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Starlight exerts up to 30 times the acceleration of gravity on sub-micron haze particles in hot exoplanet atmospheres, and this extra push makes the particles smaller and more dilute, steepening optical transmission slopes and strengthening

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Stellar radiation pressure markedly accelerates aerosol settling in hot exoplanets, reducing particle size and mass concentration, which steepens optical transmission slopes and increases near-infrared molecular feature amplitudes.

T0 review reviewed 2026-08-05 challenge →

load-bearing objection Radiation pressure on aerosols is a genuinely new physical idea for hot exoplanet atmospheres, and the core force-balance argument is sound; the quantitative scalings and spectral predictions are real but rest on a simplified coagulation model, so the paper deserves a serious referee but also a clear sensitivity discussion. the 3 major comments →

arxiv 2508.20175 v1 pith:DP7OSBES submitted 2025-08-27 astro-ph.EP

Aerosol dynamics on hot exoplanets: the role of radiation pressure

James E. Owen , Ruth A. Murray-Clay This is my paper
classification astro-ph.EP
keywords exoplanet atmospheresaerosolsradiation pressuretransmission spectroscopyhaze microphysicsgrowth-settling equilibriumhot Jupiterssub-Saturns
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved

The pith

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The reading

This paper argues that stellar radiation pressure—the momentum of starlight absorbed and scattered by small particles—is a leading, previously neglected force in the atmospheres of hot exoplanets. For low-density, highly irradiated planets (sub-Saturns and inflated giants), the radiative acceleration on sub-micron haze particles can exceed the planet's gravity by a factor of 10–30, so haze particles settle much faster than they would under gravity alone. In the growth-settling equilibrium the authors derive, that faster settling leaves less time for coagulation, so radiation pressure produces smaller particles with lower mass concentrations. Using analytic scalings and 2D equatorial-band simulations, the paper shows these smaller, thinner hazes steepen optical transmission slopes, make near-infrared molecular features less muted, and create asymmetric morning/evening terminator spectra. If this is right, radiation pressure is needed to interpret transmission spectra and albedos of the very planets best suited for atmospheric characterisation.

Core claim

The paper's central claim is that the ratio of radiative acceleration to planetary gravity, β_p, is typically larger than one for ~0.1–1 micron aerosols on highly irradiated giant planets, often reaching values of 10–30 (Equation 3, Figure 2). Because radiation pressure acts in the stellar direction, it adds to gravity in the settling of haze particles, raising their terminal velocity. Equating the coagulation timescale (Equation 9, assuming perfect sticking) with the settling timescale (Equation 8) gives the growth-settling equilibrium: particle size a ∝ (1+β_p)^(-2/9) and mass concentration X_p ∝ (1+β_p)^(-5/9) (Equations 10–11). Thus radiation pressure makes particles smaller and the aero

What carries the argument

The load-bearing mechanism is the radiation-pressure-to-gravity ratio β_p (Equation 2), which parametrises the extra downward acceleration on an aerosol particle. The argument then runs through the growth-settling equilibrium: the terminal settling velocity (Equation 8, Epstein drag with acceleration (1+β_p)g) and the coagulation timescale (Equation 9, ballistic Brownian collisions with perfect sticking) are equated, giving the particle size and mass concentration scalings (Equations 10–11). This equilibrium determines everything downstream: the aerosol opacity profile, the photospheric pressure, and finally the transmission spectrum. The 2D equatorial-band model (Section 3.3) carries this m

Load-bearing premise

The predictions rest on a growth-settling equilibrium in which every collision sticks and the aerosol population is described by a single representative size; if sticking is inefficient, fragmentation occurs, or the size distribution is broad, the scalings and spectral signatures would change.

What would settle it

Observe a sample of hot gas giants with homogeneous transmission spectra and measure the normalised 1.4 μm water amplitude and optical slope as a function of β_p; if planets with high β_p do not show larger water amplitudes and steeper slopes after accounting for scale height, the radiation-pressure mechanism is not the controlling factor. Alternatively, a laboratory measurement showing that soot/tholin aggregates bounce or fragment at the relevant collision speeds would falsify the perfect-sticking growth-settling equilibrium that the size scalings depend on.

Watch this falsifier. Get emailed when new claim-graph text bears on it.

If this is right

  • Microphysical models that omit radiation pressure will overestimate haze particle sizes and mass concentrations on highly irradiated planets, biasing retrievals of molecular abundances and cloud properties.
  • The paper predicts a population-level correlation: among hot gas giants, the normalised 1.4 μm water feature amplitude should increase with β_p (roughly with equilibrium temperature and inverse surface gravity), helping explain the scatter in measured feature amplitudes.
  • Morning and evening terminator spectra should differ systematically: the evening terminator is hazier, while the morning terminator has a steeper optical slope that can become super-Rayleigh under strong radiation pressure.
  • Radiation pressure can drive an outward flow of aerosols; for soot-like hazes the mass-loss rate is about 1.6% of the production rate, enough to deplete the upper-atmosphere haze precursor reservoir over the planet's lifetime unless replenished.
  • Radiation pressure narrows the haze production rates that produce high albedos, which could account for the lack of strong correlations between observed exoplanet albedos and standard planetary and stellar parameters.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The paper's scalings suggest a direct observational test: a sample of hot giant planets with well-determined masses, radii and temperatures should show normalised water-feature amplitudes increasing with β_p even after controlling for scale-height effects; current observations of separate morning/evening terminator spectra could check the predicted asymmetry direction.
  • If the same acceleration applies to condensate clouds, as the paper speculates, radiation pressure would shrink cloud particles too, potentially explaining super-Rayleigh optical slopes without invoking extremely strong vertical mixing.
  • The perfect-sticking, single-size growth-settling equilibrium is the load-bearing premise; if laboratory studies of soot/tholin aggregates find low sticking efficiencies or fragmentation, the size scaling with β_p weakens and the spectral predictions would need revision.
  • The radiative feedback loop described in Section 6.1 (smaller particles → lower opacity → hotter atmosphere → longer settling time → larger particles) could create bistable or time-variable haze states, which would appear as transit-depth variations across epochs.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit.

Referee Report

3 major / 6 minor

Summary. This paper proposes that stellar radiation pressure exerts a force on aerosol particles in hot exoplanet atmospheres that is often comparable to or larger than planetary gravity, with beta_p up to ~10-30 for low-gravity, highly irradiated planets. Assuming hazes with a monodisperse size and a growth-settling equilibrium, the authors derive analytic scalings in which radiation pressure reduces particle size and mass concentration; they then simulate haze dynamics in a 2D equatorial band with a single representative particle size, compute transmission spectra, and predict steeper optical slopes and larger near-IR molecular feature amplitudes at higher radiation pressure. They also discuss albedo effects, morning/evening terminator asymmetries, aerosol mass loss, and population-level correlations.

Significance. If the central scalings survive closer scrutiny, radiation pressure would be a genuinely new physical process for aerosol evolution on hot exoplanets, with direct consequences for the interpretation of HST and JWST transmission spectra and albedo measurements. The paper's analytic derivation is clean and does not fit observational data; the Mie opacities are computed from published laboratory optical constants; the simulation code is publicly available; and the main predictions (beta_p-driven steepening of optical slopes and stronger molecular features) are, in principle, testable with current observations. The paper is also appropriately cautious about implicit correlations between radiation pressure strength and other planetary/stellar parameters.

major comments (3)
  1. [Section 3.1, Eqs. (8)-(11)] The analytic growth-settling equilibrium treats collisions as driven only by Brownian relative motion of equal-mass particles. This assumption is not justified at the pressures and sizes of interest. For the HAT-P-65 b analogue at P*=1 microbar with beta_p=10, Eq. (8) gives settling velocities of about 6e3 cm/s for 0.1 micron grains and 1.3e4 cm/s for 0.2 micron grains, so differential settling between different-sized grains is about 6e3 cm/s, while v_BM in Eq. (9) is about 20 cm/s. Since v_BM scales as a^{-3/2} and v_set as (1+beta_p) a / rho_gas, the hierarchy worsens for larger grains and lower gas densities. Radiation pressure multiplies differential settling velocities by (1+beta_p), so the scalings in Eqs. (10)-(11), and their use in Section 5, are not demonstrated for a realistic size distribution. Please provide a quantitative validity condition for the Brownian-only regime, or g
  2. [Section 3.3-3.4, Eq. (36)] The numerical model evolves a single representative particle size per cell, yet the growth time is stated to come from Ormel & Min (2019), including differential particle drift. With only one size per cell it is unclear how the differential-drift relative velocity is evaluated; if it is evaluated between identical sizes it vanishes, and the model cannot capture the radiation-pressure-amplified differential-settling channel highlighted above. The separate treatment of freshly injected 10^-3 micron seeds (sweep-up vs. self-coagulation) addresses only the injection step, not the subsequent growth of the resident population. Please specify the assumed size distribution or effective relative velocity used in the Ormel & Min formula, and test the sensitivity of the size/concentration profiles (Figures 9, 11-12) and transmission spectra (Figures 14-16) to the single-size approximation. This is
  3. [Section 3.1, Eq. (9) and Section 6.1] The collision model assumes perfect sticking ('all collisions result in growth') and no fragmentation. Radiation pressure can produce collision velocities of order km/s at the low pressures considered, where sticking efficiencies are plausibly below unity and fragmentation or erosion may become important. This could alter the growth-settling equilibrium and the predicted size scalings. The manuscript does not discuss this channel, even though it is directly relevant to the claim that the qualitative result is robust. At minimum, the authors should state the expected collision velocities and justify the perfect-sticking assumption for the parameter range simulated.
minor comments (6)
  1. [Eq. (3)] The prefactor of 5 assumes F* = 4 sigma Teq^4 (full isotropic re-radiation) and zero albedo. State this explicitly when introducing Teq.
  2. [Figure 9 caption] The caption refers to a 'HATP-67 b analogue' while the text uses HAT-P-65 b. Please correct the typo.
  3. [Section 2.1] The text says 'HAT-P-67 b having the largest value', while the square point in Figure 2 is HAT-P-65 b. Harmonize the notation.
  4. [Eq. (40)] Please provide the fitted values of the eight alpha coefficients or a pointer to where they can be obtained; the functional form alone is not sufficient for reproduction.
  5. [Section 3.2] Define the Rayleigh index b more precisely: Qpr is proportional to (a/lambda*)^{1+b} in the small-particle limit, and state the particle size range over which this approximation is used.
  6. [Section 5.1] Specify how tau_pro is computed (wavelength band, gas and particle opacity) and how the production shut-off exp(-tau_pro) is normalized relative to Eq. (39).

Circularity Check

0 steps flagged

No significant circularity: radiation-pressure accelerations are from Mie theory, size/concentration scalings are closed-form equilibrium solutions, and spectral trends are model outputs, not fitted quantities.

full rationale

The paper's load-bearing chain is: (1) compute Qrad and opacity from optical constants via Mie theory (Section 2.1); (2) evaluate beta_p for observed planets (Eqs. 2-3, Fig. 2); (3) derive growth-settling equilibrium sizes and concentrations by equating settling time (Eq. 8, with 1+beta_p in the acceleration) to the Brownian collision time (Eq. 9), yielding Eqs. 10-11; (4) evolve a representative particle size in 2D simulations and ray-trace transmission spectra (Sections 3.3-5). None of these steps fits a parameter to the quantity it later 'predicts': the Mie-derived opacities are inputs, not regressions to the spectral slopes or feature amplitudes; Eqs. 10-11 follow algebraically from stated timescale equalities; the 1.4-micron feature amplitudes in Fig. 17 are computed from the simulated atmospheres, not used to set constants. Self-citations (e.g., Owen & Wu 2013, Owen 2020, Rogers & Owen 2021) appear only in background or discussion contexts (photoevaporation, sub-Neptune radii) and are not load-bearing for the aerosol equilibrium or spectral predictions. The acknowledged limitations in Section 6.1 (monodisperse representative size, perfect-sticking coagulation, omitted differential-settling coagulation and fractal growth) are modeling uncertainties that could change quantitative scalings, but they do not make the derivation circular. The analytic limit beta_p = 0 reproduces the known no-radiation-pressure scalings (Eqs. 17-18), confirming the formalism is a generalization rather than a renaming. Therefore no step reduces by construction to its own inputs.

Axiom & Free-Parameter Ledger

7 free parameters · 8 axioms · 0 invented entities

The paper introduces no new entities. The central physical claim rests on standard radiation pressure, Epstein drag, and coagulation physics. The main free parameters are the haze production rate and diffusivity, both explored over wide ranges. The simplifying axioms about isothermality, single particle size, and 2D geometry are acknowledged by the authors and do not invalidate the qualitative conclusions.

free parameters (7)
  • Haze production rate Sigma_dot_p = varied 10^-16 to 10^-10 g cm^-2 s^-1
    Controls aerosol abundance; explored over full plausible range.
  • Eddy diffusion coefficient K = varied 10^5 to 10^10 cm^2 s^-1
    Vertical mixing strength; explored over literature range.
  • Initial particle size = 10^-3 micron
    Newly inserted particles in the source term (Section 3.4).
  • Peak production pressure P* and width sigma* = P* = 1 microbar, sigma* = 0.5
    Shape of the log-normal source term (Eq. 39).
  • Zonal wind profile parameters = v_peak = 1 km/s, P0 = 0.09 bar, sigma_lp = 1.5, sigma_hp = 0.7
    Matches mean GCM zonal wind shape (Eq. 41); not varied.
  • Eight alpha coefficients in Eq. 40 = fitted to Mie-calculated opacities
    Computational convenience; not physical parameters fitted to observations.
  • Internal density rho_in = 1 g cm^-3
    From Lavvas et al. 2011; standard for hazes.
axioms (8)
  • domain assumption Epstein drag law applies (Knudsen number >> 1) for aerosol particles in the upper atmosphere.
    Used in Eq. 7 and throughout; valid for molecular mean free path larger than particle size at millibar pressures.
  • domain assumption Terminal velocity / short friction time approximation for settling.
    Eq. 8; acknowledged to break down at very high altitudes for strong radiation pressure, but the numerical model uses a semi-implicit update.
  • ad hoc to paper Globally isothermal atmosphere in hydrostatic equilibrium.
    Assumed in Section 3.3 and simulations; thermal feedback is discussed in Section 6.1 but not modeled.
  • domain assumption Plane-parallel incident stellar irradiation with no diffuse scattered/thermal radiation pressure.
    Eq. 37; authors estimate the scattered-light correction is at most ~15% and thermal is a few percent (Section 6.1).
  • ad hoc to paper Haze production parameterized as a log-normal in pressure, with production shut off on the night side.
    Section 3.4, Eq. 39; no nucleation model.
  • ad hoc to paper Single representative particle size (no full size distribution).
    Section 3.3; they evolve a representative size with Eq. 36.
  • domain assumption All collisions result in growth (sticking efficiency unity).
    Section 3.1: 'Assuming that all collisions result in growth'.
  • ad hoc to paper 2D equatorial band is representative of the 3D terminator; terminator distributions assumed symmetric in latitude.
    Section 5.1; follows Kempton et al. 2017.

reviewed 2026-08-05 · how reviews work

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Cite this review

Pith. "Pith review of Aerosol dynamics on hot exoplanets: the role of radiation pressure." pith.science (2026). https://pith.science/paper/DP7OSBES

@misc{pith2026250820175,
  author       = {Pith},
  title        = {Pith review of: Aerosol dynamics on hot exoplanets: the role of radiation pressure},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/DP7OSBES}},
  note         = {Machine review of arXiv:2508.20175}
}
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read the original abstract

Aerosols appear to be ubiquitous in exoplanetary atmospheres. However because our understanding of the physical processes that govern aerosols is incomplete, their presence makes the measurement of atmospheric properties, such as molecular abundance ratios, difficult. We show that aerosol particles in highly-irradiated exoplanets experience an additional acceleration due to stellar radiation pressure. The strength of this radiative acceleration often exceeds the planet's gravity and can approach values of ~10-20x gravity's for low-density planets (typically sub-Saturns) hosting ~0.1--1 micron aerosols. Since these highly irradiated, low-density planets are often the best targets for atmospheric characterisation with current instrumentation, radiation pressure is likely an important process when considering aerosol dynamics. We find that radiation pressure accelerates hazes produced by photochemistry at high altitudes to faster terminal velocities, causing them to grow more slowly. Hence, the particles are smaller and have lower mass concentrations in the presence of radiation pressure. By simulating haze-like aerosols in a 2D equatorial band model, we show that radiation pressure steepens optical slopes in transmission spectra, resulting in less muted molecular features in the Near-IR and gives rise to a correlation between the strength of radiation pressure and the molecular feature amplitude. Furthermore, the interaction of zonal winds and radiation pressure impacts both the optical slopes and amplitudes on the individual morning and evening terminators.

Figures

Figures reproduced from arXiv: 2508.20175 by James E. Owen, Ruth A. Murray-Clay.

Figure 1
Figure 1. Figure 1: (Top) Radiation pressure efficiency, 𝑄rad, as a function of particle size and stellar effective temperature, plotted for soot (solid), tholins (dotted) and silicate (Mg2SiO4, dashed) grains. (Bottom) Radiation pressure opacity. Since 𝜅rad ∝ 𝑄rad/𝑎, the strength of the radiation pressure peaks at slightly smaller particle sizes than the efficiency. Thus, we expect radiation pressure to operate most effectiv… view at source ↗
Figure 2
Figure 2. Figure 2: The population of exoplanets showing the radiative acceleration of a 0.1 𝜇m aerosol particle (soot: left panel, silicates: right panel) in their atmosphere as a function of the planet’s gravitational acceleration and equilibrium temperature. The square point highlights the planet HAT-P-65 b, whose parameters we will adopt in our later simulations. The lines indicate constant values of the ratio of the radi… view at source ↗
Figure 3
Figure 3. Figure 3: The optical depth, shown for the gas alone and for the gas and aerosols combined, and particle size as a function of altitude for no radiation pressure (left) and strong radiation pressure (𝛽𝑝 (𝑎 = 0.1 𝜇m) = 10, right). For high production rates (top row), such that the aerosols control the position of the photosphere, at high radiation pressure the lower particle density pushes the photosphere (𝜏∗ = 1) de… view at source ↗
Figure 4
Figure 4. Figure 4: The fraction of incident stellar irradiation with a wavelength of 0.5𝜇m scattered back at the sub-stellar point for different haze production rates and radiation pressure importance. The dotted line shows the line at which the gas and haze optical depths are equal at the photosphere, delineating between low and high production rates. The left panel shows tholin-like hazes, while the right panel shows soot-… view at source ↗
Figure 6
Figure 6. Figure 6: The schematic setup of our 2D equatorial band simulations, with our defined Cartesian coordinate system. The simulated band is shown in green. Aerosols with the directions of the gravitational force (red-dashed) and radiation pressure (black dotted) are shown at the substellar point, nightside and morning/evening terminator. The direction of the super-rotating wind that advects the aerosols is shown (green… view at source ↗
Figure 7
Figure 7. Figure 7: The profile of the haze production rate normalised to the maximum value. Our profile smoothly reduces the production rate towards the night￾side [PITH_FULL_IMAGE:figures/full_fig_p010_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Schematic of our ray-tracing scheme. The cell faces are shown as solid black lines representing our spherical grid. Our plane parallel rays, shown as dotted orange lines, intercept the cell faces at the orange points where the optical depth is computed. Our aerosol dynamics scheme requires knowledge of the optical depth at the centre of the cell faces in both the radial and angular directions (magenta star… view at source ↗
Figure 9
Figure 9. Figure 9: The evolution of the particle density, particle size and optical depth to stellar bolometric irradiation along the sub-stellar point for our HATP-67 b analogue. The lines are shown for different strengths of the radiation pressure, parameterised in terms of 𝛽𝑝 for a 0.1𝜇m sized particle. The points in the particle density and particle size panels show the values at an value of the optical depth, 𝜏∗ = 1. Th… view at source ↗
Figure 10
Figure 10. Figure 10 [PITH_FULL_IMAGE:figures/full_fig_p012_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: The density (left), particle size (middle) and velocity structure (right) on the day-side for simulations excluding radiation pressure (left) and including radiation pressure with a value of 𝛽𝑝 = 10 (right). The production rate is Σ¤ 𝑝 = 10−13 g cm−2 s −1 and the diffusivity is 𝐾 = 107 cm2 s −1 . The white contours show the position of 𝜏∗ = 0.1, 1.0 and 10. The vectors in the right-hand panel are normalis… view at source ↗
Figure 12
Figure 12. Figure 12: Similar to [PITH_FULL_IMAGE:figures/full_fig_p014_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: The zonal particle velocities as a function of pressure on the evening (left) and morning (right) terminators for simulations with and with￾out radiation pressure. A negative velocity indicates the flow is towards the night-side. Strong radiation pressure reverses the particle flow at high alti￾tudes on the morning terminator, causing them to flow towards the night-side instead of being advected onto the … view at source ↗
Figure 14
Figure 14. Figure 14: The optical-NIR transmission spectrum for our HAT-P-65b analogue with soot-like hazes. The left panel shows the full wavelength range, while the right panel shows a zoom-in on the 1.4𝜇m water feature. Radiation pressure produces atmospheres that appear less hazy and produce steeper slopes in the optical. The panels show an increasing haze production rate from top to bottom. temperature gradient would be m… view at source ↗
Figure 15
Figure 15. Figure 15: Same as [PITH_FULL_IMAGE:figures/full_fig_p017_15.png] view at source ↗
Figure 16
Figure 16. Figure 16: The transmission spectra are shown separately for the evening (dashed) and morning (dot-dashed) terminators, with strong radiation pressure (𝛽𝑝 = 10) and without radiation pressure. The left plot shows soot-like hazes, while the right plot shows tholin-like hazes. Haze-free spectra are shown for scale. Radiation pressure induces steeper optical scattering slopes and less hazy spectra at NIR wavelengths. T… view at source ↗
Figure 17
Figure 17. Figure 17: The normalised amplitude of the 1.4 𝜇m water feature (Equa￾tion 43) as a function of the total acceleration experienced by particles (1+𝛽𝑝) and haze production rate in g cm−2 s −1 for our HAT-P-65b analogue. The black line represents the value of a completely clear atmosphere. At higher accelerations, the haze particles move faster and have lower densities (at fixed production rate), resulting in clearer … view at source ↗

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Reference graph

Works this paper leans on

110 extracted references · 15 canonical work pages · cited by 1 Pith paper · 2 internal anchors

  1. [1]

    write newline

    " write newline "" before.all 'output.state := FUNCTION fin.entry write newline FUNCTION new.block output.state before.all = 'skip after.block 'output.state := if FUNCTION new.sentence output.state after.block = 'skip output.state before.all = 'skip after.sentence 'output.state := if if FUNCTION not #0 #1 if FUNCTION and 'skip pop #0 if FUNCTION or pop #1...

  2. [2]

    V., 2019, @doi [ ] 10.3847/1538-4357/ab074c , https://ui.adsabs.harvard.edu/abs/2019ApJ...874...61A 874, 61

    Adams D., Gao P., de Pater I., Morley C. V., 2019, @doi [ ] 10.3847/1538-4357/ab074c , https://ui.adsabs.harvard.edu/abs/2019ApJ...874...61A 874, 61

    doi:10.3847/1538-4357/ab074c 2019

  3. [3]

    J., Kataria T., Batalha N

    Adams D. J., Kataria T., Batalha N. E., Gao P., Knutson H. A., 2022, @doi [ ] 10.3847/1538-4357/ac3d32 , https://ui.adsabs.harvard.edu/abs/2022ApJ...926..157A 926, 157

    doi:10.3847/1538-4357/ac3d32 2022

  4. [4]

    Ag \'u ndez M., Parmentier V., Venot O., Hersant F., Selsis F., 2014, @doi [ ] 10.1051/0004-6361/201322895 , https://ui.adsabs.harvard.edu/abs/2014A&A...564A..73A 564, A73

    doi:10.1051/0004-6361/201322895 2014

  5. [5]

    A., Liu H., Kuper L., Totoni E., Vitek J., Shpeisman T., 2017, in M\" u ller P., ed., Leibniz International Proceedings in Informatics (LIPIcs) Vol

    Anderson T. A., Liu H., Kuper L., Totoni E., Vitek J., Shpeisman T., 2017, in M\" u ller P., ed., Leibniz International Proceedings in Informatics (LIPIcs) Vol. 74, 31st European Conference on Object-Oriented Programming (ECOOP 2017). Schloss Dagstuhl -- Leibniz-Zentrum f \"u r Informatik, Dagstuhl, Germany, pp 4:1--4:29, @doi 10.4230/LIPIcs.ECOOP.2017.4 ...

    work page doi:10.4230/lipics.ecoop.2017.4 2017

  6. [6]

    S., Hauschildt P

    Barman T. S., Hauschildt P. H., Allard F., 2001, @doi [ ] 10.1086/321610 , https://ui.adsabs.harvard.edu/abs/2001ApJ...556..885B 556, 885

    doi:10.1086/321610 2001

  7. [7]

    K., 2020, @doi [ ] 10.1093/mnras/staa2219 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497.4183B 497, 4183

    Barstow J. K., 2020, @doi [ ] 10.1093/mnras/staa2219 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.497.4183B 497, 4183

    doi:10.1093/mnras/staa2219 2020

  8. [8]

    K., Aigrain S., Irwin P

    Barstow J. K., Aigrain S., Irwin P. G. J., Hackler T., Fletcher L. N., Lee J. M., Gibson N. P., 2014, @doi [ ] 10.1088/0004-637X/786/2/154 , https://ui.adsabs.harvard.edu/abs/2014ApJ...786..154B 786, 154

    doi:10.1088/0004-637x/786/2/154 2014

  9. [9]

    K., Aigrain S., Irwin P

    Barstow J. K., Aigrain S., Irwin P. G. J., Sing D. K., 2017, @doi [ ] 10.3847/1538-4357/834/1/50 , https://ui.adsabs.harvard.edu/abs/2017ApJ...834...50B 834, 50

    doi:10.3847/1538-4357/834/1/50 2017

  10. [10]

    Benneke B., et al., 2019, @doi [Nature Astronomy] 10.1038/s41550-019-0800-5 , https://ui.adsabs.harvard.edu/abs/2019NatAs...3..813B 3, 813

    doi:10.1038/s41550-019-0800-5 2019

  11. [11]

    Birnstiel T., et al., 2018, @doi [ ] 10.3847/2041-8213/aaf743 , https://ui.adsabs.harvard.edu/abs/2018ApJ...869L..45B 869, L45

    doi:10.3847/2041-8213/aaf743 2018

  12. [12]

    F., Huffman D

    Bohren C. F., Huffman D. R., 1998, Absorption and Scattering of Light by Small Particles

    1998

  13. [13]

    A., Lamy P

    Burns J. A., Lamy P. L., Soter S., 1979, @doi [ ] 10.1016/0019-1035(79)90050-2 , https://ui.adsabs.harvard.edu/abs/1979Icar...40....1B 40, 1

    doi:10.1016/0019-1035(79)90050-2 1979

  14. [14]

    Burrows A., et al., 1997, @doi [ ] 10.1086/305002 , https://ui.adsabs.harvard.edu/abs/1997ApJ...491..856B 491, 856

    doi:10.1086/305002 1997

  15. [15]

    Chandrasekhar S., 1960, Radiative transfer

    1960

  16. [16]

    M., Noyes R

    Charbonneau D., Brown T. M., Noyes R. W., Gilliland R. L., 2002, @doi [ ] 10.1086/338770 , https://ui.adsabs.harvard.edu/abs/2002ApJ...568..377C 568, 377

    doi:10.1086/338770 2002

  17. [17]

    L., et al., 2021, @doi [ ] 10.1051/0004-6361/202038350 , https://ui.adsabs.harvard.edu/abs/2021A&A...646A..21C 646, A21

    Chubb K. L., et al., 2021, @doi [ ] 10.1051/0004-6361/202038350 , https://ui.adsabs.harvard.edu/abs/2021A&A...646A..21C 646, A21

    doi:10.1051/0004-6361/202038350 2021

  18. [18]

    Deming D., et al., 2013, @doi [ ] 10.1088/0004-637X/774/2/95 , https://ui.adsabs.harvard.edu/abs/2013ApJ...774...95D 774, 95

    doi:10.1088/0004-637x/774/2/95 2013

  19. [19]

    H., Yu X., Ohno K., Zhang X., Fortney J

    Dymont A. H., Yu X., Ohno K., Zhang X., Fortney J. J., Thorngren D., Dickinson C., 2022, @doi [ ] 10.3847/1538-4357/ac7f40 , https://ui.adsabs.harvard.edu/abs/2022ApJ...937...90D 937, 90

    doi:10.3847/1538-4357/ac7f40 2022

  20. [20]

    Espinoza N., et al., 2019, @doi [ ] 10.1093/mnras/sty2691 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.482.2065E 482, 2065

    doi:10.1093/mnras/sty2691 2019

  21. [21]

    Cycle 2, ID

    Espinoza N., et al., 2023, Hot Jupiter Atmospheric Forecast: are mornings cloudier than evenings in other worlds? , JWST Proposal. Cycle 2, ID. \#3969

    2023

  22. [22]

    Inhomogeneous terminators on the exoplanet WASP-39 b

    Espinoza N., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.10294 , https://ui.adsabs.harvard.edu/abs/2024arXiv240710294E p. arXiv:2407.10294

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2407.10294 2024

  23. [23]

    D., et al., 2023, @doi [ ] 10.1038/s41586-022-05674-1 , https://ui.adsabs.harvard.edu/abs/2023Natur.614..670F 614, 670

    Feinstein A. D., et al., 2023, @doi [ ] 10.1038/s41586-022-05674-1 , https://ui.adsabs.harvard.edu/abs/2023Natur.614..670F 614, 670

    doi:10.1038/s41586-022-05674-1 2023

  24. [24]

    J., 2005, @doi [ ] 10.1111/j.1365-2966.2005.09587.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.364..649F 364, 649

    Fortney J. J., 2005, @doi [ ] 10.1111/j.1365-2966.2005.09587.x , https://ui.adsabs.harvard.edu/abs/2005MNRAS.364..649F 364, 649

    arXiv 2005

  25. [25]

    Fraine J., et al., 2014, @doi [ ] 10.1038/nature13785 , https://ui.adsabs.harvard.edu/abs/2014Natur.513..526F 513, 526

    doi:10.1038/nature13785 2014

  26. [26]

    S., Lustig-Yaeger J., Fortney J

    Freedman R. S., Lustig-Yaeger J., Fortney J. J., Lupu R. E., Marley M. S., Lodders K., 2014, @doi [ ] 10.1088/0067-0049/214/2/25 , https://ui.adsabs.harvard.edu/abs/2014ApJS..214...25F 214, 25

    doi:10.1088/0067-0049/214/2/25 2014

  27. [27]

    Fu G., Deming D., Knutson H., Madhusudhan N., Mandell A., Fraine J., 2017, @doi [ ] 10.3847/2041-8213/aa8e40 , https://ui.adsabs.harvard.edu/abs/2017ApJ...847L..22F 847, L22

    doi:10.3847/2041-8213/aa8e40 2017

  28. [28]

    Gao P., Zhang X., 2020, @doi [ ] 10.3847/1538-4357/ab6a9b , https://ui.adsabs.harvard.edu/abs/2020ApJ...890...93G 890, 93

    doi:10.3847/1538-4357/ab6a9b 2020

  29. [29]

    S., Ackerman A

    Gao P., Marley M. S., Ackerman A. S., 2018, @doi [ ] 10.3847/1538-4357/aab0a1 , https://ui.adsabs.harvard.edu/abs/2018ApJ...855...86G 855, 86

    doi:10.3847/1538-4357/aab0a1 2018

  30. [30]

    Gao P., et al., 2020, @doi [Nature Astronomy] 10.1038/s41550-020-1114-3 , https://ui.adsabs.harvard.edu/abs/2020NatAs...4..951G 4, 951

    doi:10.1038/s41550-020-1114-3 2020

  31. [31]

    R., Moran S

    Gao P., Wakeford H. R., Moran S. E., Parmentier V., 2021, @doi [Journal of Geophysical Research (Planets)] 10.1029/2020JE006655 , https://ui.adsabs.harvard.edu/abs/2021JGRE..12606655G 126, e06655

    doi:10.1029/2020je006655 2021

  32. [32]

    Grant D., et al., 2023, @doi [ ] 10.3847/2041-8213/acfc3b10.3847/2041-8213/acfdab , https://ui.adsabs.harvard.edu/abs/2023ApJ...956L..32G 956, L32

    doi:10.3847/2041-8213/acfc3b10.3847/2041-8213/acfdab 2023

  33. [33]

    Guillot T., 2010, @doi [ ] 10.1051/0004-6361/200913396 , https://ui.adsabs.harvard.edu/abs/2010A&A...520A..27G 520, A27

    doi:10.1051/0004-6361/200913396 2010

  34. [34]

    B., Lunine J

    Guillot T., Burrows A., Hubbard W. B., Lunine J. I., Saumon D., 1996, @doi [ ] 10.1086/309935 , https://ui.adsabs.harvard.edu/abs/1996ApJ...459L..35G 459, L35

    doi:10.1086/309935 1996

  35. [35]

    D., et al., 2016, @doi [ ] 10.3847/0004-6256/152/6/182 , https://ui.adsabs.harvard.edu/abs/2016AJ....152..182H 152, 182

    Hartman J. D., et al., 2016, @doi [ ] 10.3847/0004-6256/152/6/182 , https://ui.adsabs.harvard.edu/abs/2016AJ....152..182H 152, 182

    work page doi:10.3847/0004-6256/152/6/182 2016

  36. [36]

    Helling C., 2019, @doi [Annual Review of Earth and Planetary Sciences] 10.1146/annurev-earth-053018-060401 , https://ui.adsabs.harvard.edu/abs/2019AREPS..47..583H 47, 583

    doi:10.1146/annurev-earth-053018-060401 2019

  37. [37]

    H., 2008, @doi [ ] 10.1086/533462 , https://ui.adsabs.harvard.edu/abs/2008ApJ...675L.105H 675, L105

    Helling C., Dehn M., Woitke P., Hauschildt P. H., 2008, @doi [ ] 10.1086/533462 , https://ui.adsabs.harvard.edu/abs/2008ApJ...675L.105H 675, L105

    doi:10.1086/533462 2008

  38. [38]

    Heng K., Demory B.-O., 2013, @doi [ ] 10.1088/0004-637X/777/2/100 , https://ui.adsabs.harvard.edu/abs/2013ApJ...777..100H 777, 100

    work page doi:10.1088/0004-637x/777/2/100 2013

  39. [39]

    J., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18315.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.413.2380H 413, 2380

    Heng K., Menou K., Phillipps P. J., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18315.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.413.2380H 413, 2380

    arXiv 2011

  40. [40]

    M., Kitzmann D., 2021, @doi [Nature Astronomy] 10.1038/s41550-021-01444-7 , https://ui.adsabs.harvard.edu/abs/2021NatAs...5.1001H 5, 1001

    Heng K., Morris B. M., Kitzmann D., 2021, @doi [Nature Astronomy] 10.1038/s41550-021-01444-7 , https://ui.adsabs.harvard.edu/abs/2021NatAs...5.1001H 5, 1001

    doi:10.1038/s41550-021-01444-7 2021

  41. [41]

    M., 2016, The Planetary Society, Clouds and haze and dust, oh my!, https://www.planetary.org/articles/0324-clouds-and-haze-and-dust-oh-my

    H\"orst S. M., 2016, The Planetary Society, Clouds and haze and dust, oh my!, https://www.planetary.org/articles/0324-clouds-and-haze-and-dust-oh-my

    2016

  42. [42]

    M., Tolbert M

    H \"o rst S. M., Tolbert M. A., 2013, @doi [ ] 10.1088/2041-8205/770/1/L10 , https://ui.adsabs.harvard.edu/abs/2013ApJ...770L..10H 770, L10

    work page doi:10.1088/2041-8205/770/1/l10 2013

  43. [43]

    M., et al., 2018, @doi [Nature Astronomy] 10.1038/s41550-018-0397-0 , https://ui.adsabs.harvard.edu/abs/2018NatAs...2..303H 2, 303

    H \"o rst S. M., et al., 2018, @doi [Nature Astronomy] 10.1038/s41550-018-0397-0 , https://ui.adsabs.harvard.edu/abs/2018NatAs...2..303H 2, 303

    doi:10.1038/s41550-018-0397-0 2018

  44. [44]

    J \"a ger C., Dorschner J., Mutschke H., Posch T., Henning T., 2003, @doi [ ] 10.1051/0004-6361:20030916 , https://ui.adsabs.harvard.edu/abs/2003A&A...408..193J 408, 193

    doi:10.1051/0004-6361:20030916 2003

  45. [45]

    Jontof-Hutter D., et al., 2016, @doi [ ] 10.3847/0004-637X/820/1/39 , https://ui.adsabs.harvard.edu/abs/2016ApJ...820...39J 820, 39

    doi:10.3847/0004-637x/820/1/39 2016

  46. [46]

    G., Helling C., 2017, @doi [ ] 10.1051/0004-6361/201629977 , https://ui.adsabs.harvard.edu/abs/2017A&A...608A..70J 608, A70

    Juncher D., J rgensen U. G., Helling C., 2017, @doi [ ] 10.1051/0004-6361/201629977 , https://ui.adsabs.harvard.edu/abs/2017A&A...608A..70J 608, A70

    work page doi:10.1051/0004-6361/201629977 2017

  47. [47]

    Kawashima Y., Ikoma M., 2019, @doi [ ] 10.3847/1538-4357/ab1b1d , https://ui.adsabs.harvard.edu/abs/2019ApJ...877..109K 877, 109

    doi:10.3847/1538-4357/ab1b1d 2019

  48. [48]

    Kempton E. M. R., Bean J. L., Parmentier V., 2017, @doi [ ] 10.3847/2041-8213/aa84ac , https://ui.adsabs.harvard.edu/abs/2017ApJ...845L..20K 845, L20

    doi:10.3847/2041-8213/aa84ac 2017

  49. [49]

    Kempton E. M. R., et al., 2018, @doi [ ] 10.1088/1538-3873/aadf6f , https://ui.adsabs.harvard.edu/abs/2018PASP..130k4401K 130, 114401

    doi:10.1088/1538-3873/aadf6f 2018

  50. [50]

    Kempton E. M. R., et al., 2023, @doi [ ] 10.1038/s41586-023-06159-5 , https://ui.adsabs.harvard.edu/abs/2023Natur.620...67K 620, 67

    doi:10.1038/s41586-023-06159-5 2023

  51. [51]

    N., Sagan C., Arakawa E

    Khare B. N., Sagan C., Arakawa E. T., Suits F., Callcott T. A., Williams M. W., 1984, @doi [ ] 10.1016/0019-1035(84)90142-8 , https://ui.adsabs.harvard.edu/abs/1984Icar...60..127K 60, 127

    doi:10.1016/0019-1035(84)90142-8 1984

  52. [52]

    arXiv:2407.03198

    Kirk J., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.03198 , https://ui.adsabs.harvard.edu/abs/2024arXiv240703198K p. arXiv:2407.03198

    Pith/arXiv arXiv doi:10.48550/arxiv.2407.03198 2024

  53. [53]

    D., Showman A

    Komacek T. D., Showman A. P., Parmentier V., 2019, @doi [ ] 10.3847/1538-4357/ab338b , https://ui.adsabs.harvard.edu/abs/2019ApJ...881..152K 881, 152

    doi:10.3847/1538-4357/ab338b 2019

  54. [54]

    J., Belmonte J

    Kreidberg L., 2018, in Deeg H. J., Belmonte J. A., eds, , Handbook of Exoplanets. p. 100, @doi 10.1007/978-3-319-55333-7_100

    doi:10.1007/978-3-319-55333-7_100 2018

  55. [55]

    Kreidberg L., et al., 2014, @doi [ ] 10.1038/nature12888 , https://ui.adsabs.harvard.edu/abs/2014Natur.505...69K 505, 69

    doi:10.1038/nature12888 2014

  56. [56]

    K., Pitrou A., Seibert S., 2015, in Proceedings of the Second Workshop on the LLVM Compiler Infrastructure in HPC

    Lam S. K., Pitrou A., Seibert S., 2015, in Proceedings of the Second Workshop on the LLVM Compiler Infrastructure in HPC. LLVM '15. Association for Computing Machinery, New York, NY, USA, @doi 10.1145/2833157.2833162 , https://doi.org/10.1145/2833157.2833162

    arXiv 2015

  57. [57]

    Lavvas P., Koskinen T., 2017, @doi [ ] 10.3847/1538-4357/aa88ce , https://ui.adsabs.harvard.edu/abs/2017ApJ...847...32L 847, 32

    doi:10.3847/1538-4357/aa88ce 2017

  58. [58]

    Lavvas P., Sander M., Kraft M., Imanaka H., 2011, @doi [ ] 10.1088/0004-637X/728/2/80 , https://ui.adsabs.harvard.edu/abs/2011ApJ...728...80L 728, 80

    work page doi:10.1088/0004-637x/728/2/80 2011

  59. [59]

    Lecavelier Des Etangs A., Pont F., Vidal-Madjar A., Sing D., 2008, @doi [ ] 10.1051/0004-6361:200809388 , https://ui.adsabs.harvard.edu/abs/2008A&A...481L..83L 481, L83

    doi:10.1051/0004-6361:200809388 2008

  60. [60]

    Lee E., Helling C., Dobbs-Dixon I., Juncher D., 2015, @doi [ ] 10.1051/0004-6361/201525982 , https://ui.adsabs.harvard.edu/abs/2015A&A...580A..12L 580, A12

    work page doi:10.1051/0004-6361/201525982 2015

  61. [61]

    R., Knutson H., Wolf A

    Line M. R., Knutson H., Wolf A. S., Yung Y. L., 2014, @doi [ ] 10.1088/0004-637X/783/2/70 , https://ui.adsabs.harvard.edu/abs/2014ApJ...783...70L 783, 70

    doi:10.1088/0004-637x/783/2/70 2014

  62. [62]

    Lueber A., Novais A., Fisher C., Heng K., 2024, @doi [ ] 10.1051/0004-6361/202348802 , https://ui.adsabs.harvard.edu/abs/2024A&A...687A.110L 687, A110

    doi:10.1051/0004-6361/202348802 2024

  63. [63]

    Madhusudhan N., Sarkar S., Constantinou S., Holmberg M., Piette A. A. A., Moses J. I., 2023, @doi [ ] 10.3847/2041-8213/acf577 , https://ui.adsabs.harvard.edu/abs/2023ApJ...956L..13M 956, L13

    doi:10.3847/2041-8213/acf577 2023

  64. [64]

    P., van Boekel R., Henning T., Molaverdikhani K., Snellen I

    Molli \`e re P., Wardenier J. P., van Boekel R., Henning T., Molaverdikhani K., Snellen I. A. G., 2019, @doi [ ] 10.1051/0004-6361/201935470 , https://ui.adsabs.harvard.edu/abs/2019A&A...627A..67M 627, A67

    doi:10.1051/0004-6361/201935470 2019

  65. [65]

    V., Fortney J

    Morley C. V., Fortney J. J., Kempton E. M. R., Marley M. S., Visscher C., Zahnle K., 2013, @doi [ ] 10.1088/0004-637X/775/1/33 , https://ui.adsabs.harvard.edu/abs/2013ApJ...775...33M 775, 33

    doi:10.1088/0004-637x/775/1/33 2013

  66. [66]

    I., et al., 2011, @doi [ ] 10.1088/0004-637X/737/1/15 , https://ui.adsabs.harvard.edu/abs/2011ApJ...737...15M 737, 15

    Moses J. I., et al., 2011, @doi [ ] 10.1088/0004-637X/737/1/15 , https://ui.adsabs.harvard.edu/abs/2011ApJ...737...15M 737, 15

    doi:10.1088/0004-637x/737/1/15 2011

  67. [67]

    M., et al., 2025, @doi [ ] 10.3847/1538-3881/addf38 , https://ui.adsabs.harvard.edu/abs/2025AJ....170...61M 170, 61

    Murphy M. M., et al., 2025, @doi [ ] 10.3847/1538-3881/addf38 , https://ui.adsabs.harvard.edu/abs/2025AJ....170...61M 170, 61

    doi:10.3847/1538-3881/addf38 2025

  68. [68]

    K., Gibson N

    Nikolov N., Sing D. K., Gibson N. P., Fortney J. J., Evans T. M., Barstow J. K., Kataria T., Wilson P. A., 2016, @doi [ ] 10.3847/0004-637X/832/2/191 , https://ui.adsabs.harvard.edu/abs/2016ApJ...832..191N 832, 191

    doi:10.3847/0004-637x/832/2/191 2016

  69. [69]

    A., Lee E

    Noti P. A., Lee E. K. H., 2024, @doi [ ] 10.1051/0004-6361/202451823 , https://ui.adsabs.harvard.edu/abs/2024A&A...691A.139N 691, A139

    doi:10.1051/0004-6361/202451823 2024

  70. [70]

    Ohno K., Kawashima Y., 2020, @doi [ ] 10.3847/2041-8213/ab93d7 , https://ui.adsabs.harvard.edu/abs/2020ApJ...895L..47O 895, L47

    doi:10.3847/2041-8213/ab93d7 2020

  71. [71]

    Ohno K., Okuzumi S., 2017, @doi [ ] 10.3847/1538-4357/835/2/261 , https://ui.adsabs.harvard.edu/abs/2017ApJ...835..261O 835, 261

    doi:10.3847/1538-4357/835/2/261 2017

  72. [72]

    W., Min M., 2019, @doi [ ] 10.1051/0004-6361/201833678 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.121O 622, A121

    Ormel C. W., Min M., 2019, @doi [ ] 10.1051/0004-6361/201833678 , https://ui.adsabs.harvard.edu/abs/2019A&A...622A.121O 622, A121

    doi:10.1051/0004-6361/201833678 2019

  73. [73]

    E., 2020, @doi [ ] 10.1093/mnras/staa2784 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.5030O 498, 5030

    Owen J. E., 2020, @doi [ ] 10.1093/mnras/staa2784 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.498.5030O 498, 5030

    doi:10.1093/mnras/staa2784 2020

  74. [74]

    E., Kollmeier J

    Owen J. E., Kollmeier J. A., 2019, @doi [ ] 10.1093/mnras/stz1591 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.487.3702O 487, 3702

    work page doi:10.1093/mnras/stz1591 2019

  75. [75]

    E., Wu Y., 2013, @doi [ ] 10.1088/0004-637X/775/2/105 , https://ui.adsabs.harvard.edu/abs/2013ApJ...775..105O 775, 105

    Owen J. E., Wu Y., 2013, @doi [ ] 10.1088/0004-637X/775/2/105 , https://ui.adsabs.harvard.edu/abs/2013ApJ...775..105O 775, 105

    doi:10.1088/0004-637x/775/2/105 2013

  76. [76]

    P., Lian Y., 2013, @doi [ ] 10.1051/0004-6361/201321132 , https://ui.adsabs.harvard.edu/abs/2013A&A...558A..91P 558, A91

    Parmentier V., Showman A. P., Lian Y., 2013, @doi [ ] 10.1051/0004-6361/201321132 , https://ui.adsabs.harvard.edu/abs/2013A&A...558A..91P 558, A91

    doi:10.1051/0004-6361/201321132 2013

  77. [77]

    J., Showman A

    Parmentier V., Fortney J. J., Showman A. P., Morley C., Marley M. S., 2016, @doi [ ] 10.3847/0004-637X/828/1/22 , https://ui.adsabs.harvard.edu/abs/2016ApJ...828...22P 828, 22

    doi:10.3847/0004-637x/828/1/22 2016

  78. [78]

    Penzlin A. B. T., et al., 2024, @doi [arXiv e-prints] 10.48550/arXiv.2407.03199 , https://ui.adsabs.harvard.edu/abs/2024arXiv240703199P p. arXiv:2407.03199

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.2407.03199 2024

  79. [79]

    Pinhas A., Madhusudhan N., 2017, @doi [ ] 10.1093/mnras/stx1849 , https://ui.adsabs.harvard.edu/abs/2017MNRAS.471.4355P 471, 4355

    doi:10.1093/mnras/stx1849 2017

  80. [80]

    Pinhas A., Madhusudhan N., Gandhi S., MacDonald R., 2019, @doi [ ] 10.1093/mnras/sty2544 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.482.1485P 482, 1485

    doi:10.1093/mnras/sty2544 2019

Showing first 80 references.

This paper was first reviewed by deepseek-v4-flash on August 5, 2026.