Jenkins, A., Jirdeh, H., Johnson, P., Johnson,
+T., Jones, V., Jones, R., Jones, D., Jones, O., Jordan, I., Jordan, M., Jur-
+czyk, S., Jurling, A., Kaleida, C., Kalmanson, P., Kammerer, J., Kang, H.,
+Kao, S.-H., Karakla, D., Kavanagh, P., Kelly, D., Kendrew, S., Kennedy,
+H., Kenny, D., Keski-kuha, R., Keyes, C., Kidwell, R., Kinzel, W., Kirk,
+J., Kirkpatrick, M., Kirshenblat, D., Klaassen, P., Knapp, B., Knight,
+J.S., Knollenberg, P., Koehler, R., Koekemoer, A., Kovacs, A., Kulp, T.,
+Kumari, N., Kyprianou, M., La Massa, S., Labador, A., Labiano Ortega,
+A., Lagage, P.-O., Lajoie, C.-P., Lallo, M., Lam, M., Lamb, T., Lam-
+bros, S., Lampenfield, R., Langston, J., Larson, K., Law, D., Lawrence,
+J., Lee, D., Leisenring, J., Lepo, K., Leveille, M., Levenson, N., Levine,
+M., Levy, Z., Lewis, D., Lewis, H., Libralato, M., Lightsey, P., Link, M.,
+Liu, L., Lo, A., Lockwood, A., Logue, R., Long, C., Long, D., Loomis,
+C., Lopez-Caniego, M., Alvarez, J.L., Love-Pruitt, J., Lucy, A., Luetz-
+gendorf, N., Maghami, P., Maiolino, R., Major, M., Malla, S., Malumuth,
+E., Manjavacas, E., Mannfolk, C., Marrione, A., Marston, A., Martel, A.,
+Maschmann, M., Masci, G., Masciarelli, M., Maszkiewicz, M., Mather,
+J., McKenzie, K., McLean, B., McMaster, M., Melbourne, K., Mel´endez,
+M., Menzel, M., Merz, K., Meyett, M., Meza, L., Miskey, C., Misselt,
+K., Moller, C., Morrison, J., Morse, E., Moseley, H., Mosier, G., Moun-
+tain, M., Mueckay, J., Mueller, M., Mullally, S., Murphy, J., Murray, K.,
+Murray, C., Mustelier, D., Muzerolle, J., Mycroft, M., Myers, R., Myrick,
+K., Nanavati, S., Nance, E., Nayak, O., Naylor, B., Nelan, E., Nickson,
+
+Springer Nature 2021 LATEX template
+42
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+B., Nielson, A., Nieto-Santisteban, M., Nikolov, N., Noriega-Crespo, A.,
+O’Shaughnessy, B., O’Sullivan, B., Ochs, W., Ogle, P., Oleszczuk, B.,
+Olmsted, J., Osborne, S., Ottens, R., Owens, B., Pacifici, C., Pagan, A.,
+Page, J., Park, S., Parrish, K., Patapis, P., Paul, L., Pauly, T., Pavlovsky,
+C., Pedder, A., Peek, M., Pena-Guerrero, M., Pennanen, K., Perez, Y.,
+Perna, M., Perriello, B., Phillips, K., Pietraszkiewicz, M., Pinaud, J.-
+P., Pirzkal, N., Pitman, J., Piwowar, A., Platais, V., Player, D., Plesha,
+R., Pollizi, J., Polster, E., Pontoppidan, K., Porterfield, B., Proffitt, C.,
+Pueyo, L., Pulliam, C., Quirt, B., Quispe Neira, I., Ramos Alarcon, R.,
+Ramsay, L., Rapp, G., Rapp, R., Rauscher, B., Ravindranath, S., Rawle,
+T., Regan, M., Reichard, T.A., Reis, C., Ressler, M.E., Rest, A., Reynolds,
+P., Rhue, T., Richon, K., Rickman, E., Ridgaway, M., Ritchie, C., Rix, H.-
+W., Robberto, M., Robinson, G., Robinson, M., Robinson, O., Rock, F.,
+Rodriguez, D., Rodriguez Del Pino, B., Roellig, T., Rohrbach, S., Roman,
+A., Romelfanger, F., Rose, P., Roteliuk, A., Roth, M., Rothwell, B., Row-
+lands, N., Roy, A., Royer, P., Royle, P., Rui, C., Rumler, P., Runnels, J.,
+Russ, M., Rustamkulov, Z., Ryden, G., Ryer, H., Sabata, M., Sabatke, D.,
+Sabbi, E., Samuelson, B., Sapp, B., Sappington, B., Sargent, B., Sauer,
+A., Scheithauer, S., Schlawin, E., Schlitz, J., Schmitz, T., Schneider, A.,
+Schreiber, J., Schulze, V., Schwab, R., Scott, J., Sembach, K., Shanahan,
+C., Shaughnessy, B., Shaw, R., Shawger, N., Shay, C., Sheehan, E., Shen,
+S., Sherman, A., Shiao, B., Shih, H.-Y., Shivaei, I., Sienkiewicz, M., Sing,
+D., Sirianni, M., Sivaramakrishnan, A., Skipper, J., Sloan, G., Slocum, C.,
+Slowinski, S., Smith, E., Smith, E., Smith, D., Smith, C., Snyder, G., Soh,
+W., Sohn, T., Soto, C., Spencer, R., Stallcup, S., Stansberry, J., Starr, C.,
+Starr, E., Stewart, A., Stiavelli, M., Straughn, A., Strickland, D., Stys, J.,
+Summers, F., Sun, F., Sunnquist, B., Swade, D., Swam, M., Swaters, R.,
+Swoish, R., Taylor, J.M., Taylor, R., Te Plate, M., Tea, M., Teague, K.,
+Telfer, R., Temim, T., Thatte, D., Thompson, C., Thompson, L., Thom-
+son, S., Tikkanen, T., Tippet, W., Todd, C., Toolan, S., Tran, H., Trejo,
+E., Truong, J., Tsukamoto, C., Tustain, S., Tyra, H., Ubeda, L., Under-
+wood, K., Uzzo, M., Van Campen, J., Vandal, T., Vandenbussche, B.,
+Vila, B., Volk, K., Wahlgren, G., Waldman, M., Walker, C., Wander, M.,
+Warfield, C., Warner, G., Wasiak, M., Watkins, M., Weaver, A., Weilert,
+M., Weiser, N., Weiss, B., Weissman, S., Welty, A., West, G., Wheate,
+L., Wheatley, E., Wheeler, T., White, R., Whiteaker, K., Whitehouse, P.,
+Whiteleather, J., Whitman, W., Williams, C., Willmer, C., Willoughby,
+S., Wilson, A., Wirth, G., Wislowski, E., Wolf, E., Wolfe, D., Wolff, S.,
+Workman, B., Wright, R., Wu, C., Wu, R., Wymer, K., Yates, K., Yeager,
+C., Yeates, J., Yerger, E., Yoon, J., Young, A., Yu, S., Zak, D., Zeidler,
+P., Zhou, J., Zielinski, T., Zincke, C., Zonak, S.: The Science Performance
+of JWST as Characterized in Commissioning. arXiv e-prints, 2207–05632
+(2022) arXiv:2207.05632 [astro-ph.IM]
+[56] Speagle, J.S.: DYNESTY: a dynamic nested sampling package for estimat-
+ing Bayesian posteriors and evidences. MNRAS 493(3), 3132–3158 (2020)
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+43
+arXiv:1904.02180 [astro-ph.IM]. https://doi.org/10.1093/mnras/staa278
+[57] Skilling, J.: Nested Sampling. In: Fischer, R., Preuss, R., Toussaint,
+U.V. (eds.) Bayesian Inference and Maximum Entropy Methods in Sci-
+ence and Engineering: 24th International Workshop on Bayesian Inference
+and Maximum Entropy Methods in Science and Engineering. Ameri-
+can Institute of Physics Conference Series, vol. 735, pp. 395–405 (2004).
+https://doi.org/10.1063/1.1835238
+[58] Chen, J., Kipping, D.: Probabilistic Forecasting of the Masses and Radii
+of Other Worlds. ApJ 834(1), 17 (2017) arXiv:1603.08614 [astro-ph.EP].
+https://doi.org/10.3847/1538-4357/834/1/17
+[59] Turbet, M., Ehrenreich, D., Lovis, C., Bolmont, E., Fauchez, T.: The
+runaway greenhouse radius inflation effect. An observational diagnostic to
+probe water on Earth-sized planets and test the habitable zone concept.
+A&A 628, 12 (2019) arXiv:1906.03527 [astro-ph.EP]. https://doi.org/10.
+1051/0004-6361/201935585
+[60] Batalha, N.E., Lewis, T., Fortney, J.J., Batalha, N.M., Kempton, E.,
+Lewis, N.K., Line, M.R.: The Precision of Mass Measurements Required
+for Robust Atmospheric Characterization of Transiting Exoplanets. ApJL
+885(1), 25 (2019) arXiv:1910.00076 [astro-ph.EP]. https://doi.org/10.
+3847/2041-8213/ab4909
+[61] Line, M.R., Yung, Y.L.: A Systematic Retrieval Analysis of Secondary
+Eclipse Spectra. III. Diagnosing Chemical Disequilibrium in Planetary
+Atmospheres. ApJ 779, 3 (2013) arXiv:1309.6679 [astro-ph.EP]. https:
+//doi.org/10.1088/0004-637X/779/1/3
+[62] Line, M.R., Knutson, H., Wolf, A.S., Yung, Y.L.: A Systematic Retrieval
+Analysis of Secondary Eclipse Spectra. II. A Uniform Analysis of Nine
+Planets and their C to O Ratios. ApJ 783, 70 (2014) arXiv:1309.6663
+[astro-ph.EP]. https://doi.org/10.1088/0004-637X/783/2/70
+[63] McBride, B.J., Gordon, S.: Computer program for calculation of complex
+chemical equilibrium compositions and applications ii. user’s manual and
+program description. Technical report, NASA (1996)
+[64] Guillot, T.: On the radiative equilibrium of irradiated planetary atmo-
+spheres. A&A 520, 27 (2010) arXiv:1006.4702 [astro-ph.EP]. https://doi.
+org/10.1051/0004-6361/200913396
+[65] Freedman, R.S., Marley, M.S., Lodders, K.: Line and Mean Opacities
+for Ultracool Dwarfs and Extrasolar Planets. ApJS 174, 504–513 (2008)
+0706.2374
+
+Springer Nature 2021 LATEX template
+44
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+[66] Freedman, R.S., Lustig-Yaeger, J., Fortney, J.J., Lupu, R.E., Marley,
+M.S., Lodders, K.: Gaseous Mean Opacities for Giant Planet and Ultra-
+cool Dwarf Atmospheres over a Range of Metallicities and Temperatures.
+ApJS 214, 25 (2014) arXiv:1409.0026 [astro-ph.EP]. https://doi.org/10.
+1088/0067-0049/214/2/25
+[67] Batalha, N., Freedman, R., Lupu, R., Marley, M.: Resampled Opac-
+ity Database for PICASO V2. https://doi.org/10.5281/zenodo.3759675.
+https://doi.org/10.5281/zenodo.3759675
+[68] Lustig-Yaeger,
+J.:
+The
+detection,
+characterization,
+and
+retrieval
+of
+terrestrial
+exoplanet
+atmospheres.
+PhD
+thesis,
+University
+of
+Washington
+(2020).
+https://www.proquest.com/dissertations-theses/
+detection-characterization-retrieval-terrestrial/docview/2457714855/
+se-2?accountid=11752
+[69] Lustig-Yaeger, J., Sotzen, K.S., Stevenson, K.B., Luger, R., May,
+E.M., Mayorga, L.C., Mandt, K., Izenberg, N.R.: Hierarchical Bayesian
+Atmospheric Retrieval Modeling for Population Studies of Exoplanet
+Atmospheres: A Case Study on the Habitable Zone. AJ 163(3),
+140 (2022) arXiv:2202.00701 [astro-ph.EP]. https://doi.org/10.3847/
+1538-3881/ac5034
+[70] Meadows, V.S., Crisp, D.: Ground-based near-infrared observations of
+the Venus nightside: The thermal structure and water abundance near
+the surface. J. Geophys. Res. 101, 4595–4622 (1996). https://doi.org/10.
+1029/95JE03567
+[71] Gordon, I.E., Rothman, L.S., Hill, C., Kochanov, R.V., Tan, Y., Bernath,
+P.F., Birk, M., Boudon, V., Campargue, A., Chance, K.V., Drouin, B.J.,
+Flaud, J.-M., Gamache, R.R., Hodges, J.T., Jacquemart, D., Perevalov,
+V.I., Perrin, A., Shine, K.P., Smith, M.-A.H., Tennyson, J., Toon, G.C.,
+Tran, H., Tyuterev, V.G., Barbe, A., Cs´asz´ar, A.G., Devi, V.M., Furten-
+bacher, T., Harrison, J.J., Hartmann, J.-M., Jolly, A., Johnson, T.J.,
+Karman, T., Kleiner, I., Kyuberis, A.A., Loos, J., Lyulin, O.M., Massie,
+S.T., Mikhailenko, S.N., Moazzen-Ahmadi, N., M¨uller, H.S.P., Naumenko,
+O.V., Nikitin, A.V., Polyansky, O.L., Rey, M., Rotger, M., Sharpe,
+S.W., Sung, K., Starikova, E., Tashkun, S.A., Auwera, J.V., Wagner, G.,
+Wilzewski, J., Wcis�lo, P., Yu, S., Zak, E.J.: The HITRAN2016 molecu-
+lar spectroscopic database. JQSRT 203, 3–69 (2017). https://doi.org/10.
+1016/j.jqsrt.2017.06.038
+[72] MacDonald, R.J., Madhusudhan, N.: HD 209458b in new light: evi-
+dence of nitrogen chemistry, patchy clouds and sub-solar water. MNRAS
+469(2), 1979–1996 (2017) arXiv:1701.01113 [astro-ph.EP]. https://doi.
+org/10.1093/mnras/stx804
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+45
+[73] Kaltenegger, L., MacDonald, R.J., Kozakis, T., Lewis, N.K., Mama-
+jek,
+E.E.,
+McDowell,
+J.C.,
+Vanderburg,
+A.:
+The
+White
+Dwarf
+Opportunity:
+Robust
+Detections
+of
+Molecules
+in
+Earth-like
+Exo-
+planet Atmospheres with the James Webb Space Telescope. ApJL
+901(1), 1 (2020) arXiv:2009.07274 [astro-ph.EP]. https://doi.org/10.
+3847/2041-8213/aba9d3
+[74] Lin, Z., MacDonald, R.J., Kaltenegger, L., Wilson, D.J.: Differentiating
+modern and prebiotic Earth scenarios for TRAPPIST-1e: high-resolution
+transmission spectra and predictions for JWST. MNRAS 505(3), 3562–
+3578 (2021) arXiv:2105.09319 [astro-ph.EP]. https://doi.org/10.1093/
+mnras/stab1486
+[75] MacDonald, R.J., Lewis, N.K.: TRIDENT: A Rapid 3D Radiative-
+transfer
+Model
+for
+Exoplanet
+Transmission
+Spectra.
+ApJ
+929(1),
+20
+(2022)
+arXiv:2111.05862
+[astro-ph.EP].
+https://doi.org/10.3847/
+1538-4357/ac47fe
+[76] Feroz, F., Hobson, M.P., Bridges, M.: MULTINEST: an efficient and
+robust Bayesian inference tool for cosmology and particle physics.
+MNRAS 398(4), 1601–1614 (2009) arXiv:0809.3437 [astro-ph]. https:
+//doi.org/10.1111/j.1365-2966.2009.14548.x
+[77] Buchner, J., Georgakakis, A., Nandra, K., Hsu, L., Rangel, C., Brightman,
+M., Merloni, A., Salvato, M., Donley, J., Kocevski, D.: X-ray spectral
+modelling of the AGN obscuring region in the CDFS: Bayesian model
+selection and catalogue. A&A 564, 125 (2014) arXiv:1402.0004 [astro-
+ph.HE]. https://doi.org/10.1051/0004-6361/201322971
+[78] Benneke,
+B.,
+Seager,
+S.:
+Atmospheric
+Retrieval
+for
+Super-Earths:
+Uniquely Constraining the Atmospheric Composition with Transmission
+Spectroscopy. ApJ 753(2), 100 (2012) arXiv:1203.4018 [astro-ph.EP].
+https://doi.org/10.1088/0004-637X/753/2/100
+[79] Aitchison, J.: The Statistical Analysis of Compositional Data. Mono-
+graphs on Statistics and Applied Probability. Springer, ??? (1986)
+[80] Astropy Collaboration, Robitaille, T.P., Tollerud, E.J., Greenfield, P.,
+Droettboom, M., Bray, E., Aldcroft, T., Davis, M., Ginsburg, A., Price-
+Whelan, A.M., Kerzendorf, W.E., Conley, A., Crighton, N., Barbary, K.,
+Muna, D., Ferguson, H., Grollier, F., Parikh, M.M., Nair, P.H., Unther,
+H.M., Deil, C., Woillez, J., Conseil, S., Kramer, R., Turner, J.E.H.,
+Singer, L., Fox, R., Weaver, B.A., Zabalza, V., Edwards, Z.I., Azalee
+Bostroem, K., Burke, D.J., Casey, A.R., Crawford, S.M., Dencheva, N.,
+Ely, J., Jenness, T., Labrie, K., Lim, P.L., Pierfederici, F., Pontzen, A.,
+Ptak, A., Refsdal, B., Servillat, M., Streicher, O.: Astropy: A commu-
+nity Python package for astronomy. A&A 558, 33 (2013) arXiv:1307.6212
+
+Springer Nature 2021 LATEX template
+46
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+[astro-ph.IM]. https://doi.org/10.1051/0004-6361/201322068
+[81] Astropy Collaboration, Price-Whelan, A.M., Sip˝ocz, B.M., G¨unther,
+H.M., Lim, P.L., Crawford, S.M., Conseil, S., Shupe, D.L., Craig, M.W.,
+Dencheva, N., Ginsburg, A., Vand erPlas, J.T., Bradley, L.D., P´erez-
+Su´arez, D., de Val-Borro, M., Aldcroft, T.L., Cruz, K.L., Robitaille,
+T.P., Tollerud, E.J., Ardelean, C., Babej, T., Bach, Y.P., Bachetti, M.,
+Bakanov, A.V., Bamford, S.P., Barentsen, G., Barmby, P., Baumbach,
+A., Berry, K.L., Biscani, F., Boquien, M., Bostroem, K.A., Bouma, L.G.,
+Brammer, G.B., Bray, E.M., Breytenbach, H., Buddelmeijer, H., Burke,
+D.J., Calderone, G., Cano Rodr´ıguez, J.L., Cara, M., Cardoso, J.V.M.,
+Cheedella, S., Copin, Y., Corrales, L., Crichton, D., D’Avella, D., Deil,
+C., Depagne, ´E., Dietrich, J.P., Donath, A., Droettboom, M., Earl, N.,
+Erben, T., Fabbro, S., Ferreira, L.A., Finethy, T., Fox, R.T., Garri-
+son, L.H., Gibbons, S.L.J., Goldstein, D.A., Gommers, R., Greco, J.P.,
+Greenfield, P., Groener, A.M., Grollier, F., Hagen, A., Hirst, P., Home-
+ier, D., Horton, A.J., Hosseinzadeh, G., Hu, L., Hunkeler, J.S., Ivezi´c,
+ˇZ., Jain, A., Jenness, T., Kanarek, G., Kendrew, S., Kern, N.S., Kerzen-
+dorf, W.E., Khvalko, A., King, J., Kirkby, D., Kulkarni, A.M., Kumar,
+A., Lee, A., Lenz, D., Littlefair, S.P., Ma, Z., Macleod, D.M., Mas-
+tropietro, M., McCully, C., Montagnac, S., Morris, B.M., Mueller, M.,
+Mumford, S.J., Muna, D., Murphy, N.A., Nelson, S., Nguyen, G.H., Ninan,
+J.P., N¨othe, M., Ogaz, S., Oh, S., Parejko, J.K., Parley, N., Pascual,
+S., Patil, R., Patil, A.A., Plunkett, A.L., Prochaska, J.X., Rastogi, T.,
+Reddy Janga, V., Sabater, J., Sakurikar, P., Seifert, M., Sherbert, L.E.,
+Sherwood-Taylor, H., Shih, A.Y., Sick, J., Silbiger, M.T., Singanamalla,
+S., Singer, L.P., Sladen, P.H., Sooley, K.A., Sornarajah, S., Streicher,
+O., Teuben, P., Thomas, S.W., Tremblay, G.R., Turner, J.E.H., Terr´on,
+V., van Kerkwijk, M.H., de la Vega, A., Watkins, L.L., Weaver, B.A.,
+Whitmore, J.B., Woillez, J., Zabalza, V., Astropy Contributors: The
+Astropy Project: Building an Open-science Project and Status of the v2.0
+Core Package. AJ 156(3), 123 (2018) arXiv:1801.02634 [astro-ph.IM].
+https://doi.org/10.3847/1538-3881/aabc4f
+[82] Bourque, M., Espinoza, N., Filippazzo, J., Fix, M., King, T., Martlin,
+C., Medina, J., Batalha, N., Fox, M., Fowler, J., Fraine, J., Hill, M.,
+Lewis, N., Stevenson, K., Valenti, J., Wakeford, H.: The Exoplanet Char-
+acterization Toolkit (ExoCTK). https://doi.org/10.5281/zenodo.4556063.
+https://doi.org/10.5281/zenodo.4556063
+[83] P´erez, F., Granger, B.E.: IPython: a system for interactive scientific
+computing. Computing in Science and Engineering 9(3), 21–29 (2007).
+https://doi.org/10.1109/MCSE.2007.53
+[84] Hunter, J.D.: Matplotlib: A 2d graphics environment. Computing in
+Science Engineering 9(3), 90–95 (2007). https://doi.org/10.1109/MCSE.
+
+Springer Nature 2021 LATEX template
+Lustig-Yaeger & Fu et al. — LHS 475b with JWST
+47
+2007.55
+[85] van der Walt, S., Colbert, S.C., Varoquaux, G.: The numpy array:
+A structure for efficient numerical computation. Computing in Science
+Engineering 13(2), 22–30 (2011). https://doi.org/10.1109/MCSE.2011.
+37
+[86] Harris, C.R., Millman, K.J., van der Walt, S.J., Gommers, R., Virtanen,
+P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N.J., Kern,
+R., Picus, M., Hoyer, S., van Kerkwijk, M.H., Brett, M., Haldane, A.,
+del R’ıo, J.F., Wiebe, M., Peterson, P., G’erard-Marchant, P., Sheppard,
+K., Reddy, T., Weckesser, W., Abbasi, H., Gohlke, C., Oliphant, T.E.:
+Array programming with NumPy. Nature 585(7825), 357–362 (2020).
+https://doi.org/10.1038/s41586-020-2649-2
+[87] Salvatier, J., Wieckiˆa, T.V., Fonnesbeck, C.: PyMC3: Python probabilis-
+tic programming framework. Astrophysics Source Code Library, record
+ascl:1610.016 (2016)
+[88] Virtanen, P., Gommers, R., Oliphant, T.E., Haberland, M., Reddy, T.,
+Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J.,
+van der Walt, S.J., Brett, M., Wilson, J., Jarrod Millman, K., Mayorov,
+N., Nelson, A.R.J., Jones, E., Kern, R., Larson, E., Carey, C., Polat, ˙I.,
+Feng, Y., Moore, E.W., Vand erPlas, J., Laxalde, D., Perktold, J., Cim-
+rman, R., Henriksen, I., Quintero, E.A., Harris, C.R., Archibald, A.M.,
+Ribeiro, A.H., Pedregosa, F., van Mulbregt, P., Contributors, S...: SciPy
+1.0: Fundamental Algorithms for Scientific Computing in Python. Nature
+Methods 17, 261–272 (2020). https://doi.org/10.1038/s41592-019-0686-2
+