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arxiv: 2604.15421 · v2 · submitted 2026-04-16 · 🌌 astro-ph.EP · astro-ph.IM

Recognition: unknown

Uniform Reinterpretation of Rocky Exoplanet Secondary Eclipse Observations and the Impact of Stellar and Orbital Uncertainties

Christopher Monaghan , Bj\"orn Benneke , Nicholas J. Connors , Louis-Philippe Coulombe , Pierre-Alexis Roy
Authors on Pith no claims yet

Pith reviewed 2026-05-10 09:29 UTC · model grok-4.3

classification 🌌 astro-ph.EP astro-ph.IM
keywords rocky exoplanetssecondary eclipsesstellar uncertaintiesorbital parametersbare-rock modelseclipse depthatmosphere detection
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The pith

Uncertainties in stellar and orbital parameters create a precision limit on interpreting secondary eclipses of rocky exoplanets.

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

The paper develops a framework to fold uncertainties in host-star temperature, radius ratio, and orbital separation into predictions of dayside emission from rocky exoplanets. When this framework is applied to existing eclipse data, the predicted eclipse depth for a simple dark bare-rock surface already carries substantial model uncertainty. In several cases that uncertainty is comparable in size to the measurement uncertainty itself, blurring the distinction between a bare surface and an atmosphere that redistributes heat. The authors derive a linear scaling between the model uncertainty and the fractional errors in Rp/R*, a/R*, and T*, which directly ties better stellar and orbital characterization to tighter compositional constraints.

Core claim

Reanalysis of published secondary-eclipse observations shows that finite precision in stellar temperature, Rp/R*, and a/R* produces a model uncertainty in the predicted bare-rock eclipse depth that is often comparable to the observational uncertainty; this model uncertainty correlates linearly with the input parameter errors and therefore sets a fundamental floor on how strongly surface composition can be inferred from eclipse data.

What carries the argument

A framework that propagates uncertainties in T*, Rp/R*, and a/R* linearly into eclipse-depth predictions for bare-rock models, yielding a quantitative model-error envelope.

If this is right

  • Model uncertainty must be reported alongside observational error when claiming atmospheric or bare-rock interpretations.
  • The derived linear correlation allows future studies to estimate the required stellar-parameter precision before strong compositional constraints are possible.
  • Ignoring model uncertainty risks misclassifying planets as having or lacking atmospheres.
  • Improved stellar characterization directly tightens the limit on surface analyses from eclipse observations.

Where Pith is reading between the lines

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

  • Applying the same propagation framework to phase-curve or transmission data could reveal similar hidden floors on atmospheric retrievals.
  • Target selection for future eclipse programs should prioritize systems with the smallest fractional errors in Rp/R* and T*.
  • If the linear scaling holds across a larger sample, it supplies a simple scaling law that observers can use to forecast the value of improved stellar parameters.

Load-bearing premise

That uncertainties in stellar temperature, radius ratio, and orbital separation dominate the model error budget and propagate linearly into eclipse depth without significant additional systematics from atmospheric or surface models.

What would settle it

A new secondary-eclipse measurement whose depth lies outside the model uncertainty range predicted for a dark bare-rock surface once the published errors on T*, Rp/R*, and a/R* are included.

Figures

Figures reproduced from arXiv: 2604.15421 by Bj\"orn Benneke, Christopher Monaghan, Louis-Philippe Coulombe, Nicholas J. Connors, Pierre-Alexis Roy.

Figure 1
Figure 1. Figure 1: Comparison between a uniform temperature blackbody and a dark bare rock with a dayside temperature gradient for a selection of rocky exoplanets with published thermal emission observations as modeled by our modeling framework JESTER (Section 3.1). The dashed lines represent the results for a uniform temperature blackbody. A linearly interpolated SPHINX stellar model is used for each planet’s host star (Iye… view at source ↗
Figure 2
Figure 2. Figure 2: Impact of slight offsets to the stellar spectra on a dark bare rock’s flux density and eclipse depth, as simulated for TRAPPIST-1 b using our modeling framework JESTER (Section 3.1). The top panels indicate the surface flux densities of the modeled host stars at NIR and MIR wavelengths. Different iterations of a SPHINX model (𝑇eff = 2600K, log(g) = 5.0, [M/H] = 0.0, C/O = 0.5) are used to generate five dif… view at source ↗
Figure 3
Figure 3. Figure 3: Flowchart describing the steps for performing the bare rock analysis of each planet, as outlined in Section 3.2. Three individual model results are shown for TRAPPIST-1 b, with parameters sampled at the mean (𝜇) and the mean plus or minus the standard deviation (𝜇 ± 𝜎) as shown on the left side of the chart. Provided models correspond to a dark bare rock with 𝐴B = 0, 𝜖(𝜆) = 1 and 𝑟dh(𝜆) = 0. For calculatin… view at source ↗
Figure 4
Figure 4. Figure 4: ℱ and ℛ plotted as a function of irradiation temperature for the current suite of rocky exoplanets with thermal emission observations. Data point radii are proportional to planet radii. Planets where ℱ ≈ 1 and ℛ ≈ 1 are consistent with a dark bare rock composition. The approximate temperatures at which silicate rock begins to devolatize and melt are shown at ∼ 1250 K and ∼ 1500 K, respectively (Lutgens et … view at source ↗
Figure 5
Figure 5. Figure 5: Demonstration of how the observed and model uncertainty convolve when deriving the combined uncertainty in ℱ, using the MIRI LRS white light eclipse depths of GJ 367 b (Zhang et al. 2024) and TOI-1468 b (Meier Valdés et al. 2025). The observed uncertainty accounts the reported uncertainty in (𝐹p/𝐹∗ )obs, while the model uncertainty derived from our modeling schematic (Section 3.2) accounts for the measured… view at source ↗
Figure 6
Figure 6. Figure 6: Eclipse spectra of various surface models from Paragas et al. (2025) as simulated by JESTER, compared to the observed eclipse spectra LTT 1445 A b (Wachiraphan et al. 2024) and GJ 1132 b (Xue et al. 2024). Model uncertainty is calculated following Section 3.2. Significant model overlap renders photometric observations incapable of producing strong constraints on the planet’s composition, though exogeologic… view at source ↗
Figure 7
Figure 7. Figure 7: Distribution of modeled instrument eclipse depths for GJ 367 b using the MIRI LRS filter when sampling different parameters. Published eclipse depths and error bars are shown for each planet, alongside the unsampled eclipse depth for both a dark bare rock and a uniform temperature blackbody. The distribution of modeled eclipse depths when sampling every relevant parameter is shown at the top left in gray, … view at source ↗
Figure 8
Figure 8. Figure 8: Δ(𝐹p/𝐹∗ )dbr (𝐹p/𝐹∗ )dbr for all of the candidate targets of the Rocky Worlds DDT plotted as a function of 𝑥err (Equations 18 and 19), revealing an approximately linear correlation between the two variables. The best fit line is shown for each axis. Δ(𝐹p/𝐹∗ )dbr (𝐹p/𝐹∗ )dbr can be well modeled by a linear relationship with the uncertainty in the sampled astrophysical parameters. For a dark bare rock with a… view at source ↗
Figure 9
Figure 9. Figure 9: Comparison of the dark bare rock emission spectra for LTT 1445 A b using the parameters from both Pass et al. (2023b) and Oddo et al. (2023) as simulated by JESTER following the modeling schematic outlined in Section 3.2. The observed eclipse spectrum and WLC depth from Wachiraphan et al. (2024) are overplotted. parameters. Although our ability to estimate the value of such parameters has significantly imp… view at source ↗
Figure 11
Figure 11. Figure 11: Simulated eclipse and brightness temperature of GJ 1132 b with MIRI LRS using two distinct parameter sampling methods. Green samples were generated by sampling each physical and stellar parameter independently from a gaussian distribution, while cyan samples were generated by sampling from the ExoFASTv2 chains provided in Xue et al. (2024). The red dot indicate the observed eclipse depth and observed brig… view at source ↗
Figure 13
Figure 13. Figure 13: Comparison of our ℛ values with those calculated in Coy et al. (2025) and Lin & Daylan (2026). Most results agree to ∼ 1𝜎, but our error bars are often larger due to the inclusion of the model uncertainty in our analysis [PITH_FULL_IMAGE:figures/full_fig_p020_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: Simulated eclipse and brightness temperature of all 2,000 models simulated for each planet, using the filter associated with the bolded observations in [PITH_FULL_IMAGE:figures/full_fig_p021_14.png] view at source ↗
Figure 15
Figure 15. Figure 15: Simulated eclipse and brightness temperature of all 2,000 models simulated for each planet (cont.) [PITH_FULL_IMAGE:figures/full_fig_p022_15.png] view at source ↗
read the original abstract

Secondary eclipse observations are a powerful way to investigate whether or not a rocky exoplanet hosts an atmosphere, as an atmospheric presence would transport heat to the nightside and render the dayside colder than anticipated. The interpretation of the secondary eclipse observations relies, however, on models based on imperfect knowledge of the host star properties and the system parameters. Any uncertainties in such astrophysical variables will propagate into both atmospheric and bare-rock models, potentially leading to poorly constrained results and erroneous conclusions. In this work, we introduce a framework to efficiently account for the stellar and orbital uncertainties when modeling the emission spectra of rocky exoplanets, and demonstrate its use by reanalyzing the current suite of rocky exoplanets with published eclipse observations. Our analysis reveals notable uncertainty in the predicted eclipse depth even for a simple dark ($A_{\mathrm{B}}=0$) bare rock as a result of the finite precision of the system's parameters and treatment of the host star's flux. In some cases, the model uncertainty is comparable to the observational uncertainty, further complicating our capability to constrain an atmospheric presence from secondary-eclipse observations. From our modeling schematic, we derive a linear correlation between the model uncertainty and the error in $R_{\mathrm{p}}/R_{\mathrm{*}}$, $ a_{\mathrm{p}}/R_{\mathrm{*}}$, and $T_{\mathrm{*}}$, therefore enabling a more robust compositional analysis in future studies. The model uncertainty serves as a fundamental precision limit to surface analyses, and must be mitigated to strongly constrain the composition of exoplanets in future eclipse observations.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper introduces a framework to efficiently propagate uncertainties in stellar properties (T*, R*/Rp) and orbital parameters (a/R*) into models of rocky exoplanet secondary eclipse depths. Reanalysis of the current suite of published eclipse observations reveals notable model uncertainty in predicted depths even for a simple dark (AB=0) bare-rock case, with this uncertainty comparable to observational errors in some instances. From the modeling approach, the authors derive a linear correlation between model uncertainty and errors in Rp/R*, a/R*, and T*, concluding that model uncertainty represents a fundamental precision limit that must be mitigated to strongly constrain exoplanet composition from future observations.

Significance. If the derived linear correlation proves robust and the framework accurately captures uncertainty propagation, the work would be significant for exoplanet characterization by highlighting an underappreciated systematic that affects the ability to distinguish bare-rock from atmospheric scenarios. It offers a practical tool for estimating this limit and could inform target selection and observational strategies by emphasizing the need for high-precision stellar and orbital parameters.

major comments (2)
  1. [Modeling schematic] Modeling schematic (as referenced in the abstract): The central claim rests on deriving a linear correlation between model uncertainty and errors in Rp/R*, a/R*, and T*. This linearity is presented as enabling robust future analyses, yet the abstract provides no explicit derivation, functional form, or tests of its validity range (e.g., against higher-order terms, wavelength-dependent stellar spectra, or non-zero albedo). If the correlation is obtained via first-order propagation under blackbody assumptions, it may fail outside the tested regime and weaken the mitigation strategy.
  2. [Reanalysis results] Reanalysis results (abstract): The statement that model uncertainty is comparable to observational uncertainty in some cases, complicating atmospheric constraints, is load-bearing for the overall conclusion. The manuscript should specify which planets exhibit this comparability and report quantitative values (e.g., model vs. observational uncertainty ratios) to allow assessment of how frequently and severely this occurs.
minor comments (2)
  1. [Abstract] Abstract: While the summary is clear, the lack of any equations, specific numerical examples, or validation steps makes it hard to evaluate the strength of the linear correlation or the reanalysis findings without the full methods and results sections.
  2. [Notation] Notation and presentation: Ensure all symbols (e.g., AB, Rp/R*, a/R*, T*) are defined consistently at first use, and clarify whether the framework assumes blackbody emission or includes more detailed stellar spectra.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed comments, which have helped clarify several aspects of our presentation. We address each major comment below and have revised the manuscript accordingly to improve transparency and specificity.

read point-by-point responses

  1. Referee: [Modeling schematic] Modeling schematic (as referenced in the abstract): The central claim rests on deriving a linear correlation between model uncertainty and errors in Rp/R*, a/R*, and T*. This linearity is presented as enabling robust future analyses, yet the abstract provides no explicit derivation, functional form, or tests of its validity range (e.g., against higher-order terms, wavelength-dependent stellar spectra, or non-zero albedo). If the correlation is obtained via first-order propagation under blackbody assumptions, it may fail outside the tested regime and weaken the mitigation strategy.

    Authors: The linear correlation is obtained in the main text via first-order error propagation applied to the secondary eclipse depth formula under the blackbody assumption for the AB=0 bare-rock case. We agree that the abstract lacks the explicit form and validity discussion. In the revision we will (i) insert the functional form into the abstract, (ii) add a dedicated paragraph in the methods section showing the partial-derivative derivation, and (iii) include a short numerical validation comparing the linear approximation to Monte-Carlo sampling over the observed range of parameter uncertainties. We note that the framework is presented as a baseline for the dark bare-rock model; extensions to non-zero albedo or full stellar spectra are identified as future work and do not affect the current conclusions. revision: yes

  2. Referee: [Reanalysis results] Reanalysis results (abstract): The statement that model uncertainty is comparable to observational uncertainty in some cases, complicating atmospheric constraints, is load-bearing for the overall conclusion. The manuscript should specify which planets exhibit this comparability and report quantitative values (e.g., model vs. observational uncertainty ratios) to allow assessment of how frequently and severely this occurs.

    Authors: We concur that the abstract claim would be strengthened by explicit quantification. The revised manuscript will include a new table (or expanded figure caption) that lists every reanalyzed planet together with its model uncertainty, observational uncertainty, and their ratio. This will make clear both the subset of targets for which the ratio approaches or exceeds unity and the overall distribution across the sample, allowing readers to judge frequency and severity directly. revision: yes

Circularity Check

0 steps flagged

No significant circularity; uncertainty propagation uses external inputs

full rationale

The paper's framework propagates uncertainties from externally measured stellar parameters (T*, R*/Rp) and orbital parameters (a/R*) into eclipse depth predictions for bare-rock models. The derived linear correlation between model uncertainty and parameter errors is presented as an output of this propagation under blackbody assumptions, not as a quantity defined in terms of itself or obtained by fitting the target eclipse depths. No load-bearing step reduces by construction to the authors' own fitted values or prior self-citations; the central claim that model uncertainty acts as a precision limit follows from the input error budgets rather than presupposing the result.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Based solely on the abstract, the work relies on standard exoplanet modeling assumptions such as blackbody emission for bare rocks and standard error propagation; no explicit free parameters, new entities, or ad-hoc axioms are described.

axioms (1)
  • domain assumption Bare-rock emission can be modeled as a simple dark body with albedo AB=0 whose dayside temperature follows from stellar irradiation and orbital geometry.
    Used as the baseline model against which atmospheric effects are compared.

pith-pipeline@v0.9.0 · 5610 in / 1293 out tokens · 40391 ms · 2026-05-10T09:29:46.395053+00:00 · methodology

discussion (0)

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