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arxiv: 2606.19056 · v1 · pith:PXNFHSLC · submitted 2026-06-17 · astro-ph.EP

Three dimensional temporal evolution of photochemical haze in exoplanet atmospheres I. Description and test application to HD 189733b

Elspeth K.H. Lee , Maria E. Steinrueck , Kazumasa Ohno , Diana Powell , Xi Zhang This is my paper

Reviewed by Pith2026-06-26 19:17 UTCgrok-4.3pith:PXNFHSLCopen to challenge →

classification astro-ph.EP
keywords photochemical hazeexoplanet atmospheresHD 189733bmicrophysical modelgeneral circulation modelparticle growthradiative feedbacktransmission spectra
0
0 comments X

The pith

Haze particles in HD 189733b stay below 30 nm and accumulate at east and west limbs following vertical winds.

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

The paper develops a flexible microphysical model for photochemical haze formation and time-dependent evolution that can be coupled to 3D general circulation models. It introduces an activation timescale to approximate delayed particle formation from photochemistry and tests the scheme on an idealized HD 189733b case. Simulations show that particles remain small, their locations track atmospheric vertical flows including equatorial convergence at 0.01 bar, and the resulting distribution produces stronger opacity at the limbs. Haze radiative effects can reshape upper-atmosphere temperature-pressure profiles depending on production rate, with longer timescales strengthening transmission-spectrum signals while nightside formation boosts dayside emission flux.

Core claim

The paper claims that for the chosen haze formation efficiency, particles do not grow beyond ~30 nm. The haze spatial distribution follows the vertical velocity structure of the atmosphere, with equatorial convergence patterns of material deeper in the atmosphere at ~10^{-2} bar. The resulting global distribution leads to enhanced haze opacity at the east and west limbs. Radiative feedback from haze opacity can strongly affect the temperature-pressure structures in the upper atmosphere depending on the production rate. Longer haze-production timescales give rise to stronger haze opacity effects on the observed transmission spectra compared to short-timescale dayside formation, but the strong

What carries the argument

The mini-haze microphysical scheme, which uses a simple activation timescale mechanism to emulate delayed formation of solid particles and is coupled to the Exo-FMS GCM to track 3D particle growth, transport, and radiative feedback.

If this is right

  • Particles remain no larger than ~30 nm under the chosen formation efficiency.
  • Haze follows vertical velocity structure with equatorial convergence at ~10^{-2} bar.
  • Global distribution produces enhanced opacity specifically at the east and west limbs.
  • Haze radiative feedback modifies upper-atmosphere temperature-pressure profiles in a production-rate-dependent way.
  • Longer production timescales strengthen transmission-spectrum opacity effects while nightside formation increases dayside emission flux.

Where Pith is reading between the lines

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

  • The time-dependent 3D approach could be extended to model orbital-phase variability in haze properties on other hot Jupiters.
  • Similar wind-driven convergence patterns may appear in sub-Neptune atmospheres when the same scheme is applied there.
  • Future versions that add chemical feedback loops would allow self-consistent tests of how haze production alters the underlying chemistry.
  • The limb-enhanced opacity could be tested against phase-resolved or eclipse-mapping data even if full spectra are not yet available.

Load-bearing premise

The simple activation timescale mechanism accurately emulates a delayed formation of solid haze particles from photochemical processes without requiring a full chemical network.

What would settle it

Direct measurements showing haze particles larger than 30 nm or transmission spectra of HD 189733b lacking enhanced east-west limb opacity would contradict the reported particle sizes and spatial distribution.

Figures

Figures reproduced from arXiv: 2606.19056 by Diana Powell, Elspeth K.H. Lee, Kazumasa Ohno, Maria E. Steinrueck, Xi Zhang.

Figure 1
Figure 1. Figure 1: Temperature-pressure (T-p) profiles (top row) at the equatorial region as a function of longitude (colourbar) for the short (left) and long (right) timescale formation simulation. The dashed line shows a polar T-p profile. Zonal mean zonal velocity (bottom row) of the HD 189733b simulation for the short (left) and long (right) timescale formation simulation. namical evolution of the haze, after which we in… view at source ↗
Figure 2
Figure 2. Figure 2: 2D latitude-longitude map of the solid haze particle mass mixing ratio formation rate, P˙ h [g g−1 s −1 ≡ s −1 ], at the 10−5 bar pressure level for the short formation timescale (left) and long formation timescale (right) GCM simulation. sor material to this pressure layer before it is converted to solid haze. 3.5. Short formation timescale In [PITH_FULL_IMAGE:figures/full_fig_p009_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Short formation timescale vertical profiles of the zeroth moment volume mixing ratio, q0 [cm3 cm−3 ] (top left), first moment mass mixing ratio, q1 [g g−1 ] (top right), haze particle number density, nh [cm−3 ] (bottom left) and haze particle radius, rh [nm] (bottom right). Coloured lines denote the longitude (colour bar) at the equatorial region, while the black dashed line denotes a polar region. In addi… view at source ↗
Figure 4
Figure 4. Figure 4: Same as [PITH_FULL_IMAGE:figures/full_fig_p011_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Transmission spectra (left), and dayside emission spectra (right) of our GCM simulations, for the short (blue solid line), and long (orange solid line) haze formation timescales. Green dotted lines show the spectrum before the radiative-feedback from haze was introduced. We include the available transmission spectra for HD 189733b from Cubillos et al. (2023), Sing et al. (2016), and Fu et al. (2024), as we… view at source ↗
Figure 6
Figure 6. Figure 6: Dayside averaged 3D contribution functions of the GCM simulations for short (left) and long (right) haze formation timescale simulations. The regions contributing to the emission spectra are similar between each simulation. Lavvas & Koskinen (2017) applied a haze evolution model originally designed for Titan studies (Lavvas et al. 2010) to the atmosphere of HD 209458b and HD 189733b. This uses a 1D bin evo… view at source ↗
read the original abstract

The formation and global spatial distribution of photochemically produced haze particles remain a key process in exoplanet atmospheres for understanding their observed properties. We aim to develop a flexible haze particle formation and evolution model suitable for time-dependent exoplanet atmosphere simulations. Inspired by recent 2D photochemical modelling efforts, we include a simple activation timescale mechanism to emulate a delayed formation of solid haze particles. We couple our new microphysical haze formation scheme, mini-haze, to the Exo-FMS general circulation model (GCM) and simulate an idealised HD 189733b case study to examine the 3D spatial distribution and sizes of haze particles. Our results suggest that for our chosen haze formation efficiency, particles do not grow beyond $\sim$30 nm, in line with previous detailed 1D modelling. We find the haze spatial distribution follows the vertical velocity structure of the atmosphere, with equatorial convergence patterns of material deeper in the atmosphere at $\sim$10$^{-2}$ bar. The resulting global distribution leads to enhanced haze opacity at the east and west limbs of the atmosphere. In our test cases, radiative feedback from haze opacity can strongly affect the temperature-pressure structures in the upper atmosphere depending on the production rate. Our synthetic spectra results suggest that longer haze-production timescales give rise to stronger haze opacity effects on the observed transmission spectra compared to short-timescale dayside formation, but the stronger thermal feedback from nightside formation leads to an overall larger dayside emission flux. Our current simulations represent a step towards investigating self-consistent haze formation and evolution with chemical feedback effects in 3D, and can be readily applied to other objects of interest, such as sub-Neptune atmospheres.

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 / 1 minor

Summary. The paper introduces the mini-haze microphysical scheme, which employs a simple activation timescale parameterization (inspired by 2D photochemical models) to emulate delayed solid haze particle formation without a full chemical network. This is coupled to the Exo-FMS GCM for time-dependent 3D simulations of HD 189733b. Key results include: particles remaining below ~30 nm for the chosen formation efficiency; haze spatial distribution tracking vertical velocities with equatorial convergence at ~10^{-2} bar; enhanced limb opacities; and production-rate-dependent radiative feedback on upper-atmosphere T-P profiles. Synthetic spectra indicate that longer haze-production timescales strengthen transmission effects while nightside formation yields larger dayside emission fluxes due to thermal feedback.

Significance. If the activation timescale faithfully captures photochemical delays under 3D advection, the work supplies a computationally tractable route to self-consistent haze-radiation-dynamics coupling in GCMs. It extends prior 1D microphysics and 2D chemistry results to three dimensions and supplies a reusable framework for sub-Neptune and other atmospheres. The explicit test application to HD 189733b and the reported east-west limb asymmetry constitute concrete, falsifiable predictions.

major comments (1)
  1. [Abstract / model description] Abstract and model description: the headline claims on particle sizes (≤30 nm), equatorial convergence at ~10^{-2} bar, limb-enhanced opacity, and T-P feedback all rest on the activation timescale mechanism accurately standing in for full photochemical production rates once vertical and horizontal transport are active. No quantitative comparison to the 2D photochemical benchmarks that motivated the parameterization, nor sensitivity tests under 3D advection, are reported; if the effective formation delay differs materially, the reported spatial distribution and opacity maps would shift.
minor comments (1)
  1. [Abstract] The abstract states results for 'our chosen haze formation efficiency' and 'production rate' but does not list the numerical values or ranges explored; these should be stated explicitly in the methods or a table for reproducibility.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for their constructive review and recommendation of major revision. We address the major comment below and commit to the necessary changes.

read point-by-point responses

  1. Referee: [Abstract / model description] Abstract and model description: the headline claims on particle sizes (≤30 nm), equatorial convergence at ~10^{-2} bar, limb-enhanced opacity, and T-P feedback all rest on the activation timescale mechanism accurately standing in for full photochemical production rates once vertical and horizontal transport are active. No quantitative comparison to the 2D photochemical benchmarks that motivated the parameterization, nor sensitivity tests under 3D advection, are reported; if the effective formation delay differs materially, the reported spatial distribution and opacity maps would shift.

    Authors: We agree that the submitted manuscript lacks a direct quantitative comparison of the activation timescale parameterization against the 2D photochemical benchmarks that motivated it, as well as explicit sensitivity tests under 3D advection. The timescale was chosen to reproduce the characteristic formation delays reported in those 2D studies while remaining computationally tractable for GCM coupling; our reported particle sizes are consistent with prior 1D microphysical results. However, we acknowledge that without the requested benchmarks and tests, the robustness of the spatial distribution, limb opacity enhancements, and T-P feedback cannot be fully demonstrated. In the revised manuscript we will add (i) a direct comparison of effective production rates and delays between the mini-haze scheme and the original 2D models, and (ii) a set of sensitivity experiments varying the activation timescale under the 3D flow to quantify any shifts in haze distribution and opacity maps. These additions will directly address the concern raised. revision: yes

Circularity Check

0 steps flagged

No significant circularity in derivation chain

full rationale

The paper introduces a new mini-haze microphysical scheme that adopts an activation timescale parameterization (inspired by prior 2D photochemical work) as a modeling simplification to enable 3D GCM coupling, then reports forward simulation outputs for particle sizes, spatial distributions, limb opacities, and radiative feedback on HD 189733b. These results are generated by integrating the chosen parameters through the time-dependent dynamical model rather than being forced by definition, self-citation chains, or renaming of inputs. No load-bearing steps reduce to fitted quantities called predictions or to self-referential uniqueness theorems; the derivation remains self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

2 free parameters · 1 axioms · 0 invented entities

The central claim rests on the new microphysical scheme and its coupling, with the activation timescale as an ad hoc addition for temporal effects. Free parameters are the haze formation efficiency and production rates selected for the test cases. No new physical entities are postulated; relies on standard GCM and microphysics components from prior literature.

free parameters (2)
  • haze formation efficiency
    Chosen value for the HD 189733b simulation that sets the ~30 nm particle size limit.
  • haze production rate
    Varied across test cases to examine effects on opacity, feedback, and spectra.
axioms (1)
  • ad hoc to paper Simple activation timescale mechanism emulates delayed formation of solid haze particles
    Included to model time-dependent evolution, inspired by 2D photochemical modelling efforts.

pith-pipeline@v0.9.1-grok · 5865 in / 1478 out tokens · 36377 ms · 2026-06-26T19:17:29.235681+00:00 · methodology

discussion (0)

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Works this paper leans on

102 extracted references · 1 canonical work pages

  1. [1]

    Ackerman, A. S. & Marley, M. S. 2001, ApJ, 556, 872

    2001

  2. [2]

    Adams, D., Gao, P., de Pater, I., & Morley, C. V . 2019, ApJ, 874, 61

    2019

  3. [3]

    J., Wittenmyer, R

    Addison, B., Wright, D. J., Wittenmyer, R. A., et al. 2019, PASP, 131, 115003

    2019

  4. [4]

    B., Knutson, H

    Agol, E., Cowan, N. B., Knutson, H. A., et al. 2010, ApJ, 721, 1861

    2010

  5. [5]

    2025, ApJ, 985, L10

    Ahrer, E.-M., Radica, M., Piaulet-Ghorayeb, C., et al. 2025, ApJ, 985, L10

    2025

  6. [6]

    S., Tremblin, P., Manners, J., Baraffe, I., & Mayne, N

    Amundsen, D. S., Tremblin, P., Manners, J., Baraffe, I., & Mayne, N. J. 2017, A&A, 598, A97

    2017

  7. [7]

    & Lavvas, P

    Arfaux, A. & Lavvas, P. 2024, MNRAS, 530, 482

    2024

  8. [8]

    & Forget, F

    Bertrand, T. & Forget, F. 2017, Icarus, 287, 72

    2017

  9. [9]

    Bohren, C. F. & Huffman, D. R. 1983, Absorption and scattering of light by small particles (New York: John Wiley & Sons)

    1983

  10. [10]

    2005, A&A, 444, L15

    Bouchy, F., Udry, S., Mayor, M., et al. 2005, A&A, 444, L15

    2005

  11. [11]

    Brande, J., Crossfield, I. J. M., Kreidberg, L., et al. 2024, ApJ, 961, L23

    2024

  12. [12]

    1943, Reviews of Modern Physics, 15, 1

    Chandrasekhar, S. 1943, Reviews of Modern Physics, 15, 1

    1943

  13. [13]

    A., Mayne, N

    Christie, D. A., Mayne, N. J., Gillard, R. M., et al. 2022, MNRAS, 517, 1407

    2022

  14. [14]

    L., Tennyson, J., & Yurchenko, S

    Chubb, K. L., Tennyson, J., & Yurchenko, S. N. 2020, MNRAS, 493, 1531

    2020

  15. [15]

    I., Paradise, A., Bollasina, M

    Cohen, M., Palmer, P. I., Paradise, A., Bollasina, M. A., & Tiranti, P. I. 2024, AJ, 167, 97

    2024

  16. [16]

    A., Yurchenko, S

    Coles, P. A., Yurchenko, S. N., & Tennyson, J. 2019, MNRAS, 490, 4638

    2019

  17. [17]

    J., & Kempton, E

    Corrales, L., Gavilan, L., Teal, D. J., & Kempton, E. M. R. 2023, ApJ, 943, L26

    2023

  18. [18]

    E., Fossati, L., Koskinen, T., et al

    Cubillos, P. E., Fossati, L., Koskinen, T., et al. 2023, A&A, 671, A170

    2023

  19. [19]

    1993, A Simple and Accurate Method for Calculating Viscosity of Gaseous Mixtures, Report of investigations (U.S

    Davidson, T. 1993, A Simple and Accurate Method for Calculating Viscosity of Gaseous Mixtures, Report of investigations (U.S. Department of the Interior, Bureau of Mines, Amarillo, TX) Désert, J.-M., Sing, D., Vidal-Madjar, A., et al. 2011, A&A, 526, A12

    1993

  20. [20]

    J., et al

    Drummond, B., Hébrard, E., Mayne, N. J., et al. 2020, A&A, 636, A68

    2020

  21. [21]

    W., Xin, Y ., et al

    Finnerty, L., Xuan, J. W., Xin, Y ., et al. 2024, AJ, 167, 43

    2024

  22. [22]

    S., Henderson, B

    Fleury, B., Gudipati, M. S., Henderson, B. L., & Swain, M. 2019, ApJ, 871, 158

    2019

  23. [23]

    2024, Nature, 632, 752

    Fu, G., Welbanks, L., Deming, D., et al. 2024, Nature, 632, 752

    2024

  24. [24]

    & Benneke, B

    Gao, P. & Benneke, B. 2018, ApJ, 863, 165

    2018

  25. [25]

    Gao, P., Piette, A. A. A., Steinrueck, M. E., et al. 2023, ApJ, 951, 96

    2023

  26. [26]

    P., Lee, E

    Gao, P., Thorngren, D. P., Lee, E. K. H., et al. 2020, Nature Astronomy, 4, 951

    2020

  27. [27]

    J., Charbonneau, D., Burrows, A., et al

    Grillmair, C. J., Charbonneau, D., Burrows, A., et al. 2007, ApJ, 658, L115

    2007

  28. [28]

    Guillot, T., Ida, S., & Ormel, C. W. 2014, A&A, 572, A72

    2014

  29. [29]

    2019, in EPSC-DPS Joint Meeting 2019, V ol

    Hargreaves, R., Gordon, I., Kochanov, R., & Rothman, L. 2019, in EPSC-DPS Joint Meeting 2019, V ol. 2019, EPSC–DPS2019–919

    2019

  30. [30]

    J., Gordon, I

    Hargreaves, R. J., Gordon, I. E., Rey, M., et al. 2020, ApJS, 247, 55

    2020

  31. [31]

    J., Tennyson, J., Kaminsky, B

    Harris, G. J., Tennyson, J., Kaminsky, B. M., Pavlenko, Y . V ., & Jones, H. R. A. 2006, MNRAS, 367, 400

    2006

  32. [32]

    M., Lewis, N

    He, C., Hörst, S. M., Lewis, N. K., et al. 2018, AJ, 156, 38

    2018

  33. [33]

    M., Lewis, N

    He, C., Hörst, S. M., Lewis, N. K., et al. 2020, Planetary Science Journal, 1, 51

    2020

  34. [34]

    M., Radke, M., & Yant, M

    He, C., Hörst, S. M., Radke, M., & Yant, M. 2022, The Planetary Science Journal, 3, 25

    2022

  35. [35]

    E., et al

    He, C., Radke, M., Moran, S. E., et al. 2024, Nature Astronomy, 8, 182

    2024

  36. [36]

    Helling, C., Woitke, P., & Thi, W. F. 2008, A&A, 485, 547 Hörst, S. M., He, C., Lewis, N. K., et al. 2018, Nature Astronomy, 2, 303

    2008

  37. [37]

    E., Pearson, N., et al

    Huseby, L., Moran, S. E., Pearson, N., et al. 2025, Planetary Science Journal, 6, 145

    2025

  38. [38]

    E., Lewis, N

    Inglis, J., Batalha, N. E., Lewis, N. K., et al. 2024, ApJ, 973, L41

    2024

  39. [39]

    Jacobson, M. Z. 2005, Fundamentals of Atmospheric Modeling, 2nd edn. (Cam- bridge University Press, Cambridge)

    2005

  40. [40]

    E., van der Avoird, A., et al

    Karman, T., Gordon, I. E., van der Avoird, A., et al. 2019, Icarus, 328, 160

    2019

  41. [41]

    P., Lewis, N

    Kataria, T., Showman, A. P., Lewis, N. K., et al. 2013, ApJ, 767, 76

    2013

  42. [42]

    & Ikoma, M

    Kawashima, Y . & Ikoma, M. 2018, ApJ, 853, 7

    2018

  43. [43]

    M.-R., Bean, J

    Kempton, E. M.-R., Bean, J. L., Louie, D. R., et al. 2018, PASP, 130, 114401

    2018

  44. [44]

    Kempton, E. M. R., Zhang, M., Bean, J. L., et al. 2023, Nature, 620, 67 Article number, page 13 A&A proofs:manuscript no. aa60641-26

    2023

  45. [45]

    N., Sagan, C., Arakawa, E

    Khare, B. N., Sagan, C., Arakawa, E. T., et al. 1984, Icarus, 60, 127

    1984

  46. [46]

    2005, Journal of Research of the National Institute of Standards and Technology, 110, 1

    Kim, J., Mulholland, G., Kukuck, S., & Pui, D. 2005, Journal of Research of the National Institute of Standards and Technology, 110, 1

    2005

  47. [47]

    & Heng, K

    Kitzmann, D. & Heng, K. 2018, MNRAS, 475, 94

    2018

  48. [48]

    A., Lewis, N., Fortney, J

    Knutson, H. A., Lewis, N., Fortney, J. J., et al. 2012, ApJ, 754, 22

    2012

  49. [49]

    L., Désert, J.-M., et al

    Kreidberg, L., Bean, J. L., Désert, J.-M., et al. 2014, Nature, 505, 69

    2014

  50. [50]

    Larson, E. J. L., Toon, O. B., West, R. A., & Friedson, A. J. 2015, Icarus, 254, 122

    2015

  51. [51]

    & Koskinen, T

    Lavvas, P. & Koskinen, T. 2017, ApJ, 847, 32

    2017

  52. [52]

    2024, arXiv e-prints, arXiv:2410.09981

    Lavvas, P., Paraskevaidou, S., & Arfaux, A. 2024, arXiv e-prints, arXiv:2410.09981

    work page arXiv 2024

  53. [53]

    V ., & Griffith, C

    Lavvas, P., Yelle, R. V ., & Griffith, C. A. 2010, Icarus, 210, 832

    2010

  54. [54]

    2012, Icarus, 218, 707

    Lebonnois, S., Burgalat, J., Rannou, P., & Charnay, B. 2012, Icarus, 218, 707

    2012

  55. [55]

    Lee, E. K. H. 2023, MNRAS, 524, 2918

    2023

  56. [56]

    Lee, E. K. H. 2025, A&A, 698, A220

    2025

  57. [57]

    Lee, E. K. H. & Ohno, K. 2025, A&A, 695, A111

    2025

  58. [58]

    Lee, E. K. H., Parmentier, V ., Hammond, M., et al. 2021, MNRAS, 506, 2695

    2021

  59. [59]

    Lee, E. K. H., Tan, X., & Tsai, S.-M. 2024, MNRAS, 529, 2686

    2024

  60. [60]

    Lee, E. K. H., Tsai, S.-M., Hammond, M., & Tan, X. 2023, A&A, 672, A110

    2023

  61. [61]

    Lee, E. K. H., Wardenier, J. P., Prinoth, B., et al. 2022, ApJ, 929, 180

    2022

  62. [62]

    E., Rothman, L

    Li, G., Gordon, I. E., Rothman, L. S., et al. 2015, ApJS, 216, 15

    2015

  63. [63]

    T., Mayne, N

    Mak, M. T., Mayne, N. J., Sergeev, D. E., et al. 2023, Journal of Geophysical Research (Atmospheres), 128, e2023JD039343

    2023

  64. [64]

    T., Sergeev, D

    Mak, M. T., Sergeev, D. E., Mayne, N., et al. 2024, MNRAS, 529, 3971

    2024

  65. [65]

    T., Sergeev, D

    Mak, M. T., Sergeev, D. E., Mayne, N. J., et al. 2025, MNRAS, 542, 1873

    2025

  66. [66]

    2025, AJ, 169, 221

    Malsky, I., Rauscher, E., Stevenson, K., et al. 2025, AJ, 169, 221

    2025

  67. [67]

    W., Carslaw, K

    Mann, G. W., Carslaw, K. S., Spracklen, D. V ., et al. 2010, Geoscientific Model Development, 3, 519 Moosmüller, H. & Sorensen, C. M. 2018, J. Quant. Spectr. Rad. Transf., 219, 333

    2010

  68. [68]

    E., Hörst, S

    Moran, S. E., Hörst, S. M., Vuitton, V ., et al. 2020, Planetary Science Journal, 1, 17

    2020

  69. [69]

    V ., Fortney, J

    Morley, C. V ., Fortney, J. J., Kempton, E. M. R., et al. 2013, ApJ, 775, 33

    2013

  70. [70]

    V ., Fortney, J

    Morley, C. V ., Fortney, J. J., Marley, M. S., et al. 2015, ApJ, 815, 110 Morán, J. 2022, Fractal and Fractional, 6, 529

    2015

  71. [71]

    & Kawashima, Y

    Ohno, K. & Kawashima, Y . 2020, ApJ, 895, L47

    2020

  72. [72]

    & Okuzumi, S

    Ohno, K. & Okuzumi, S. 2017, ApJ, 835, 261

    2017

  73. [73]

    & Okuzumi, S

    Ohno, K. & Okuzumi, S. 2018, ApJ, 859, 34

    2018

  74. [74]

    2020, ApJ, 891, 131

    Ohno, K., Okuzumi, S., & Tazaki, R. 2020, ApJ, 891, 131

    2020

  75. [75]

    J., et al

    Ohno, K., Schlawin, E., Bell, T. J., et al. 2025, ApJ, 979, L7

    2025

  76. [76]

    Owen, J. E. & Murray-Clay, R. A. 2025, MNRAS, 543, 587

    2025

  77. [77]

    O., Murga, M

    Pentsak, E. O., Murga, M. S., & Ananikov, V . P. 2024, ACS Earth and Space Chemistry, 8, 798

    2024

  78. [78]

    M., Radke, M

    Pesciotta, C., Hörst, S. M., Radke, M. J., et al. 2026, ApJ, 1002, 221

    2026

  79. [79]

    L., Kyuberis, A

    Polyansky, O. L., Kyuberis, A. A., Zobov, N. F., et al. 2018, MNRAS, 480, 2597

    2018

  80. [80]

    K., Gibson, N

    Pont, F., Sing, D. K., Gibson, N. P., et al. 2013, MNRAS, 432, 2917

    2013

Showing first 80 references.