Hot Rocks Survey III: A deep eclipse for LHS 1140c and a new Gaussian process method to account for correlated noise in individual pixels

Alexander D. Rathcke; Am\'elie Gressier; Brice-Olivier Demory; Daniel Kitzmann; Erik Meier Vald\'es; Hannah Diamond-Lowe; Jegug Ih; Jo\~ao M. Mendon\c{c}a; Kathryn Jones; Kevin Heng

REVIEW 2 major objections 4 minor 4 cited by

Hot Rocks Survey III: A deep eclipse for LHS 1140c and a new Gaussian process method to account for correlated noise in individual pixels

T0 review · 2 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read A deep 15 µm eclipse of the rocky super-Earth LHS 1140c, detected at >5σ by three independent analyses, puts its dayside at 561±44 K, matching a low-albedo bare rock and ruling out a wide range of CO2 and H2O atmospheres at >3σ, while a…

desk verdict Solid eclipse measurement and a reusable pixel-level GP method, but the abstract's H2O exclusion overstates what the analysis supports. read the letter →

arxiv 2505.22186 v2 pith:KDGWBARV submitted 2025-05-28 astro-ph.EP astro-ph.IM

Mark Fortune , Neale P. Gibson , Hannah Diamond-Lowe , João M. Mendonça , Amélie Gressier , Daniel Kitzmann , Natalie H. Allen , Prune C. August

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Jegug Ih Erik Meier Valdés Merlin Zgraggen Lars A. Buchhave Brice-Olivier Demory Néstor Espinoza Kevin Heng Kathryn Jones Alexander D. Rathcke

This is my paper · ORCID

classification astro-ph.EPastro-ph.IM

keywords exoplanetatmosphereseclipsephotometryGaussianprocesspixel-levelfittingMIRILHS1140cheatredistributionsuper-Earth

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

This paper claims that three 15 µm eclipses of the rocky super-Earth LHS 1140c, observed with JWST's MIRI imager, show a dayside that is hot, bright, and consistent with a low-albedo bare rock that does not redistribute heat. The recovered dayside brightness temperature is 561±44 K, close to the 537±9 K maximum expected for a zero-albedo rock with no heat redistribution, and inconsistent with full redistribution. Combining this measurement with atmospheric forward models, the paper claims to rule out pure CO2 atmospheres with surface pressures of 10 mbar or more, pure H2O atmospheres of 1 bar or more, and CO2-rich or Earth-like 1 bar atmospheres at better than 3σ. It also introduces a Gaussian process method that fits individual pixel light curves jointly, which on simulated data recovers eclipse depths more precisely and reliably than aperture photometry when systematics contaminate a single pixel. If the bare-rock interpretation is right, LHS 1140c sits on the airless side of the cosmic shoreline and provides a benchmark for atmospheric escape around M dwarfs.

What carries the argument

The argument is carried by two pieces of machinery. The first is a two-dimensional Gaussian process that joint-fits pixel light curves rather than an aperture sum, with a covariance kernel written as a sum of Kronecker products, $K = K_p \otimes K_t + \Sigma_p \otimes \Sigma_t$, so the exact likelihood scales as $O(2N_p^3 + 2N_t^3 + N_pN_t(N_p+N_t))$ instead of $O(N_p^3N_t^3)$. Its pixel-side components model flux-conserved anti-correlations between neighbouring pixels, independent pixel systematics, common systematics, interpixel capacitance, and background row/column noise, and its shared time kernel captures PSF evolution; this lets the fit down-weight pixels contaminated by a cosmic-ray persistence effect. The second is the physical interpretation chain: a heat-balance model with a redistribution factor (from Koll 2022) sets the dayside temperature for bare rocks and atmospheres, HELIOS computes emission spectra, and the measured 15 µm eclipse depth is compared to those spectra to exclude atmospheres.

What would settle it

A phase-curve observation of LHS 1140c that detects nightside flux or a phase offset, or a rerun of the atmospheric comparison with heat redistribution fixed to zero, would directly test the bare-rock claim.

Watch

Extended reading notes

Core claim

The central discovery is a deep eclipse: joint fits of the three LHS 1140c eclipses deliver a 15 µm planet-to-star flux ratio of about 270 ppm at >5σ, with aperture photometry, the new pixel Gaussian process fit, and an independent reduction all agreeing. Converting the eclipse depth through an absolute flux calibration gives a dayside brightness temperature of 561±44 K, matching the 537±9 K maximum for a smooth zero-albedo bare rock with no heat redistribution and rejecting the 421±7 K expected from full redistribution. Atmospheric forward models with the analytic heat-redistribution prescription predict that any substantial CO2 or H2O atmosphere would cool the dayside and add 15 µm absorption; the observed depth rules these out, leaving the planet best described as a low-albedo airless rock, possibly with an optically thin or spectrally bland residual atmosphere.

Load-bearing premise

The pure H2O and mixed-atmosphere exclusions depend on the analytic heat-redistribution formula relating surface pressure to redistribution; if that formula is replaced by assuming no redistribution, 1-bar pure H2O models become consistent, and the comparison does not propagate the observed ~10% excess of stellar flux over the BT-Settl models used.

Editorial extensions

If this is right

LHS 1140c joins TRAPPIST-1b and c as rocky planets whose 15 µm eclipses point to airless or nearly airless surfaces, strengthening the picture that low-mass M-dwarf planets lose their atmospheres.
A broad class of secondary atmospheres—thick CO2, H2O, SO2/CO2 mixtures, and Earth-like 1 bar N2/O2 with >100 ppm CO2—is excluded, so future characterization can focus on tenuous or optically thin atmospheres.
The new pixel-level Gaussian process method can be applied to other MIRI time series, including LRS spectroscopy, where correlated noise between neighbouring pixels is currently ignored in standard analyses.
The settling-ramp trend with the previously used MIRI filter suggests a simple operational change—switching the filter before target acquisition—could reduce the amount of data needing to be discarded from future observations.

Reading between the lines

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

If the ~10% stellar-model flux offset is real, the forward-model eclipse depths should be shifted shallower, which would make the atmospheric exclusions even stronger rather than weaker; the brightness temperature itself does not depend on stellar models.
The same anti-correlated pixel systematics found here may explain the excess scatter seen in one-pixel-wide spectroscopic extractions, and the pixel-GP framework could be extended to spectra by sharing the eclipse model only across pixels at the same wavelength.
The eclipse-time constraint that LHS 1140c's secondary eclipse occurs 2.8±0.9 minutes early implies a small non-zero eccentricity; if confirmed by more eclipses, it would be a rare eccentricity constraint for a tidally locked rocky planet.
A direct test of the bare-rock claim is to observe LHS 1140c in a second MIRI band such as F1800W or a shorter wavelength, where CO2 and SO2 have different absorption strengths; the current models predict the same bare-rock depth in those bands.

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Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

This is a solid, careful paper, and the part that is most worth your time is not the astrophysical conclusion. The first 15 µm eclipse detection of LHS 1140c is a real measurement, and it is consistent across three independent analyses (aperture photometry, the new pixel-level GP fit, and a secondary pipeline) at better than 5σ. The inferred brightness temperature of 561±44 K fits a low-albedo bare rock with negligible heat redistribution, and the stronger exclusions (pure CO2 ≥10 mbar, CO2/N2 mixtures at 1 bar) survive changes in the assumed heat redistribution. That is a useful result for the cosmic-shoreline debate.

The genuinely new thing here is the pixel-level Gaussian process method. The authors jointly fit individual pixel light curves with a shared eclipse model, PSF shifts, and a kernel that separates pixel and time covariances, so the exact GP likelihood is tractable. They validate it on 200 simulations in three noise scenarios, and it outperforms aperture extraction when a single pixel carries systematics, while matching it otherwise. The paper ships code (luas) and data, and it uses the method to weight away from a cosmic-ray persistence effect. That is a reusable contribution for JWST time-series work.

The soft spots are real but localized. The abstract's H2O claim is overstated. Section 5 states that the pure-H2O ≥1 bar exclusion at 3.1σ is 'completely dependent on our heat redistribution model,' and with f=2/3 all pure-H2O models up to 1 bar fall within 1σ. The abstract reports pure-H2O ≥1 bar ruled out at >3σ without that caveat, and the grid does not actually extend above 1 bar. The CO2-based constraints are essentially insensitive to that choice, so the central bare-rock conclusion holds; the H2O sentence should be softened or the grid extended. Second, the absolute flux calibration finds BT-Settl models are ~10% too faint in F1500W, and that offset is not propagated into the forward-model comparisons. The authors flag it and argue it would not change the main conclusion, but a reader has to dig to find it. Minor: the jump-detection threshold was tuned on the same data, though the appendix tests show little sensitivity to that choice.

This paper deserves a serious referee. I would send it out. The referee should ask for the abstract to match the body, and for the flux-model offset to be propagated or explicitly bounded. The pixel-GP method is the most citable part and should be scrutinized carefully, because the simulations are the main evidence that it works as claimed.

Referee Report

2 major / 4 minor

Summary. The paper presents 15 μm MIRI/F1500W eclipse photometry of the super-Earth LHS 1140c from three eclipses, develops and validates a new pixel-level Gaussian process fitting method, and compares the measured eclipse depth to bare-rock and atmospheric forward models. The authors report a robust eclipse detection around 250–275 ppm across aperture photometry, the new pixel-fit, and an independent reduction pipeline, with a dayside brightness temperature of 561±44 K. They interpret this as consistent with a low-albedo bare rock and use HELIOS forward models to exclude a broad range of CO2-bearing and other atmospheres. The paper also documents a possible correlation between MIRI detector settling and the previously used filter, and releases the pixel-fitting code as part of the open-source luas package.

Significance. If accepted, the eclipse measurement would be among the most constraining 15 μm eclipse observations of a cool rocky exoplanet, and the pixel-level GP method is a genuinely useful methodological contribution with realistic simulations and an open-source implementation. The cross-checks between independent reductions, multiple systematics models, and varying reduction choices are a clear strength: Tables 4–7 and G.1–G.2 show the bare-rock interpretation is robust to these choices. However, the headline atmospheric exclusion of pure H2O is conditional on a specific heat-redistribution parameterization, and the abstract states this claim more strongly than the analysis supports, which is a load-bearing issue for the paper's central interpretation.

major comments (2)

[Section 5, pure H2O paragraph; Abstract] The abstract's statement that pure H2O atmospheres with surface pressure ≥1 bar are ruled out at >3σ is not supported by the body of the paper. In Section 5 the authors state that the 1 bar pure H2O model is excluded at 3.1σ only when heat redistribution is described by the analytic f-factor of Koll (2022), and that fixing f=2/3 brings all pure H2O models up to 1 bar within 1σ of the data. No pure H2O model with surface pressure above 1 bar is actually computed, so the '≥1 bar' wording overstates the grid tested. The H2O exclusion is a conditional prediction of one redistribution parameterization rather than an independent observational constraint, and the abstract (and the conclusions, which repeat it) should either be reworded to state the conditionality explicitly or drop the H2O claim.
[Sections 4.7, 5, and Table 8] The absolute flux calibration in Section 4.7 shows that the observed F1500W flux exceeds the BT-Settl prediction by 10.3±3.2%, and the text acknowledges that this may shift the forward-model eclipse depths by roughly 10%. However, the exclusion significances quoted in Section 5 and Table 8 are not recomputed under this systematic, even though the stellar model enters both the incident stellar flux and the predicted planet-to-star flux ratio. The stated direction of the effect is conservative for the CO2 constraints, but for the already model-dependent H2O exclusion the quoted 3.1σ does not include this 10% systematic. The authors should either propagate this offset through the model comparisons or explicitly quantify the largest plausible shift in each quoted significance.

minor comments (4)

[Abstract and Table 6] The statement that 'an independent analysis' detects the eclipse at >5σ is not true for all variants in Table 6: the optimal-extraction L+E+GP model gives 235±70 ppm (3.4σ) and L+GP gives 254±53 ppm (4.8σ), although several classic-extraction variants do exceed 5σ. Please specify which reduction and detrending combination is being cited.
[Section 4.5] The text says that 'observations which both used the same previous filter tend to have quite consistent slopes' and then two paragraphs later says 'the two observations which previously used the F560W filter show inconsistent settling.' This apparent contradiction should be resolved, for example by explicitly noting that consistency holds for most filters but not for F560W.
[Section 4.7] The sentence introducing the absolute flux calibration says stellar model inaccuracies could affect the eclipse-spectra models 'in two di fferent ways', but the two ways are not explicitly enumerated. Please spell them out for the reader.
[References] The Morrison et al. (2023) reference appears twice with different journal abbreviations (PASP 135, 075004 and PASA 135, 075004); these should be merged into a single correct citation.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the eclipse depth is measured and independently corroborated; the atmospheric exclusions are conditional forward-model comparisons, with model dependence disclosed rather than hidden.

full rationale

The paper's central measured quantity, the 15 µm eclipse depth, is not derived from the atmospheric models it is compared against. Section 4.3 reports joint-fit depths from aperture photometry (273±43 ppm with GP), the new pixel GP method (253±49 ppm for common+shared independent systematics), and an independent pipeline (e.g. 254±53 ppm for L+GP), all >5σ; Section 3's simulations validate the pixel method's weighting behavior, but the real detection does not depend on those simulations. The atmospheric interpretation in Section 5 uses external forward-model ingredients: HELIOS radiative transfer, the Koll (2022) analytic f-factor, BT-Settl stellar spectra, and fixed Asurf=0.1, none of which are fitted to the measured depth. The pure-H2O exclusion is explicitly caveated as "completely dependent on our heat redistribution model," and the paper discloses that fixing f=2/3 brings all pure-H2O models up to 1 bar within 1σ; this is model-conditionality and presentation, not a constructional circularity. The 10.3±3.2% BT-Settl flux offset in Section 4.7 is acknowledged and not propagated, weakening absolute model comparisons but again not making the measurement an input to itself. Self-citations (Fortune et al. 2024 for the Kronecker GP optimization; August et al. 2025 for survey systematics) are methodological and contextual and do not carry the weight of the physical conclusion. No equation is shown to reduce to its own input, and no fitted parameter is renamed as a prediction.

Assumptions & free parameters 3 free parameters · 7 assumptions · 1 invented entities

The central measurement is an empirical eclipse depth; the interpretation relies on standard stellar/detector models and two ad hoc statistical constructs (separable GP kernel, flux-conserved systematics). The free parameters listed are analysis choices and the fixed surface albedo. No new physical entities are required for the astrophysical conclusion.

free parameters (3)

Surface albedo of atmospheric models = Asurf = 0.1 (fixed)
All HELIOS forward models fix the surface albedo to 0.1 (Section 5). The >3σ atmosphere exclusion significances are conditional on this choice; the paper does not fit or marginalize over it.
Jump detection threshold = 7σ (pipeline)
Selected by minimizing the recovered white-noise amplitude across the three eclipse observations themselves (Section 4.1). This is an a posteriori data-processing choice; the paper shows results are stable across thresholds 4-10σ and alternative reductions (Table G.2).
Settling clip time = 45 minutes for joint fits
The first 45 minutes are clipped in joint fits (Section 4.3.1); individual fits test 30-60 min (Table 5). The preferred eclipse depth changes by a few ppm across these choices, within uncertainties.

assumptions (7)

ad hoc to paper The full covariance matrix of the pixel-time dataset can be written as a sum of two Kronecker products (K = Kp⊗Kt + Σp⊗Σt).
Eq. 5 in Section 2.4. The GP optimization (Rakitsch et al. 2013) is exact only under this separable structure; the paper does not test non-separable noise models.
ad hoc to paper Flux-conserved systematics move flux between neighbouring pixels with amplitude proportional to the geometric mean of the pixel fluxes and are perfectly anti-correlated between neighbours.
Section 2.4.1, Eq. 7. Motivated by pixel autocorrelations (Appendix H) but the functional form is assumed, not independently measured.
domain assumption The Koll (2022) analytic f-factor parameterization correctly maps surface pressure and composition to heat-redistribution efficiency for LHS 1140c.
Section 5. Used to set heat redistribution in all atmospheric forward models; the pure H2O exclusion is completely dependent on it (Section 5).
domain assumption BT-Settl (CIFIST) stellar models provide an accurate input stellar spectrum for the atmospheric forward models.
Section 5. Section 4.7 shows the observed F1500W flux is 10.3±3.2% higher than BT-Settl, but the models are not adjusted; this could shift model eclipse depths by ~10%.
domain assumption A bare rocky planet without a substantial atmosphere has negligible heat redistribution from day to night side (f = 2/3).
Section 1 and Eq. 21, citing Joshi et al. 1997, Selsis et al. 2011, Koll 2022. Central to interpreting the high brightness temperature as evidence of a bare rock.
domain assumption The planet is tidally locked and the measured 15 µm eclipse is dominated by thermal emission from the permanent dayside, with negligible reflected light.
Section 1 (tidal locking, Gomes & Ferraz-Mello 2020) and Section 5 (reflected light (Rp/a)^2 ≈ 4 ppm). Used to convert eclipse depth to dayside brightness temperature.
ad hoc to paper The noise processes are described by the assumed exponential kernel in time and the pixel kernels in Eq. 16, with all time-correlated processes sharing one length scale lt.
Section 2.4.6, Eq. 16. Required for the Kronecker structure; the autocorrelation check (Appendix H) supports but does not prove the exponential form.

invented entities (1)

Flux-conserved systematics (FCS)
purpose: A latent correlated-noise process that moves flux between neighbouring pixels while conserving the total aperture sum, used to model PSF-shape changes or charge migration.
Introduced in Section 2.4.1 and supported only by indirect pixel autocorrelations and simulations that assume the same model. No direct measurement of such a process is presented.

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Cite this review

Pith. "Pith review of Hot Rocks Survey III: A deep eclipse for LHS 1140c and a new Gaussian process method to account for correlated noise in individual pixels." pith.science (2026). https://pith.science/paper/KDGWBARV

@misc{pith2026250522186,
  author       = {Pith},
  title        = {Pith review of: Hot Rocks Survey III: A deep eclipse for LHS 1140c and a new Gaussian process method to account for correlated noise in individual pixels},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/KDGWBARV}},
  note         = {Machine review of arXiv:2505.22186}
}

abstract

Time-series photometry at mid-infrared wavelengths is becoming a common technique to search for atmospheres around rocky exoplanets. This method constrains the brightness temperature of the planet to determine whether heat redistribution is taking place - indicative of an atmosphere - or whether the heat is reradiated from a low albedo bare rock. By observing at 15$\mu$m we are also highly sensitive to CO$_2$ absorption. We observed three eclipses of the rocky super-Earth LHS 1140c using MIRI/Imaging with the F1500W filter. We found significant variation in the initial settling ramp for these observations and identify a potential trend between detector settling and the previous filter used by MIRI. We analysed our data using aperture photometry but also developed a novel approach which joint-fits pixel light curves directly using a shared eclipse model and a flexible multi-dimensional Gaussian process which models changes in the PSF over time. We demonstrate using simulated data that our method has the ability to weight away from particular pixels which show increased systematics, allowing for the recovery of eclipse depths in a more robust and precise way. Both methods and an independent analysis detect the eclipse at $>5\sigma$ and are highly consistent with a low albedo bare rock. We recover a dayside brightness temperature of $T_\mathrm{day} = 561\pm44$ K, close to the theoretical maximum of $T_\text{day; max} = 537\pm9$ K. We rule out a wide range of atmospheric forward models to $>3\sigma$ including pure CO$_2$ atmospheres with surface pressure $\ge10$ mbar and pure H$_2$O atmospheres with surface pressure $\ge1$ bar. Our strict constraints on potential atmospheric composition, in combination with future observations of the exciting outer planet LHS 1140b, could provide a powerful benchmark to understand atmospheric escape around M dwarfs.

Figures

Figures reproduced from arXiv: 2505.22186 by the authors.

**Figure 1.** Pixel light curves centred on the PSF for the second eclipse, excluding the first 45 minutes dominated by settling and binned for clarity. A sharp persistence effect from a cosmic ray is highlighted with orange dashed boxes (see Appendix A for details). Pixels highlighted with green boundaries were fit using the pixel-fitting method except where specified we excluded the pixels containing the highlighted flux jum… view at source ↗

**Figure 2.** Three different random draws of time-correlated systematics for a grid of 3x3 pixels. Left grid shows flux-conserved systematics whose sum is zero after aperture extraction. The second grid shows systematics independent to a particular pixel. The third grid shows common systematics with the same shape and with an amplitude proportional to the flux on each pixel. While the amplitude of common systematics may appear s… view at source ↗

**Figure 3.** Pixel light curves for the first simulation in the flux-conserved systematics (FCS) and independent pixel systematics (IPS) scenarios. The only difference is the pixel light curve in orange which had independent systematics added to it. The pixels included within the pixel-fits are highlighted with green boundaries [PITH_FULL_IMAGE:figures/full_fig_p008_3.png] view at source ↗

Figures from the paper (13 more)

**Figure 4.** Figure 4: Aperture extracted light curves from simulated datasets shown in [PITH_FULL_IMAGE:figures/full_fig_p008_4.png]

**Figure 5.** Figure 5: Constraints on the Independent Pixel Systematics (IPS) height scale for each pixel for the first simulation in the FCS and IPS scenarios (shown in [PITH_FULL_IMAGE:figures/full_fig_p010_5.png]

**Figure 6.** Figure 6: Eclipse depth constraint for all simulations in the IPS scenario, which each had a single pixel contaminated with time-correlated systematics. The left plot shows the results from using aperture extraction with a GP. The right plot shows pixel-fitting accounting for bo…

**Figure 7.** Figure 7: Results from Tables 1, 2, and 3 comparing the RMSE, mean uncertainty in eclipse depth, and χ 2 r of recovered eclipse depths for various methods. Aperture extraction with a GP is shown to perform similarly for the IPS and CS scenarios as the aperture extracted light c…

**Figure 8.** Figure 8: Three aperture extracted eclipse light curves from the primary reduction. Observations are binned into four minute bins for clarity. Expected eclipse location for a circular orbit is shaded in gray. There are differences in initial detector settling in the first half …

**Figure 9.** Figure 9: Median frame of the first observation centred on the target PSF. Aperture extraction was performed with a 5px circular aperture in blue, centred for each integration. Pixels used for the pixel-fitting are enclosed in orange. 4.2. Secondary data reduction We performed …

**Figure 10.** Figure 10: Difference in GP predictive mean from pixel-fitting the second eclipse due to fitting for independent pixel systematics. Pixels affected by the strong cosmic ray persistence effect from [PITH_FULL_IMAGE:figures/full_fig_p014_10.png]

**Figure 11.** Figure 11: JWST mnemonics which track telescope orientation (sa_zattest) overlaid with the mnemonic tracking current MIRI filter position. Left y-axis shows difference in telescope pointing parameters from our observations. Filter wheel position is plotted as black dashed line a…

**Figure 12.** Figure 12: Possible trend in detector settling based on the previous filter used by MIRI. The mean and uncertainty in the slope of the first 30 minutes of the aperture extracted light curve is plotted for various Hot Rocks observations. Left plot shows previous imaging filters b…

**Figure 13.** Figure 13: Central pixel light curves for the first 30 minutes of each LHS 1140c eclipse. Each plot shows the change in flux relative to the last ten integrations of the first 30 minutes. The legend specifies which previous filter was in place for each eclipse. Note the strong d…

**Figure 14.** Figure 14: Marginal posterior distributions of various pixel-fitting systematics parameters for each eclipse. Values from joint-fit of three eclipses with independent systematics parameters for each eclipse. Common systematics and correlated background scatter were not strongly …

**Figure 15.** Figure 15: Atmospheric forward models compared to eclipse depth measurements using various analyses. Spectra are compared to eclipse depths recovered using aperture extraction with a GP, pixel-fitting or a secondary analysis fit using optimal extraction without a GP. Left: Emiss…

**Figure 16.** Figure 16 [PITH_FULL_IMAGE:figures/full_fig_p019_16.png]

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Forward citations

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Reference graph

Works this paper leans on

119 extracted references · 51 canonical work pages · cited by 4 Pith papers

[1]

, " * write output.state after.block = add.period write newline

ENTRY address archiveprefix author booktitle chapter edition editor howpublished institution eprint journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 ...
[2]

write newline

" write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in " " * FUNCTION format....
[3]

L., et al

Agol , E., Dorn , C., Grimm , S. L., et al. 2021, , 2, 1

2021
[4]

& Foreman-Mackey , D

Aigrain , S. & Foreman-Mackey , D. 2023, , 61, 329

2023
[5]

K., Gao , P., Adams Redai , J., et al

Alam , M. K., Gao , P., Adams Redai , J., et al. 2025, , 169, 15

2025
[6]

2011, in Astronomical Society of the Pacific Conference Series, Vol

Allard , F., Homeier , D., & Freytag , B. 2011, in Astronomical Society of the Pacific Conference Series, Vol. 448, 16th Cambridge Workshop on Cool Stars, Stellar Systems, and the Sun, ed. C. Johns-Krull , M. K. Browning , & A. A. West , 91

2011
[7]

2018, in Handbook of Exoplanets, ed

Alonso , R. 2018, in Handbook of Exoplanets, ed. H. J. Deeg & J. A. Belmonte , 40

2018
[8]

M., Lim , P

Astropy Collaboration , Price-Whelan , A. M., Lim , P. L., et al. 2022, , 935, 167

2022

Show all 119 references

[9]

C., Buchhave , L

August , P. C., Buchhave , L. A., Diamond-Lowe , H., et al. 2025, , 695, A171

2025
[10]

K., Gressier, A., et al

Banerjee, A., Barstow, J. K., Gressier, A., et al. 2024, , 975, L11

2024
[11]

J., Tennyson , J., Harris , G

Barber , R. J., Tennyson , J., Harris , G. J., & Tolchenov , R. N. 2006, , 368, 1087

2006
[12]

J., Crouzet , N., Cubillos , P

Bell , T. J., Crouzet , N., Cubillos , P. E., et al. 2024, Nature Astronomy, 8, 879

2024
[13]

A., et al

Bello-Arufe, A., Damiano, M., Bennett, K. A., et al. 2025, , 980, L26

2025
[14]

2018, JAX : composable transformations of P ython+ N um P y programs

Bradbury, J., Frostig, R., Hawkins, P., et al. 2018, JAX : composable transformations of P ython+ N um P y programs

2018
[15]

2024, astropy/photutils: 1.13.0

Bradley, L., Sipőcz, B., Robitaille, T., et al. 2024, astropy/photutils: 1.13.0

2024
[16]

2024 a , , 960, L3

Cadieux , C., Plotnykov , M., Doyon , R., et al. 2024 a , , 960, L3

2024
[17]

J., et al

Cadieux , C., Doyon , R., MacDonald , R. J., et al. 2024 b , , 970, L2

2024
[18]

E., Megeath , S

Charbonneau , D., Allen , L. E., Megeath , S. T., et al. 2005, , 626, 523

2005
[19]

Chatterjee, R. D. & Pierrehumbert, R. T. 2024, , submitted, arXiv:2412.05188

2024
[20]

Cox , A. N. 2000, Allen's astrophysical quantities

2000
[21]

2024, , 968, L22

Damiano , M., Bello-Arufe , A., Yang , J., & Hu , R. 2024, , 968, L22

2024
[22]

2015, , 805, 132

Deming , D., Knutson , H., Kammer , J., et al. 2015, , 805, 132

2015
[23]

2016, , 532, 207

Demory , B.-O., Gillon , M., de Wit , J., et al. 2016, , 532, 207

2016
[24]

G., Shivaei , I., et al

Dicken , D., Mar \' n , M. G., Shivaei , I., et al. 2024, , 689, A5

2024
[25]

A., Irwin , J

Dittmann , J. A., Irwin , J. M., Charbonneau , D., et al. 2017, , 544, 333

2017
[26]

2024, in EGU General Assembly Conference Abstracts, EGU General Assembly Conference Abstracts, 20183

Ducrot , E., Lagage , P.-O., & Min , M. 2024, in EGU General Assembly Conference Abstracts, EGU General Assembly Conference Abstracts, 20183

2024
[27]

S., & Agol, E

Eastman, J., Gaudi, B. S., & Agol, E. 2013, , 125, 83

2013
[28]

P., Sprague , A

Emery , J. P., Sprague , A. L., Witteborn , F. C., et al. 1998, , 136, 104

1998
[29]

2022, TransitSpectroscopy

Espinoza , N. 2022, TransitSpectroscopy

2022
[30]

2019, , 490, 2262–2283

Espinoza, N., Kossakowski, D., & Brahm, R. 2019, , 490, 2262–2283

2019
[31]

M., Aigrain, S., Gibson, N., et al

Evans, T. M., Aigrain, S., Gibson, N., et al. 2015, , 451, 680

2015
[32]

2016, The Journal of Open Source Software, 1, 24

Foreman-Mackey, D. 2016, The Journal of Open Source Software, 1, 24

2016
[33]

2017, , 154, 220

Foreman-Mackey , D., Agol , E., Ambikasaran , S., & Angus , R. 2017, , 154, 220

2017
[34]

2021, exoplanet: Gradient-based probabilistic inference for exoplanet data & other astronomical time series

Foreman-Mackey , D., Luger , R., Agol , E., et al. 2021, exoplanet: Gradient-based probabilistic inference for exoplanet data & other astronomical time series

2021
[35]

P., Foreman-Mackey , D., et al

Fortune , M., Gibson , N. P., Foreman-Mackey , D., et al. 2024, , 686, A89

2024
[36]

Gaia Collaboration , Brown , A. G. A., Vallenari , A., et al. 2021, , 649, A1

2021
[37]

2004, , 611, 1005

Gehrels , N., Chincarini , G., Giommi , P., et al. 2004, , 611, 1005

2004
[38]

& Rubin , D

Gelman , A. & Rubin , D. B. 1992, Statistical Science, 7, 457

1992
[39]

Gibson , N. P. 2014, , 445, 3401

2014
[40]

P., Aigrain , S., Barstow , J

Gibson , N. P., Aigrain , S., Barstow , J. K., et al. 2013, , 428, 3680

2013
[41]

P., Aigrain , S., Roberts , S., et al

Gibson , N. P., Aigrain , S., Roberts , S., et al. 2012, , 419, 2683

2012
[42]

H., Bauwens , E., et al

Glasse , A., Rieke , G. H., Bauwens , E., et al. 2015, , 127, 686

2015
[43]

Gomes , G. O. & Ferraz-Mello , S. 2020, , 494, 5082

2020
[44]

E., Rothman , L

Gordon , I. E., Rothman , L. S., Hargreaves , R. J., et al. 2022, , 277, 107949

2022
[45]

D., Sloan , G

Gordon , K. D., Sloan , G. C., Garcia Marin , M., et al. 2025, , 169, 6

2025
[46]

P., Bell , T

Greene , T. P., Bell , T. J., Ducrot , E., et al. 2023, , 618, 39

2023
[47]

H., et al

Gressier , A., Espinoza , N., Allen , N. H., et al. 2024, , 975, L10

2024
[48]

Grimm , S. L. & Heng , K. 2015, , 808, 182

2015
[49]

M., Lichtenberg , T., et al

Hammond , M., Guimond , C. M., Lichtenberg , T., et al. 2025, , 978, L40

2025
[50]

Hansen , B. M. S. 2008, , 179, 484

2008
[51]

1993, Theory of Reflectance and Emittance Spectroscopy, Topics in Remote Sensing (Cambridge University Press)

Hapke, B. 1993, Theory of Reflectance and Emittance Spectroscopy, Topics in Remote Sensing (Cambridge University Press)

1993
[52]

R., Millman, K

Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357

2020
[53]

2024, exoplanet-dev/jaxoplanet: Astronomical time series analysis with JAX

Hattori, S., Garcia, L., Murray, C., et al. 2024, exoplanet-dev/jaxoplanet: Astronomical time series analysis with JAX

2024
[54]

M., & Kitzmann , D

Heng , K., Morris , B. M., & Kitzmann , D. 2021, Nature Astronomy, 5, 1001

2021
[55]

Hoffman, M. D. & Gelman, A. 2014, Journal of Machine Learning Research, 15, 1593–1623

2014
[56]

1986, , 98, 609

Horne , K. 1986, , 98, 609

1986
[57]

2024, , 630, 609

Hu , R., Bello-Arufe , A., Zhang , M., et al. 2024, , 630, 609

2024
[58]

Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90

2007
[59]

& Kempton , E

Ih , J. & Kempton , E. M. R. 2021, , 162, 237

2021
[60]

Ih , J., Kempton , E. M. R., Whittaker , E. A., & Lessard , M. 2023, , 952, L4

2023
[61]

G., Krick , J

Ingalls , J. G., Krick , J. E., Carey , S. J., et al. 2012, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 8442, Space Telescopes and Instrumentation 2012: Optical, Infrared, and Millimeter Wave, ed. M. C. Clampin , G. G. Fazio , H. A. Mac...

2012
[62]

S., Kjærulff, U., & Kong, A

Jensen, C. S., Kjærulff, U., & Kong, A. 1995, International Journal of Human-Computer Studies, 42, 647

1995
[63]

1997, Icarus, 129, 450

Joshi, M., Haberle, R., & Reynolds, R. 1997, Icarus, 129, 450

1997
[64]

Kite , E. S. & Barnett , M. N. 2020, Proceedings of the National Academy of Science, 117, 18264

2020
[65]

A., Charbonneau , D., Allen , L

Knutson , H. A., Charbonneau , D., Allen , L. E., Burrows , A., & Megeath , S. T. 2008, , 673, 526

2008
[66]

Koll , D. D. B. 2022, , 924, 134

2022
[67]

Koll , D. D. B., Malik , M., Mansfield , M., et al. 2019, , 886, 140

2019
[68]

Kreidberg , L., Koll , D. D. B., Morley , C., et al. 2019, , 573, 87

2019
[69]

Krissansen-Totton , J., Wogan , N., Thompson , M., & Fortney , J. J. 2024, Nature Communications, 15, 8374

2024
[70]

2019, Journal of Open Source Software, 4, 1143

Kumar, R., Carroll, C., Hartikainen, A., & Martin, O. 2019, Journal of Open Source Software, 4, 1143

2019
[71]

& Barnes , R

Luger , R. & Barnes , R. 2015, Astrobiology, 15, 119

2015
[72]

S., Eastman , J

Mahajan , A. S., Eastman , J. D., & Kirk , J. 2024, , 963, L37

2024
[73]

M., et al

Malik , M., Grosheintz , L., Mendon c a , J. M., et al. 2017, , 153, 56

2017
[74]

Malik , M., Kempton , E. M. R., Koll , D. D. B., et al. 2019 a , , 886, 142

2019
[75]

M., et al

Malik , M., Kitzmann , D., Mendon c a , J. M., et al. 2019 b , , 157, 170

2019
[76]

& Agol , E

Mandel , K. & Agol , E. 2002, , 580, L171

2002
[77]

S., Hu , R., et al

Mansfield , M., Kite , E. S., Hu , R., et al. 2019, , 886, 141

2019
[78]

A., Demory , B

Meier Vald \'e s , E. A., Demory , B. O., Diamond-Lowe , H., et al. 2025, , accepted, arXiv:2503.19772

2025 arXiv
[79]

A., Astudillo-Defru , N., et al

Ment , K., Dittmann , J. A., Astudillo-Defru , N., et al. 2019, , 157, 32

2019
[80]

C., Ninkov , Z., & Forrest , W

Moore , A. C., Ninkov , Z., & Forrest , W. J. 2006, Optical Engineering, 45, 076402

2006
[81]

2015, , 808, 56

Morello , G. 2015, , 808, 56

2015
[82]

P., & Tinetti , G

Morello , G., Waldmann , I. P., & Tinetti , G. 2016, , 820, 86

2016
[83]

P., Tinetti , G., et al

Morello , G., Waldmann , I. P., Tinetti , G., et al. 2014, , 786, 22

2014
[84]

E., Dicken , D., Argyriou , I., et al

Morrison , J. E., Dicken , D., Argyriou , I., et al. 2023, , 135, 075004

2023
[85]

E., Dicken, D., Argyriou, I., et al

Morrison, J. E., Dicken, D., Argyriou, I., et al. 2023, , 135, 075004

2023
[86]

Neal, R. M. 2003, The Annals of Statistics, 31, 705

2003
[87]

2020, pandas-dev/pandas: Pandas

pandas development team, T. 2020, pandas-dev/pandas: Pandas

2020
[88]

S., et al

Park Coy , B., Ih , J., Kite , E. S., et al. 2024, arXiv e-prints, arXiv:2412.06573

2024 arXiv
[89]

K., Charbonneau , D., & Vanderburg , A

Pass , E. K., Charbonneau , D., & Vanderburg , A. 2025, , accepted, arXiv:2504.01182

2025 arXiv
[90]

A., Brandeker , A., Kitzmann , D., et al

Patel , J. A., Brandeker , A., Kitzmann , D., et al. 2024, , 690, A159

2024
[91]

& Granger, B

P\'erez, F. & Granger, B. E. 2007, Computing in Science and Engineering, 9, 21

2007
[92]

D., Sivaramakrishnan , A., Lajoie , C.-P., et al

Perrin , M. D., Sivaramakrishnan , A., Lajoie , C.-P., et al. 2014, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9143, Space Telescopes and Instrumentation 2014: Optical, Infrared, and Millimeter Wave, ed. J. M. Oschmann , Jr., M. Clampi...

2014
[93]

V., Apai , D., & Giampapa , M

Rackham , B. V., Apai , D., & Giampapa , M. S. 2018, , 853, 122

2018
[94]

2013, in Advances in Neural Information Processing Systems, Vol

Rakitsch, B., Lippert, C., Borgwardt, K., & Stegle, O. 2013, in Advances in Neural Information Processing Systems, Vol. 26

2013
[95]

2024, arXiv e-prints, arXiv:2404.02932

Redfield , S., Batalha , N., Benneke , B., et al. 2024, arXiv e-prints, arXiv:2404.02932

2024 arXiv
[96]

2023, , 135, 048001

Rigby , J., Perrin , M., McElwain , M., et al. 2023, , 135, 048001

2023
[97]

S., Gordon , I

Rothman , L. S., Gordon , I. E., Barber , R. J., et al. 2010, , 111, 2139

2010
[98]

V., & Fonnesbeck, C

Salvatier, J., Wiecki, T. V., & Fonnesbeck, C. 2016, PeerJ Computer Science, 2, e55

2016
[99]

Z., Feinstein , A

Seligman , D. Z., Feinstein , A. D., Lai , D., et al. 2024, , 961, 22

2024
[100]

D., & Forget , F

Selsis , F., Wordsworth , R. D., & Forget , F. 2011, , 532, A1

2011
[101]

L., Ballard , S., & Johnson , J

Shields , A. L., Ballard , S., & Johnson , J. A. 2016, , 663, 1

2016
[102]

& Ubachs , W

Sneep , M. & Ubachs , W. 2005, , 92, 293

2005
[103]

2019, , 627, A144

Spinelli , R., Borsa , F., Ghirlanda , G., et al. 2019, , 627, A144

2019
[104]

B., Harrington , J., Fortney , J

Stevenson , K. B., Harrington , J., Fortney , J. J., et al. 2012, , 754, 136

2012
[105]

2014, , 147, 171–177

Thalman, R., Zarzana, K., Tolbert, M., & Volkamer, R. 2014, , 147, 171–177

2014
[106]

& Heng , K

Tian , M. & Heng , K. 2024, , 963, 157

2024
[107]

P., et al

Tulasi Ram , S., Veenadhari , B., Dimri , A. P., et al. 2024, Space Weather, 22, 2024SW004126

2024
[108]

S., Tennyson, J., Yurchenko, S

Underwood, D. S., Tennyson, J., Yurchenko, S. N., et al. 2016, , 459, 3890

2016
[109]

E., et al

Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261

2020
[110]

Waldmann , I. P. 2012, , 747, 12

2012
[111]

P., Tinetti , G., Deroo , P., et al

Waldmann , I. P., Tinetti , G., Deroo , P., et al. 2013, , 766, 7

2013
[112]

W., Foreman-Mackey , D., & Sch \"o lkopf , B

Wang , D., Hogg , D. W., Foreman-Mackey , D., & Sch \"o lkopf , B. 2016, , 128, 094503

2016
[113]

2024, , 975, L22

Weiner Mansfield , M., Xue , Q., Zhang , M., et al. 2024, , 975, L22

2024
[114]

A., Malik , M., Ih , J., et al

Whittaker , E. A., Malik , M., Ih , J., et al. 2022, , 164, 258

2022
[115]

2023, , 674, A69

Wohlfarth , K., W \"o hler , C., Hiesinger , H., & Helbert , J. 2023, , 674, A69

2023
[116]

S., Wright, D., Goodson, G

Wright, G. S., Wright, D., Goodson, G. B., et al. 2015, , 127, 595

2015
[117]

Zahnle , K. J. & Catling , D. C. 2017, , 843, 122

2017
[118]

2023 a , The search for regolith on the airless exoplanet LHS 3844 b , JWST Proposal

Zieba , S., Hu , R., Kreidberg , L., et al. 2023 a , The search for regolith on the airless exoplanet LHS 3844 b , JWST Proposal. Cycle 2, ID. \#4008

2023
[119]

2023 b , , 620, 746

Zieba , S., Kreidberg , L., Ducrot , E., et al. 2023 b , , 620, 746

2023

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.

[1] [1]

, " * write output.state after.block = add.period write newline

ENTRY address archiveprefix author booktitle chapter edition editor howpublished institution eprint journal key month note number organization pages publisher school series title type volume year label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts #0 'before.all := #1 ...

[2] [2]

write newline

" write newline "" before.all 'output.state := FUNCTION n.dashify 't := "" t empty not t #1 #1 substring "-" = t #1 #2 substring "--" = not "--" * t #2 global.max substring 't := t #1 #1 substring "-" = "-" * t #2 global.max substring 't := while if t #1 #1 substring * t #2 global.max substring 't := if while FUNCTION word.in bbl.in " " * FUNCTION format....

[3] [3]

L., et al

Agol , E., Dorn , C., Grimm , S. L., et al. 2021, , 2, 1

2021

[4] [4]

& Foreman-Mackey , D

Aigrain , S. & Foreman-Mackey , D. 2023, , 61, 329

2023

[5] [5]

K., Gao , P., Adams Redai , J., et al

Alam , M. K., Gao , P., Adams Redai , J., et al. 2025, , 169, 15

2025

[6] [6]

2011, in Astronomical Society of the Pacific Conference Series, Vol

Allard , F., Homeier , D., & Freytag , B. 2011, in Astronomical Society of the Pacific Conference Series, Vol. 448, 16th Cambridge Workshop on Cool Stars, Stellar Systems, and the Sun, ed. C. Johns-Krull , M. K. Browning , & A. A. West , 91

2011

[7] [7]

2018, in Handbook of Exoplanets, ed

Alonso , R. 2018, in Handbook of Exoplanets, ed. H. J. Deeg & J. A. Belmonte , 40

2018

[8] [8]

M., Lim , P

Astropy Collaboration , Price-Whelan , A. M., Lim , P. L., et al. 2022, , 935, 167

2022