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arxiv: 2603.24779 · v2 · pith:4SDAISHTnew · submitted 2026-03-25 · 🌌 astro-ph.EP · astro-ph.IM

Resizing the giants: How modelling adiabatic interiors impacts predicted planetary radii

Pith reviewed 2026-05-15 00:12 UTC · model grok-4.3

classification 🌌 astro-ph.EP astro-ph.IM
keywords adiabatic gradientplanetary interiorsgiant planetsnumerical methodsplanetary radiiexoplanet structurehydrogen-helium EOS
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The pith

Numerical methods for adiabatic temperature profiles can change giant planet radii by up to 3.4 percent.

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

This paper tests how different numerical schemes for solving the adiabatic temperature gradient alter the internal structure and radius of a one-Jupiter-mass planet. Giant-planet models assume fully convective, adiabatic interiors, so the temperature profile directly sets the radius for given mass and composition. The authors compare several common evaluation methods against an isentropic baseline using both logarithmic and non-logarithmic forms of the temperature equation. With the logarithmic form, central temperatures shift by thousands of kelvin and surface radii differ by as much as 3.4 percent. The non-logarithmic form keeps most differences below 1 percent. The work shows that current radius-measurement precision of one percent can be exceeded by modeling choices alone.

Core claim

Static interior models of a one-Jupiter-mass planet computed with a hydrogen-helium equation of state show that the numerical method chosen to evaluate the adiabatic gradient produces central-temperature deviations of several thousand kelvin and radius differences up to 3.4 percent when the logarithmic temperature equation is used; the non-logarithmic form reduces deviations below about 1 percent for most methods. Spline derivatives combined with the non-logarithmic equation minimize the error, while finite differencing and direct use of tabulated gradients should be avoided.

What carries the argument

The adiabatic temperature gradient, computed by different numerical schemes (finite differences, splines, tabulated derivatives) applied to the logarithmic or non-logarithmic temperature differential equation inside a one-dimensional, fully convective planet model.

If this is right

  • Radius predictions for giant exoplanets can carry systematic errors larger than current observational uncertainties.
  • Inferred bulk heavy-element masses from radius measurements become method-dependent.
  • Evolution tracks that rely on the logarithmic temperature equation can produce inconsistent cooling histories.
  • Standardizing on spline derivatives with the non-logarithmic form would allow direct comparison across different interior codes.

Where Pith is reading between the lines

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

  • Previous radius-based composition estimates for warm Jupiters may need re-evaluation once models adopt a consistent adiabatic solver.
  • The same numerical sensitivity could affect inferred radii for sub-Neptunes if their interiors are also treated as adiabatic.
  • Coupling the recommended spline method to three-dimensional convection simulations would test whether the one-dimensional assumption itself amplifies the discrepancy.
  • Observational campaigns targeting radius precision better than 1 percent will require interior models that document their adiabatic-gradient implementation.

Load-bearing premise

The planet is assumed to be strictly one-dimensional, fully convective, and perfectly adiabatic, so that the temperature profile is set solely by the numerical treatment of the gradient.

What would settle it

Recompute the radius of Jupiter with the same equation of state but with each numerical method and check whether the 3.4 percent radius spread remains when the model is required to match Jupiter's observed radius, mass, and luminosity.

read the original abstract

The interiors of giant planets are commonly assumed to be convective and adiabatic, making the adiabatic temperature gradient a key ingredient in interior and evolution models. Multiple numerically distinct methods exist for computing this gradient, yet their impact on inferred planetary structure and radius has not been systematically assessed. We investigate how the numerical treatment of adiabatic temperature profiles affects inferred planetary radii and internal structure, comparing different methods for evaluating the adiabatic gradient against a ground-truth isentropic baseline, for both the logarithmic and non-logarithmic forms of the temperature differential equation. Static interior models of a one Jupiter mass planet were computed using a state-of-the-art hydrogen-helium equation of state. The choice of numerical method significantly impacts the inferred interior structure and radius. Using the logarithmic temperature equation, central temperatures deviate by several thousand Kelvin and surface radii differ by up to 3.4%, exceeding the one-percent precision of current giant exoplanet radius measurements threefold. The non-logarithmic form reduces deviations to below about 1% for most methods. We recommend spline derivatives to evaluate the adiabatic gradient, combined with the non-logarithmic temperature equation. Finite differencing and direct use of tabulated gradients or derivatives should be avoided.

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

1 major / 3 minor

Summary. The paper claims that different numerical methods for computing the adiabatic temperature gradient in giant planet interior models produce significant variations in predicted radii and central temperatures. For static 1 M_Jup H-He models using a state-of-the-art EOS, comparisons against an independent isentropic baseline show radius differences up to 3.4% (and central temperature deviations of several thousand K) when using the logarithmic form of the temperature differential equation, with deviations reduced to <1% for the non-logarithmic form. The authors recommend spline-based derivatives combined with the non-logarithmic equation and advise against finite differencing or direct tabulated gradients.

Significance. If the numerical sensitivity holds, the result is significant for exoplanet science because it identifies a modeling uncertainty (up to 3.4%) that exceeds the ~1% precision of current radius measurements, potentially affecting inferences of bulk composition and formation history. The direct, parameter-free comparison to a ground-truth isentropic baseline constructed via the EOS (rather than any tested gradient evaluator) provides a reproducible benchmark and supports a concrete recommendation for numerical best practices.

major comments (1)
  1. The central claim of radius differences up to 3.4% is load-bearing for the recommendation, yet the manuscript provides no table or figure explicitly listing the radius and central temperature for each method against the isentropic baseline; without these data the exact magnitude cannot be verified independently.
minor comments (3)
  1. Abstract: replace the qualitative phrase 'several thousand Kelvin' with the specific central-temperature deviations obtained for each method.
  2. Methods section: clarify the precise numerical tolerance and interpolation scheme used to enforce constant entropy in the isentropic baseline so that the ground-truth construction is fully reproducible.
  3. Discussion: add a brief statement on whether the reported differences remain when the EOS is varied within its current uncertainties.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive review and for highlighting the importance of our results for exoplanet radius measurements. We address the major comment below and will revise the manuscript accordingly.

read point-by-point responses
  1. Referee: The central claim of radius differences up to 3.4% is load-bearing for the recommendation, yet the manuscript provides no table or figure explicitly listing the radius and central temperature for each method against the isentropic baseline; without these data the exact magnitude cannot be verified independently.

    Authors: We agree that an explicit tabulation would improve verifiability. In the revised manuscript we will add a new table listing the radius and central temperature for every numerical method against the isentropic baseline, so that the reported maximum differences (3.4% in radius and several thousand K in central temperature) can be checked directly. revision: yes

Circularity Check

0 steps flagged

No significant circularity

full rationale

The paper conducts a controlled numerical sensitivity study comparing multiple methods for computing the adiabatic temperature gradient against an independently defined isentropic baseline (constant entropy enforced directly via the EOS, not via any tested gradient evaluator). Radius and temperature differences are generated by the distinct integration paths of the logarithmic versus non-logarithmic forms and the choice of derivative method (splines, finite differencing, tabulated gradients). No parameters are fitted to produce the reported differences, no self-citations supply load-bearing uniqueness theorems or ansatzes, and the central claim does not reduce to a self-definition or renaming of inputs. The 1D adiabatic framework is an explicit shared modeling assumption rather than a derived result, making the analysis self-contained.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the standard domain assumption that giant-planet interiors are fully convective and adiabatic; no new free parameters, fitted constants, or invented entities are introduced.

axioms (1)
  • domain assumption Giant planet interiors are convective and adiabatic
    Stated as the common modeling assumption whose numerical implementation is being tested.

pith-pipeline@v0.9.0 · 5505 in / 1156 out tokens · 54368 ms · 2026-05-15T00:12:38.955927+00:00 · methodology

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