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arxiv: 2604.07176 · v1 · submitted 2026-04-08 · 🌌 astro-ph.EP

Panchromatic View of the Frigid Jovian Exoplanet COCONUTS-2 b

Matthieu Ravet , Micka\"el Bonnefoy , Ga\"el Chauvin , Zhoujian Zhang , Jacqueline K. Faherty , Ma\"el Voyer , Mark W. Phillips , Pascal Tremblin
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Rocio Kiman Jessica Copeland James J. Mang Caroline V. Morley Helena K\"uhnle Benjamin Charnay Sam de Regt Paul Molli\`ere Simon Petrus Allan Denis Alice Radcliffe Paulina Palma-Bifani Arthur Vigan Mathilde M\^alin Gabriel-Dominique Marleau Elena Manjavacas Kevin Hoy Elisabeth C. Matthews Thomas K. Henning
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Pith reviewed 2026-05-10 18:10 UTC · model grok-4.3

classification 🌌 astro-ph.EP
keywords COCONUTS-2 bexoplanet atmosphereMIRI spectroscopyself-consistent modelscold giant planetspectral energy distributionmolecular featuresplanetary mass
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0 comments X p. Extension

The pith

Panchromatic 1-15 micron observations with ATMO2020++ models constrain COCONUTS-2 b to 496 K, 1.03 Jupiter radii, and 7.3 Jupiter masses.

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

The paper combines a new high signal-to-noise MIRI-LRS spectrum showing clear H2O, CH4, and NH3 features with near-infrared spectra and photometry to build a nearly continuous 1-15 micron spectral energy distribution for the cold exoplanet COCONUTS-2 b. Five grids of self-consistent atmospheric models are tested against the full dataset, with ATMO2020++ (with and without PH3) emerging as statistically preferred even though all grids underpredict flux in the Y and N bands. The best-fit parameters are T_eff of 496 K, log g of 4.30 dex, near-solar metallicity, and radius of 1.03 Jupiter radii; these values plus the known system age then yield a bolometric luminosity and a mass of 7.3 Jupiter masses from cooling tracks. A sympathetic reader would care because the work supplies one of the most complete observational constraints yet on a frigid directly imaged giant planet, testing how well current models handle chemistry and energy balance at low temperatures.

Core claim

The MIRI-LRS data (5.45-11 microns, accounting for 41 percent of the bolometric flux) complete the spectral energy distribution when merged with Gemini/FLAMINGOS-2, JWST/NIRSpec, WISE, and Spitzer observations. Fitting the ATMO2020++ atmospheric model grid to this combined dataset, after accounting for correlated noise via Gaussian processes, produces T_eff = 496^{+5}_{-3} K, log(g) = 4.30^{+0.04}_{-0.02} dex, [M/H] = -0.02^{+0.03}_{-0.02} dex, and R = 1.03^{+0.01}_{-0.02} R_jup. Combined with the system age of 414 ± 23 Myr, evolutionary cooling models then predict a mass of 7.3 ± 0.3 M_jup and a precise luminosity of log(L/L_⊙) = -6.166 ± 0.002 dex.

What carries the argument

Self-consistent atmospheric model grids, especially ATMO2020++, fitted to the full 1-15 micron spectral energy distribution to extract temperature, gravity, metallicity, radius, luminosity, and mass.

If this is right

  • The MIRI contribution enables a bolometric luminosity precise to 0.002 dex, tightening the mass estimate from evolutionary models.
  • All five tested model grids reproduce the main molecular absorption features but share a systematic flux deficit in the Y and N bands.
  • The derived parameters remain consistent with earlier studies once correlated noise is modeled with Gaussian processes.
  • The presence of strong NH3 absorption confirms ammonia as a detectable constituent in atmospheres near 500 K.

Where Pith is reading between the lines

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

  • Improving the underpredicted Y- and N-band fluxes in the models would allow tighter constraints on additional opacity sources or vertical mixing.
  • The same multi-instrument SED approach could be applied to other cold directly imaged companions to build a comparative sample of their atmospheric properties.
  • A revised system age would scale the inferred mass linearly through the cooling tracks, altering formation-scenario interpretations.
  • The clear NH3 detection at this temperature provides a calibration point for ammonia chemistry and cloud formation in future model grids.

Load-bearing premise

The self-consistent atmospheric models correctly capture the temperature structure, molecular chemistry, and radiative transfer throughout this cold atmosphere even though they systematically underpredict the observed flux in the Y and N bands.

What would settle it

An independent dynamical mass measurement for COCONUTS-2 b that lies more than 1 M_jup away from 7.3 M_jup at the 3-sigma level would falsify the combination of the derived atmospheric parameters and the cooling-model mass inference.

Figures

Figures reproduced from arXiv: 2604.07176 by Alice Radcliffe, Allan Denis, Arthur Vigan, Benjamin Charnay, Caroline V. Morley, Elena Manjavacas, Elisabeth C. Matthews, Gabriel-Dominique Marleau, Ga\"el Chauvin, Helena K\"uhnle, Jacqueline K. Faherty, James J. Mang, Jessica Copeland, Kevin Hoy, Ma\"el Voyer, Mark W. Phillips, Mathilde M\^alin, Matthieu Ravet, Micka\"el Bonnefoy, Pascal Tremblin, Paulina Palma-Bifani, Paul Molli\`ere, Rocio Kiman, Sam de Regt, Simon Petrus, Thomas K. Henning, Zhoujian Zhang.

Figure 1
Figure 1. Figure 1: Top panel: Forward modeling results of the combined COCONUTS-2 b observations. The black solid lines represent the spectroscopic data (from left to right: Gemini/FLAMINGOS-2, JWST/NIRSpec, and JWST/MIRI-LRS) while colored lines represents each Rλ ∼ 100 model ("classic"). Pink and white stars indicate the photometric observations (WISE and Spitzer). Grey-shaded regions indicate the masked wavelengths during… view at source ↗
Figure 2
Figure 2. Figure 2: Top-left panel: Interpolated pressure–temperature (P–T) profiles for models providing a P–T grid (excluding BT-Settl) in Sect. 3.1. Re￾maining panels: Posteriors of key parameters. Vertical dashed indicate the boundaries of the respective model grids when encountered during the inversion [PITH_FULL_IMAGE:figures/full_fig_p006_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Corner plot comparing forward modeling using the ATMO2020++ grid with (dark green) and without (light green) Gaus￾sian Processes (GP). Black points indicate the mean predictions from evolutionary models with their associated error bars (see Sect. 3.3). in the FLAMINGOS-2 matrix with correlated noise extending across multiple spectral channels. Its block-like structure arises from the spectral windows used … view at source ↗
read the original abstract

We use a high signal-to-noise MIRI-LRS spectrum (5.45 - 11 $\mu$m, R$_\lambda$ $\sim100$) of COCONUTS-2~b revealing prominent molecular features of H$_2$O, CH$_4$ and NH$_3$. This dataset is combined with spectra from Gemini/FLAMINGOS-2 and JWST/NIRSpec (G395H), as well as photometry from WISE and Spitzer, resulting in almost continuous wavelength coverage from 1 to 15 $\mu$m. We analyze the data using five grids of self-consistent atmospheric models, spanning a wide range of T$_\text{eff}$, log(g), and [M/H]. We also investigate the use of Gaussian Processes to account for correlated noise either caused by the spectrograph or by systematic departures of models in the inversion framework. All models manage to fit the overall combined observations but predict fainter flux in Y- and N-bands. Classical model comparison suggests that the ATMO2020++ synthetic specra (with and without PH$_3$) are statistically preferred. Fitting for the correlated noise of the three spectroscopic instruments, ATMO2020++ models yields constraints consistent with previous studies and evolutionary models predictions: T$_\text{eff}$ $=496^{+5}_{-3}$ K, log(g) $=4.30^{+0.04}_{-0.02}$ dex, [M/H] $=-0.02^{+0.03}_{-0.02}$ dex, and R $=1.03^{+0.01}_{-0.02}$ R$_\text{jup}$. The extended wavelength coverage provided by MIRI (accounting for 41% of the bolometric flux) completes the SED, yielding a precise luminosity estimation of log(L/L$_{\odot}$) $=-6.166\pm0.002$ dex. Combined with a previous estimate of the system age ($414\pm23$ Myr), cooling models predict a mass of M $=7.3\pm0.3$ M$_\text{jup}$.

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 manuscript presents a panchromatic SED analysis of the directly imaged exoplanet COCONUTS-2 b, combining a new high-S/N JWST/MIRI-LRS spectrum (5.45–11 μm) with NIRSpec G395H, Gemini/FLAMINGOS-2 spectra, and WISE/Spitzer photometry to achieve near-continuous 1–15 μm coverage. Five self-consistent atmospheric model grids are fitted to the data, with Gaussian Processes used to model correlated noise or systematic model–data residuals; the preferred ATMO2020++ grid yields T_eff = 496^{+5}_{-3} K, log g = 4.30^{+0.04}_{-0.02}, [M/H] = −0.02^{+0.03}_{-0.02}, R = 1.03^{+0.01}_{-0.02} R_Jup. Bolometric luminosity is obtained by direct integration of the observed SED (log L/L_⊙ = −6.166 ± 0.002), and mass (7.3 ± 0.3 M_Jup) follows from cooling tracks given the system age.

Significance. If the atmospheric-parameter posteriors are robust, the work supplies one of the most precise characterizations of a cold (~500 K) Jovian exoplanet, with MIRI supplying 41 % of the bolometric flux and completing the SED. Strengths include the use of multiple independent model grids, explicit GP treatment of correlated noise, and direct (model-independent) luminosity integration; these elements allow a clean comparison with evolutionary predictions and prior studies.

major comments (2)
  1. [Abstract and §3] Abstract and §3 (atmospheric modeling): All five grids, including the statistically preferred ATMO2020++ models, systematically underpredict flux in the Y- and N-bands. Because the Y-band lies on the Wien tail and the N-band overlaps the MIRI range that supplies 41 % of the bolometric flux, any residual mismatch not fully absorbed by the GP kernel can shift the joint posterior on T_eff, log g, [M/H], and R. The manuscript does not report quantitative tests (e.g., fits with those bands masked or with varied GP length-scale priors) to demonstrate that the quoted uncertainties (T_eff = 496^{+5}_{-3} K etc.) remain unbiased.
  2. [§4] §4 (results and fitting procedure): The exact likelihood, priors on the free parameters (T_eff, log g, [M/H], R), GP kernel forms for each of the three spectroscopic instruments, and full error budget (including hyperparameter marginalization) are not specified in sufficient detail. Without these, it is impossible to assess whether the reported parameter uncertainties fully propagate the known model–data discrepancies in the Y- and N-bands.
minor comments (2)
  1. [Abstract] The abstract states that MIRI accounts for 41 % of the bolometric flux but does not explicitly list the wavelength intervals used for the integration; a short table or sentence in §2 would improve clarity.
  2. Notation for surface gravity is given as both “log(g)” and “log g” in different places; adopt a single convention throughout.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed comments. We address each major point below and describe the revisions that will be incorporated to improve clarity and robustness.

read point-by-point responses

  1. Referee: [Abstract and §3] All five grids, including the statistically preferred ATMO2020++ models, systematically underpredict flux in the Y- and N-bands. Because the Y-band lies on the Wien tail and the N-band overlaps the MIRI range that supplies 41 % of the bolometric flux, any residual mismatch not fully absorbed by the GP kernel can shift the joint posterior on T_eff, log g, [M/H], and R. The manuscript does not report quantitative tests (e.g., fits with those bands masked or with varied GP length-scale priors) to demonstrate that the quoted uncertainties (T_eff = 496^{+5}_{-3} K etc.) remain unbiased.

    Authors: We explicitly note in the manuscript that all model grids underpredict flux in the Y- and N-bands. The Gaussian Process terms fitted to each spectroscopic dataset are designed to capture correlated residuals, including systematic model-data mismatches in specific wavelength regions. The derived parameters remain consistent with independent literature values and with evolutionary-model predictions at the system age, providing supporting evidence that the GP marginalization has mitigated bias. To directly address the referee's concern, we will add quantitative robustness tests in the revised manuscript: (i) refits with the Y- and N-band photometry masked, and (ii) refits with varied GP length-scale priors. These additional results will be presented to confirm that the reported posterior uncertainties are not materially affected. revision: yes

  2. Referee: [§4] The exact likelihood, priors on the free parameters (T_eff, log g, [M/H], R), GP kernel forms for each of the three spectroscopic instruments, and full error budget (including hyperparameter marginalization) are not specified in sufficient detail. Without these, it is impossible to assess whether the reported parameter uncertainties fully propagate the known model–data discrepancies in the Y- and N-bands.

    Authors: We agree that §4 would benefit from a more complete technical description of the fitting procedure. In the revised manuscript we will expand this section to specify: the exact likelihood function employed, the prior distributions placed on T_eff, log g, [M/H], and R, the functional form of the GP kernel (including length-scale and amplitude hyperparameters) adopted for the NIRSpec, FLAMINGOS-2, and MIRI spectra separately, and the method used to marginalize or optimize the GP hyperparameters. This added detail will make the full error budget transparent and allow readers to evaluate how model-data discrepancies are propagated into the final parameter uncertainties. revision: yes

Circularity Check

0 steps flagged

No circularity: luminosity integrated directly, parameters fitted to data, mass from independent cooling tracks

full rationale

The derivation begins with direct integration of the observed 1–15 μm SED (MIRI contributing 41% of bolometric flux) to obtain log(L/L⊙) = −6.166 ± 0.002. Atmospheric parameters are obtained by χ² minimization of five external self-consistent model grids (including ATMO2020++) against the combined spectra and photometry, with Gaussian Processes added to absorb correlated residuals in Y- and N-bands where models underpredict flux. Radius, T_eff, log g and [M/H] are therefore outputs of the fit, not inputs. Mass follows from standard evolutionary cooling models evaluated at the independently measured system age (414 ± 23 Myr). No equation defines a quantity in terms of itself, no fitted parameter is relabeled as a prediction, and no load-bearing premise rests on a self-citation chain or imported uniqueness theorem. The analysis explicitly acknowledges model–data mismatches and cross-checks results across grids, keeping the chain self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

5 free parameters · 2 axioms · 0 invented entities

Analysis rests on pre-existing atmospheric model grids and evolutionary cooling models; the central claims are obtained by fitting these grids to new data rather than deriving from first principles.

free parameters (5)
  • effective temperature = 496 K
    Fitted parameter from model-grid comparison to spectra
  • surface gravity = 4.30 dex
    Fitted parameter from model-grid comparison to spectra
  • metallicity = -0.02 dex
    Fitted parameter from model-grid comparison to spectra
  • radius = 1.03 Rjup
    Fitted parameter from model-grid comparison to spectra
  • luminosity
    Integrated from the observed spectral energy distribution
axioms (2)
  • domain assumption Self-consistent atmospheric models (ATMO2020++ and others) accurately represent the temperature, chemistry, and radiative transfer in this cold exoplanet atmosphere
    Invoked when selecting preferred models and deriving parameters from spectral fit
  • domain assumption Evolutionary cooling models correctly map luminosity and system age to planetary mass for this object
    Used to convert the measured luminosity into the reported mass

pith-pipeline@v0.9.0 · 5818 in / 1769 out tokens · 49127 ms · 2026-05-10T18:10:33.252878+00:00 · methodology

discussion (0)

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Reference graph

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