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JWST Transmission Spectroscopy of TOI-3235 b: Challenges in Constraining Giant Planet Atmospheres Around M Dwarfs Amid Stellar Contamination

T0 review · 2 major / 5 minor · reviewed 2026-08-15 · deepseek-v4-flash

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Pith's one-line read JWST transmission spectroscopy of TOI-3235 b cannot yet determine the planet's atmospheric composition, because stellar contamination and correlated noise let different models fit the same data.

desk verdict A careful, honest null result: the JWST transmission spectrum of TOI-3235 b cannot robustly constrain its atmosphere, and the paper's model-dependent analysis makes that case convincingly. read the letter →

arxiv 2608.04194 v1 pith:4PIMPMVE submitted 2026-08-04 astro-ph.EP

Zoe Ko , Néstor Espinoza , Andrés Jordán , Daniel Bayliss , Edward M. Bryant , Martin Schlecker , Melissa J. Hobson , Rafael Brahm
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Remo Burn Thomas Henning
This is my paper · ORCID
classification astro-ph.EP
keywords exoplanetatmospherestransmissionspectroscopystellarcontaminationMdwarfplanetsGaussianprocessesJWST/NIRSpecsecondaryeclipseatmosphericretrieval
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper tries to establish whether a single JWST/NIRSpec PRISM transit spectrum can reveal the atmospheric composition of TOI-3235 b, a 604 K giant planet orbiting a 0.39 solar-mass M dwarf. The authors find that the answer depends on how stellar contamination is modeled: a retrieval with only parametric star-spot spectra yields a constrained methane abundance, a strongly sub-solar metallicity, and hints of elevated CO and CO2, an interpretation that would challenge standard planet-formation expectations. But that same spectrum leaves wavelength-correlated residuals, especially beyond 4.7 microns, and adding a Gaussian process to absorb that structure broadens every abundance posterior until no reliable composition constraint remains. Because these two readings lead to different formation conclusions, the paper argues that a single secondary-eclipse observation is the decisive next step: emission features would measure the metallicity, while a featureless eclipse spectrum would show that stellar contamination dominates the transit spectrum.

What carries the argument

The load-bearing machinery is a hierarchical retrieval that combines three components: a free-chemistry atmospheric forward model for the planet; a parametric stellar-contamination factor built from synthetic stellar spectra with a fitted spot temperature and covering fraction; and a multiplicative Gaussian process with a Matérn 3/2 kernel, a smooth flexible correlation model, that absorbs residual wavelength-correlated structure. The Gaussian process is the decisive component: when it is switched off, the deterministic model must absorb the long-wavelength residuals into atmospheric parameters, producing apparently precise but model-dependent abundances; when it is switched on, the uncertainty is propagated into the posterior, broadening the constraints. The paper also uses a truncation test at 4.7 microns and a synthetic injection-retrieval test to show that the GP does not erase injected signals and that the broad posteriors reflect real unmodeled structure. The proposed discriminator is a grid of synthetic secondary-eclipse spectra spanning metallicity and cloud-top pressure, which predicts the precision and classification confidence a single eclipse observation would achieve.

What would settle it

A secondary-eclipse spectrum of TOI-3235 b taken with NIRSpec/PRISM at roughly the paper's estimated ~98 ppm per spectral bin would settle the ambiguity: molecular emission features would favor the deterministic sub-solar, possibly disequilibrium interpretation, while a featureless eclipse spectrum would prove that stellar contamination dominates the transit spectrum. A cheaper check is to observe a second transit and compare the 13 bins beyond 4.7 microns: if the same ~-740 ppm weighted-mean residual reproduces, the structure is systematic stellar or instrumental; if it vanishes, the original offset was a noise realization.

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Extended reading notes

Core claim

On the paper's own terms, the central discovery is that the transmission spectrum of TOI-3235 b is consistent with qualitatively different atmospheres depending on the treatment of the host star's active regions. When star spots are modeled deterministically, the retrieval converges on a methane-rich, sub-solar-metallicity atmosphere (prior-corrected $[\mathrm{M/H}]\sim -2.25$ in the full spectrum) with posterior peaks at CO and CO2 abundances that would require disequilibrium chemistry; this is a physically interpretable but conditional scenario. When a Gaussian process is allowed to marginalize over residual wavelength-correlated structure, the long-wavelength residuals drop to a 1$\sigma$ offset but the molecular abundance, metallicity, and C/O posteriors broaden until they are largely uninformative. The paper therefore concludes that the current data cannot distinguish planetary absorption from stellar contamination, and demonstrates through synthetic retrievals that an eclipse observation could break the degeneracy: a single NIRSpec/PRISM eclipse could either classify the metallicity as sub-solar or super-solar with high confidence or, if featureless, supply an empirical M-dwarf contamination spectrum.

Load-bearing premise

The load-bearing premise is that the wavelength-correlated residual structure, especially beyond 4.7 microns, is unmodeled stellar contamination or instrumental noise rather than genuine planetary spectral features; if some of it is planetary, the GP retrieval would be discarding real atmospheric signal and the conclusion that no reliable constraints are possible would be too pessimistic.

Editorial extensions

If this is right

  • If the GP-broadened interpretation is correct, no reliable statement about TOI-3235 b's composition can be made from the current transmission spectrum; the apparent sub-solar metallicity and chemical-disequilibrium hints are conditional on the deterministic contamination model.
  • If the deterministic atmosphere-plus-contamination solution is the true atmosphere, the planet's strongly sub-solar metallicity would sit outside both core-accretion and gravitational-instability expectations, and the elevated CO and CO2 abundances would imply disequilibrium chemistry or solid-depleted gas accretion.
  • A single secondary-eclipse observation at the precision the paper estimates would either measure the metallicity, with high classification confidence for moderate-to-deep cloud decks, or return a featureless spectrum that confirms stellar contamination dominates the transit spectrum.
  • Retrievals on the spectrum truncated at 4.7 microns give different abundances, metallicities, and C/O ratios than the full spectrum, so the long-wavelength residual structure, not the molecular bands alone, drives the deterministic results.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • If the same GP-aided approach were applied to other giant planets around very low-mass stars, transmission spectroscopy alone would likely prove inconclusive for many of them, making eclipse follow-up a standard requirement for this population.
  • A stronger test than a single eclipse would be a joint hierarchical retrieval of the transit and eclipse datasets, letting the planetary model share parameters while the contamination model is constrained by the eclipse spectrum's continuum.
  • The truncation sensitivity test suggests a transferable diagnostic: whenever full-wavelength and truncated retrievals disagree beyond the posterior width, correlated residuals are probably biasing deterministic results, and a GP or a better physical model is needed.
  • Because the GP's broadening depends on the assumed deterministic models, an even more conservative analysis would vary the stellar spectral grid and the number of spot components; the paper itself flags the grid choice as an unquantified source of systematic uncertainty.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

2 major / 5 minor

Summary. The paper presents a JWST/NIRSpec PRISM transmission spectrum of TOI-3235 b (0.665 MJ, 604 K, M-dwarf host), reduced with transitspectroscopy/juliet and analyzed with POSEIDON retrievals in three hierarchical configurations: atmosphere only; atmosphere plus parametric stellar contamination (atm+SC); and atmosphere plus SC plus a Matérn 3/2 Gaussian process (atm+SC+GP). The atmosphere-only and atm+SC retrievals yield constrained CH4 and a prior-corrected sub-solar metallicity, while leaving a ~3.9σ uncertainty-weighted residual at λ>4.7 μm. Adding the GP removes this residual but broadens the molecular abundance posteriors, so the paper concludes that current data cannot robustly constrain the composition. The authors also run truncated-spectrum sensitivity tests and an injection-retrieval control, and use synthetic emission retrievals to argue that a single eclipse observation could distinguish a planetary atmosphere from dominant stellar contamination.

Significance. If the conclusions hold, this is a valuable cautionary demonstration that JWST transmission spectra of giant planets around active M dwarfs can be fundamentally limited by the degeneracy between planetary absorption, parametric stellar contamination, and unmodeled correlated noise; the paper's framing of the atm+SC results as conditional is appropriately careful. The work is strengthened by the public release of data and code, the multiple retrieval configurations, the wavelength-truncation sensitivity tests, the injection-retrieval control, and the transparent prior reweighting for derived metallicity and C/O. The proposed eclipse experiment is a useful, falsifiable path forward even though it is exploratory.

major comments (2)
  1. [§4.3 and Appendix E] The synthetic injection-retrieval test in Appendix E only exercises the case where the deterministic atm+SC model is an adequate description of the data: the injected spectrum is generated from the median atm+SC model, and the GP is shown not to erase the injected signal. In the real spectrum, however, the deterministic model fails specifically in the long-wavelength region, with a 3.9σ uncertainty-weighted residual over the 13 bins at λ>4.7 μm reported in §4.2. The control therefore does not reproduce the regime that matters. If the residual structure contains genuine planetary features (e.g., CO2 near 4.3 μm or CH4 band structure), the Matérn 3/2 GP with a length-scale prior spanning 10^-3 to 10^2 μm could absorb that signal and artificially broaden the atmospheric posteriors. Section 5.1 already gives the more careful framing that the data do not contain enough information to distinguish planetary absorption, stellar contamination, and residual correlated structure, but the abstract's claim that the GP 'prevents robust constraints' is stronger than the evidence supports. Please either add an injection test in which a planetary signal is embedded in the residual structure while the deterministic model is misspecified, or soften the abstract and conclusion to match the §5.1 framing.
  2. [§3.5 and Appendix D] The headline sub-solar metallicity of the atm+SC retrieval is a consequence of the importance-reweighting choice described in §3.5 and Appendix D: independent log-uniform abundance priors induce a strongly super-solar-weighted prior on metallicity, and reweighting to a uniform-in-log10(Z/Z⊙) target prior shifts the posterior to sub-solar values. This is a defensible choice, but it is not the only reasonable one, and the paper does not show that the sub-solar conclusion is robust to alternative target priors (e.g., uniform in Z or a log-normal prior centered at solar). Since the abstract explicitly invokes the sub-solar metallicity as challenging formation scenarios, a sensitivity test under alternative target priors should be reported, or the conditional nature of this result should be stated even more prominently.
minor comments (5)
  1. [§3.1] The atmospheric model is described with a single retrieved 'Atmospheric Temperature T' but the isothermal assumption is never stated explicitly; please state clearly that the model assumes an isothermal atmosphere.
  2. [Figure 3] In the atm+SC+GP panel, it would be informative to show the GP contribution to the model separately (as in Appendix E's orange curve) so the reader can see what spectral structure is being absorbed by the GP rather than by the deterministic components.
  3. [§4.2] The model comparisons quote ΔlnZ values without associated numerical uncertainties; reporting the evidence uncertainties from the nested sampling runs would help assess whether the ΔlnZ=3, 5, and 10 differences are meaningful given sampling noise.
  4. [§5.3] Equation (7) propagates the transmission light-curve residual scatter to estimate eclipse precision, but eclipse observations have different systematics (no transit, different background and pointing drifts); please justify that this is a representative noise estimate for the proposed single eclipse observation.
  5. [Table 2] The notation '10^2' and '10^3' in the table header should be typeset as superscripts to avoid confusion with powers of ten.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the retrieval conclusions are empirical model comparisons, the GP is a disclosed nuisance component, and the eclipse analysis is a forward-model sensitivity study.

full rationale

This paper is a Bayesian retrieval and sensitivity analysis rather than a derivation chain in which a prediction reduces to its own input. The central claim that inferred atmospheric properties are model-dependent and that GP marginalization broadens the posteriors is produced by running three distinct retrieval configurations on the same measured spectrum; the differences are presented as empirical outputs (Section 4, Figures 3-5) and not as quantities defined by the priors. The GP is explicitly introduced as 'a multiplicative GP that fits the residuals from the atmospheric and stellar contamination model' (Section 3.3), and the injection-retrieval control in Appendix E tests whether the GP erases genuine signals; its admitted limitation—that it cannot certify the real-data case—is a modeling risk, not a circular reduction. The eclipse analysis in Section 5.3 is a forward-model grid sensitivity study: synthetic spectra with injected metallicities are generated and re-retrieved to map W68 and P_correct, with no real-data eclipse forecast derived from a fitted parameter. Citations to Espinoza et al. 2025 and to the reduction/sampling software are tool and framework citations to peer-reviewed, independently published work; they are not used as an unverified uniqueness theorem nor as the sole justification for the main conclusion. No equation or fitted quantity is renamed as a prediction, and no derived quantity is defined in terms of the quantity it is claimed to explain.

Assumptions & free parameters 8 free parameters · 7 assumptions · 0 invented entities

The central claim is model-dependence, which rests on the retrieval framework's assumptions about the forward model, stellar spectra, and noise model. The paper itself acknowledges the BT-SETTL grid limitation (Section 3.2), and the GP-assumption is tested in Appendix E. Free parameters are the ordinary retrieval parameters; none are invented ad hoc beyond the standard POSEIDON setup.

free parameters (8)
  • Ten molecular log mixing ratios (CO2, CH4, H2O, NH3, HCN, CO, SO2, H2S, C2H2, C2H4) = CH4 constrained (logX_CH4 ~ -5.18 and -2.33 modes in atm+SC); others mostly unconstrained
    Central retrieval outputs; prior-corrected metallicity and C/O are derived from them; their posteriors drive the model-dependence result.
  • Atmospheric temperature T = Not reported in abstract; retrieved in [100, 1000] K
    Free parameter in the POSEIDON free-chemistry retrieval.
  • Cloud top pressure log P_cloud, haze amplitude log a, haze scattering slope gamma = gamma = -8.82 (+4.15/-4.83), log a = 4.07 (+1.58/-1.48) in atm+SC
    Haze and cloud parameters are strongly degenerate with stellar contamination; their drift across models is key evidence of model dependence.
  • Reference pressure log P_ref = Not reported in text
    Sets the pressure at which the atmospheric integration begins; partially degenerate with the flux offset.
  • White noise amplitude log sigma_w and flux offset = White light sigma_w = 227.9 (+4.8/-4.9) ppm; flux offset 0.00066 in white light fit
    Nuisance parameters to absorb underestimated errors and absolute transit depth.
  • Stellar heterogeneity temperature(s) and covering fraction(s) T_het, f_spot, f_fac = T_het = 3140 (+190/-1320) K, log f_het = -1.40 (+0.48/-0.37) in atm+SC
    Parametric spot and faculae model; the one-component version wins by Delta lnZ = 5 and drives the contamination correction.
  • GP length scale log rho and amplitude log sigma_GP = Not reported in text; priors in Table 2
    Matern 3/2 GP hyperparameters that absorb residual correlated structure; their inclusion broadens the posterior, which is central to the result.
  • Eclipse simulation P-T profile temperatures T_upper and T_deep = Forward models use 400 K and 800 K; retrieval priors 400-1000 K
    The eclipse forecast assumes this two-parameter gradient pressure-temperature profile; results depend on it.
assumptions (7)
  • domain assumption POSEIDON free-chemistry transmission forward model correctly predicts observable transit spectra of H2/He giant planet atmospheres.
    Used for all retrievals (Section 3.1); any systematic error in line lists or temperature structure propagates into abundances.
  • domain assumption BT-SETTL synthetic spectra represent the M dwarf photosphere and spot and facula spectra well enough for the contamination model.
    Section 3.2; the authors note other grids may give different shapes, so this is an acknowledged source of systematic uncertainty.
  • domain assumption The Rackham et al. (2018) multiplicative contamination factor with a homogeneous transit chord is a valid description.
    Equations 2 to 5; no spot-crossing is observed, but unocculted heterogeneity is assumed uniformly distributed across the stellar disk.
  • domain assumption A Matern 3/2 Gaussian process in wavelength captures residual correlated noise without absorbing true astrophysical signals.
    Section 3.3 and Appendix E; tested on injected signals, but not provable for the real data.
  • domain assumption Photometric noise in the eclipse forecast is white and follows the transmission light curve residuals via Equation 7.
    Section 5.3; the precision estimate of about 98 ppm per bin assumes N_in approximately equals N_out and uncorrelated residuals.
  • domain assumption Stellar and planetary physical parameters from Hobson et al. (2023) are accurate.
    Used in light curve fitting and retrieval gravity and radius; adopted from prior literature.
  • domain assumption VULCAN equilibrium calculations are representative of the true chemical state for the disequilibrium comparison.
    Appendix A; assumed thermochemical equilibrium at T_eq = 604 K and solar or super-solar C/O.

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Cite this review

Pith. "Pith review of JWST Transmission Spectroscopy of TOI-3235 b: Challenges in Constraining Giant Planet Atmospheres Around M Dwarfs Amid Stellar Contamination." pith.science (2026). https://pith.science/paper/4PIMPMVE

@misc{pith2026260804194,
  author       = {Pith},
  title        = {Pith review of: JWST Transmission Spectroscopy of TOI-3235 b: Challenges in Constraining Giant Planet Atmospheres Around M Dwarfs Amid Stellar Contamination},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/4PIMPMVE}},
  note         = {Machine review of arXiv:2608.04194}
}
read the original abstract

Giant planets orbiting low-mass M dwarfs challenge current planet formation theories, which predict that such planets are unlikely to form. Characterizing their atmospheres can provide key insight into their origins, but analysis is complicated by stellar contamination in transmission spectra. We present a JWST/NIRSpec PRISM transmission spectrum of TOI-3235 b, a 604 K, 0.665 Jupiter-mass giant planet orbiting a 0.39 Solar-mass M dwarf. We apply a hierarchical retrieval framework incorporating an atmospheric model, a parametric stellar contamination model, and a Gaussian process (GP) to capture residual structure not explained by these deterministic components. We find that the inferred atmospheric properties are model-dependent: retrievals that treat stellar contamination deterministically yield a constrained CH4 abundance corresponding to a sub-solar metallicity that would challenge standard expectations from both core accretion and gravitational instability, along with potentially elevated CO and CO2 abundances that would require chemical disequilibrium. However, residual wavelength-correlated structure suggests the deterministic model is incomplete. Including a GP to marginalize over this structure broadens the atmospheric posterior distributions, preventing robust constraints on the atmospheric composition and highlighting the challenge of characterizing giant planet atmospheres around M dwarfs. We demonstrate that an eclipse observation could clarify these model-dependent ambiguities: detected emission features would constrain the planet's metallicity and test formation scenarios, while a featureless spectrum would confirm stellar contamination dominates the transmission spectrum, providing an empirical M dwarf contamination spectrum.

Figures

Figures reproduced from arXiv: 2608.04194 by the authors.

Figure 1
Figure 1. White light curve fit against data (top panel) and residuals (bottom panel) [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Sample wavelength-dependent light curve fits. There are a total of 441 curves spanning from 0.63 µm to 5.59 µm. light curve analysis, allowing only the planet-to-star ra￾dius ratio, limb-darkening coefficients and instrumental systematics to vary with wavelength [PITH_FULL_IMAGE:figures/full_fig_p003_2.png] view at source ↗
Figure 3
Figure 3. Retrieved spectra from each retrieval. The solid lines represent the median spectrum, and the shaded regions show the 1σ bounds. The first panel shows the retrieval only fitting for the atmospheric model, the second shows the retrieval fitting for the atmospheric model and the stellar contamination model, and the third shows the retrieval fitting for the atmospheric model, the stellar contamination model, and a Gaus… view at source ↗
Figures from the paper (17 more)
Figure 4
Figure 4. Figure 4: Retrieved trace abundances for all three retrievals. Each panel shows the posterior distribution of log Xi for one molecular species. Numerical labels above each panel summarize the abundance constraint: for molecules with two-sided bounded posteriors, we quote the med…
Figure 5
Figure 5. Figure 5: Posterior distributions for the stellar contamination and haze parameters across the three retrieval models. From left to right: photosphere temperature (Tphot), heterogeneity (spot) temperature (Thet), log heterogeneity (spot) covering fraction (log fspot), log haze s…
Figure 6
Figure 6. Figure 6: Prior-corrected metallicity and C/O posteriors for the full-spectrum retrievals, with truncated-spectrum atm+SC and atm+SC+GP results shown for comparison. stellar contamination can bias water inferences toward artificially high abundances. We again observe bimodal￾ity…
Figure 7
Figure 7. Figure 7: Comparison between the atm+SC abundance posteriors and VULCAN chemical equilibrium predictions for CO2 and CO. The blue histograms show the full-spectrum atm+SC posterior distributions, while the orange histograms show the truncated atm+SC posterior distributions (excl…
Figure 8
Figure 8. Figure 8: Three representative cases from our synthetic emission retrieval experiment. The left panels show the synthetic emission spectrum (gray points), the injected forward model (black dashed line), and the retrieved spectrum (orange line and shaded 1σ region). The right pan…
Figure 9
Figure 9. Figure 9: Emission retrieval performance across a grid of injected atmospheric metallicities and cloud-top pressures. The left panel shows W68, the width of the central 68% credible interval of the retrieved metallicity posterior, indicating metallicity precision. The right pane…
Figure 10
Figure 10. Figure 10: Chemical equilibrium abundance profiles computed with VULCAN for TOI-3235 b across metallicities from 0.01× to 100× solar. Solid colored curves show models with solar C/O (0.55), while dashed colored curves show models with super-solar C/O (1). The shaded orange regio…
Figure 11
Figure 11. Figure 11: Posterior distributions from retrieval fitting for the atmospheric model. C. RETRIEVALS ON TRUNCATED AND UNTRUNCATED SPECTRUM Figures 14 to 17 compare retrievals performed on the full transmission spectrum and on a spectrum truncated at 4.7 µm, showing how the long-wa…
Figure 12
Figure 12. Figure 12: Posterior distributions from retrieval fitting for the atmospheric model and stellar contamination model. then assigned a weight wj ∝ 1 πind(qj ) , (D1) where qj is the value of the derived quantity for the jth posterior sample and πind is the induced prior density ev…
Figure 13
Figure 13. Figure 13: Posterior distributions from retrieval fitting for the atmospheric model, the stellar contamination model, and a Gaussian process. weights. This sampling noise does not affect our conclusion: the atm+SC+GP retrieval does not provide strong evidence for a narrowly cons…
Figure 14
Figure 14. Figure 14: Atm+SC retrieval on the full spectrum and the truncated spectrum. The left panel shows both median retrieved spectra and 1σ bounds and the right shows the retrieved abundances for four trace species. The two retrievals yield different results. are crucial for the atm+…
Figure 15
Figure 15. Figure 15: Posterior distributions from atm+SC retrieval on the truncated spectrum [PITH_FULL_IMAGE:figures/full_fig_p025_15.png]
Figure 16
Figure 16. Figure 16: Atm+SC+GP retrieval on the full spectrum and the truncated spectrum. The left panel shows both median retrieved spectra and 1σ bounds and the right shows the retrieved abundances for four trace species. The two retrievals yield similar results [PITH_FULL_IMAGE:figure…
Figure 17
Figure 17. Figure 17: Posterior distributions from atm+SC+GP retrieval on the truncated spectrum [PITH_FULL_IMAGE:figures/full_fig_p027_17.png]
Figure 18
Figure 18. Figure 18: Derived metallicity posteriors before and after correcting for the induced metallicity prior. The top row shows the uncorrected metallicity posteriors, with the induced metallicity prior shown in gray. The bottom row shows the prior-corrected posteriors obtained using…
Figure 19
Figure 19. Figure 19: Derived C/O posteriors before and after correcting for the induced C/O prior. The top row shows uncorrected posteriors in log10(C/O), with the induced C/O prior shown in gray. The bottom row shows prior-corrected posteriors obtained using the inverse-density weights f…
Figure 20
Figure 20. Figure 20: Synthetic retrieval test assessing whether the GP component absorbs atmospheric and stellar contamination signals. The synthetic data were generated from a representative atm+SC model using the median parameters from the atm+SC retrieval, with Gaussian noise added fol…

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