pith. sign in

arxiv: 2602.18553 · v2 · pith:DEFMDYFXnew · submitted 2026-02-20 · 🌌 astro-ph.EP

POSEIDON I: The Dynamical Origins of Transiting Neptunes

Juan I. Espinoza-Retamal , Joshua N. Winn , Rafael Brahm , Cristobal Petrovich , Gu{\dh}mundur Stef\'ansson , Hareesh Bhaskar , Elise Koo , Andr\'es Jord\'an
show 12 more authors
Marcelo Tala Pinto Melissa J. Hobson Hugo Veldhuis Felipe I. Rojas Johanna K. Teske R. Paul Butler Jeffrey D. Crane Stephen Shectman Shreyas Vissapragada Gavin Boyle Rodrigo Leiva Vincent Suc
This is my paper

Pith reviewed 2026-05-25 07:21 UTC · model grok-4.3

classification 🌌 astro-ph.EP
keywords exoplanetsstellar obliquityRossiter-McLaughlinNeptuneplanetary migrationspin-orbit alignmentTOI-181TOI-883
0
0 comments X

The pith

Transiting Neptunes show a mix of aligned and random stellar spin-orbit angles, matching the pattern for Jupiters.

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

The paper measures sky-projected obliquities for two new transiting Neptunes using Rossiter-McLaughlin spectroscopy. One system is misaligned and the other eccentric, both consistent with high-eccentricity migration. When added to the existing sample the distribution of angles fits a model with mostly aligned orbits plus a smaller random component. This shape closely resembles the obliquity distribution of transiting Jupiters, implying the two populations experienced similar dynamical histories.

Core claim

The current sample of transiting Neptunes is consistent with a population of well-aligned systems and a smaller population with nearly random obliquities; this distribution resembles that observed for more massive planets, suggesting that transiting Jupiters and Neptunes originate from similar dynamical processes.

What carries the argument

Addition of two new Rossiter-McLaughlin measurements of sky-projected spin-orbit angle λ to the existing sample, followed by statistical comparison of the combined obliquity distribution against aligned-plus-random and bimodal models.

If this is right

  • High-eccentricity migration is a viable channel for at least some transiting Neptunes.
  • The dynamical processes that set spin-orbit angles do not depend strongly on planet mass in the Neptune-to-Jupiter range.
  • The relative fraction of aligned versus random systems can be refined with additional measurements.

Where Pith is reading between the lines

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

  • If the similarity persists, models of scattering or disk migration must produce comparable outcomes across a wide mass range.
  • Future data could distinguish whether the random component is fully isotropic or carries a weak preferred direction.
  • Transit detection biases may still affect how well the current sample represents the full population.

Load-bearing premise

The combined measurements give an unbiased view of the true obliquity distribution for transiting Neptunes.

What would settle it

A significantly larger sample whose obliquity histogram deviates strongly from an aligned-plus-random mixture would falsify the consistency claim.

Figures

Figures reproduced from arXiv: 2602.18553 by Andr\'es Jord\'an, Cristobal Petrovich, Elise Koo, Felipe I. Rojas, Gavin Boyle, Gu{\dh}mundur Stef\'ansson, Hareesh Bhaskar, Hugo Veldhuis, Jeffrey D. Crane, Johanna K. Teske, Joshua N. Winn, Juan I. Espinoza-Retamal, Marcelo Tala Pinto, Melissa J. Hobson, Rafael Brahm, Rodrigo Leiva, R. Paul Butler, Shreyas Vissapragada, Stephen Shectman, Vincent Suc.

Figure 1
Figure 1. Figure 1: Orbital period versus planet radius for transit￾ing planets. Gray points are from the TEPCat catalog (J. Southworth 2011) as of November 2025. Colored points are those for which the stellar obliquity has been measured, with five-pointed stars highlighting TOI-181 b and TOI-883 b. Dashed blue lines indicate the boundaries of the Neptune desert, ridge, and savanna as defined by A. Castro-González et al. (202… view at source ↗
Figure 2
Figure 2. Figure 2: Radial-velocity and photometric observations of TOI-181. In all cases, the red curves are best-fit models and the residuals are plotted beneath the data. The error bars include a white noise jitter term added in quadrature. a) PFS velocities spanning a transit and exhibiting the RM effect. b) HARPS velocities across all orbital phases. c) MOANA photometry of the same transit observed with PFS. d) Phase-fol… view at source ↗
Figure 3
Figure 3. Figure 3: Radial-velocity and photometric observations of TOI-883. In all cases, the red curves are best-fit models and the residuals are plotted beneath the data. The RV error bars include a white noise jitter term added in quadrature. a) NEID velocities spanning a transit and exhibiting the RM effect. b) HARPS and PFS velocities across all orbital phases. c) Phase-folded photometry based on TESS observations with … view at source ↗
Figure 4
Figure 4. Figure 4: Mass versus radius diagram. Grey points are all the transiting exoplanets from TEPCat (J. Southworth 2011) as of November 2025. Colored points convey the projected obliquity for systems with published measurements. Trian￾gles indicate systems with only upper limits available for the mass. TOI-181 b and TOI-883 b are highlighted as stars fol￾lowing the same color code. The green dashed lines indicate the re… view at source ↗
Figure 5
Figure 5. Figure 5: Stellar obliquity of Neptune (2 ≤ Rp/R⊕ ≤ 6 or 10 ≤ Mp/M⊕ ≤ 50) hosts as a function of the stellar effective temperature. Upper panels show the projected obliquity while lower panels the true obliquity. Left panels show systems where no companion star has been reported and right panels show known multiple-star systems. Neptunes that have planetary companions with periods between 1/5th and 5 times the perio… view at source ↗
Figure 6
Figure 6. Figure 6: Inferred stellar obliquity distributions for the samples of Jupiter and Neptune hosts. This inference was based on sky-projected obliquity measurements, following the methodology of J. Dong & D. Foreman-Mackey (2023), without including information about the stellar inclination. The solid line shows the median distribution, and random samples from the posteriors are shown in the background. a) Distribution … view at source ↗
Figure 7
Figure 7. Figure 7: Inferred stellar obliquity distributions for the different subsamples of Neptune hosts. In all panels the median distribution is shown as the solid line, and random samples from the posteriors are shown in the background. a) Neptunes that are apparently isolated, i.e., that have no known close planetary companions (orange). b) Neptunes with known close companions (blue). c) Neptune hosts that are single st… view at source ↗
read the original abstract

We present the first results from the POSEIDON survey, aimed at constraining the dynamical origins of transiting Neptunes through stellar obliquity measurements. We report Rossiter-McLaughlin observations of two Neptunes, TOI-181 b and TOI-883 b, obtained with high-resolution spectroscopy from Magellan/PFS and WIYN/NEID. TOI-181 b is on a 4.5-day orbit with a sky-projected spin-orbit misalignment $\lambda = 32.0_{-6.5}^{+6.3}\,^{\circ}$ and a low eccentricity ($e<0.12$ with $2\sigma$ confidence). TOI-883 b has a longer orbital period of 10 days with $\lambda = 22_{-14}^{+15}\,^{\circ}$ and eccentricity $e = 0.16 \pm 0.03$. The significant misalignment of TOI-181 b and the significant eccentricity of TOI-883 b are suggestive of high-eccentricity migration for both systems. After adding these and other new measurements to the sample, we analyze the obliquity distribution of the host stars of transiting Neptunes. Earlier studies had suggested that the obliquity distribution is bimodal, with peaks corresponding to aligned orbits and polar orbits; the addition of more measurements has weakened the evidence for bimodality. The current sample appears to be consistent with a population of well-aligned systems and a smaller population with nearly random obliquities. This distribution resembles that observed for more massive planets, suggesting that transiting Jupiters and Neptunes originate from similar dynamical processes.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript reports new Rossiter-McLaughlin observations of two transiting Neptunes (TOI-181 b with λ ≈ 32° and e < 0.12; TOI-883 b with λ ≈ 22° and e = 0.16 ± 0.03) obtained with Magellan/PFS and WIYN/NEID. After incorporating these and other recent measurements into the literature sample, the authors analyze the obliquity distribution of transiting Neptunes and conclude that it is consistent with a mixture of well-aligned systems plus a smaller population with nearly random orientations. This distribution is stated to resemble that of transiting Jupiters, implying similar dynamical origins via high-eccentricity migration for some systems. The addition of measurements is noted to have weakened earlier evidence for bimodality.

Significance. If the population inference holds after accounting for observational selection, the result would be significant for unifying the dynamical histories of Neptunes and Jupiters. The new RM measurements add concrete data points that help test prior claims of distinct Neptune obliquity behavior. The manuscript provides explicit measured values with uncertainties and notes the change in evidence for bimodality.

major comments (2)
  1. [obliquity distribution analysis (post-observation section)] The central claim that the combined sample 'appears to be consistent with a population of well-aligned systems and a smaller population with nearly random obliquities' (abstract) and resembles the Jupiter distribution is load-bearing on the assumption of an unbiased draw from the underlying obliquity distribution. The manuscript does not describe forward-modeling of the RM selection function (dependent on host brightness, v sin i, transit depth, and geometry), which correlates with stellar and planetary properties and could alter the inferred aligned/random fractions.
  2. [obliquity distribution analysis (post-observation section)] The comparison to the Jupiter obliquity distribution (abstract) requires that the Neptune sample selection effects are comparable to those in the Jupiter RM samples; without explicit modeling or quantification of differential biases, the similarity conclusion rests on an untested assumption.
minor comments (2)
  1. [abstract and methods] The abstract reports specific λ and e values with uncertainties for the two new systems; the corresponding methods, data tables, and fitting details (e.g., how the RM model and eccentricity constraints were derived) should be cross-referenced explicitly in the main text for reproducibility.
  2. [results section] Notation for sky-projected obliquity (λ) and eccentricity (e) is standard, but ensure consistent use of 1σ vs. 2σ confidence intervals across text and any tables/figures.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive feedback, which highlights important considerations for interpreting the obliquity sample. We agree that selection effects warrant explicit discussion and will revise the manuscript accordingly to qualify our conclusions. Point-by-point responses to the major comments follow.

read point-by-point responses

  1. Referee: The central claim that the combined sample 'appears to be consistent with a population of well-aligned systems and a smaller population with nearly random obliquities' (abstract) and resembles the Jupiter distribution is load-bearing on the assumption of an unbiased draw from the underlying obliquity distribution. The manuscript does not describe forward-modeling of the RM selection function (dependent on host brightness, v sin i, transit depth, and geometry), which correlates with stellar and planetary properties and could alter the inferred aligned/random fractions.

    Authors: We agree that a full forward-modeling of the RM selection function would strengthen the statistical interpretation. Our analysis is descriptive of the observed sample and documents the weakening of bimodality evidence with new measurements. In revision we will add a subsection on potential biases, describing how host brightness, v sin i, and transit geometry influence RM detectability, and will explicitly state that the aligned-plus-random fractions are preliminary pending such modeling. revision: yes

  2. Referee: The comparison to the Jupiter obliquity distribution (abstract) requires that the Neptune sample selection effects are comparable to those in the Jupiter RM samples; without explicit modeling or quantification of differential biases, the similarity conclusion rests on an untested assumption.

    Authors: We acknowledge that the resemblance is currently qualitative. While both samples rely on RM measurements of transiting planets around bright hosts, we will revise the discussion to compare median stellar magnitudes, v sin i values, and planetary radii between the Neptune and Jupiter RM samples. This will allow readers to assess the plausibility of comparable biases; we will also note that a joint forward model of both populations lies beyond the present scope. revision: yes

Circularity Check

0 steps flagged

No circularity: distribution analysis uses new independent RM data plus external literature sample

full rationale

The paper's central claim follows from compiling new Rossiter-McLaughlin measurements (TOI-181 b, TOI-883 b) with previously published obliquity values from the literature and inspecting the resulting empirical distribution for consistency with an aligned-plus-isotropic mixture. No equations, fitted parameters, or self-citations are invoked that would make the reported mixture fractions or resemblance to the Jupiter sample tautological by construction. The derivation chain is observational and externally falsifiable; the reader's assessment of score 2 is consistent with the absence of any load-bearing self-referential step.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

Based solely on the abstract, the work relies on established observational techniques without introducing new free parameters, axioms beyond standard domain assumptions, or invented entities.

axioms (1)
  • domain assumption The Rossiter-McLaughlin effect modeling assumptions (including stellar rotation, limb darkening, and orbital geometry) are valid for these systems.
    The reported lambda and eccentricity values depend on these standard modeling choices in high-resolution transit spectroscopy.

pith-pipeline@v0.9.0 · 5928 in / 1406 out tokens · 40048 ms · 2026-05-25T07:21:52.965135+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Lean theorems connected to this paper

Citations machine-checked in the Pith Canon. Every link opens the source theorem in the public Lean library.

What do these tags mean?
matches
The paper's claim is directly supported by a theorem in the formal canon.
supports
The theorem supports part of the paper's argument, but the paper may add assumptions or extra steps.
extends
The paper goes beyond the formal theorem; the theorem is a base layer rather than the whole result.
uses
The paper appears to rely on the theorem as machinery.
contradicts
The paper's claim conflicts with a theorem or certificate in the canon.
unclear
Pith found a possible connection, but the passage is too broad, indirect, or ambiguous to say the theorem truly supports the claim.

Reference graph

Works this paper leans on

121 extracted references · 121 canonical work pages · 4 internal anchors

  1. [1]

    C., Horner, J., Wittenmyer, R

    Addison, B. C., Horner, J., Wittenmyer, R. A., et al. 2021, AJ, 162, 137, doi: 10.3847/1538-3881/ac1685

    work page doi:10.3847/1538-3881/ac1685 2021

  2. [2]

    N., Johnson, J

    Albrecht, S., Winn, J. N., Johnson, J. A., et al. 2012, ApJ, 757, 18, doi: 10.1088/0004-637X/757/1/18

    work page doi:10.1088/0004-637x/757/1/18 2012

  3. [3]

    H., Dawson, R

    Albrecht, S. H., Dawson, R. I., & Winn, J. N. 2022, PASP, 134, 082001, doi: 10.1088/1538-3873/ac6c09

    work page doi:10.1088/1538-3873/ac6c09 2022

  4. [4]

    H., Marcussen, M

    Albrecht, S. H., Marcussen, M. L., Winn, J. N., Dawson, R. I., & Knudstrup, E. 2021, ApJL, 916, L1, doi: 10.3847/2041-8213/ac0f03

    work page doi:10.3847/2041-8213/ac0f03 2021

  5. [5]

    R., Storch, N

    Anderson, K. R., Storch, N. I., & Lai, D. 2016, MNRAS, 456, 3671, doi: 10.1093/mnras/stv2906

    work page doi:10.1093/mnras/stv2906 2016

  6. [6]

    A., et al

    Ansdell, M., Gaidos, E., Rappaport, S. A., et al. 2016, ApJ, 816, 69, doi: 10.3847/0004-637X/816/2/69 18 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sipőcz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Collabor...

    work page doi:10.3847/0004-637x/816/2/69 2016

  7. [7]

    2023, A&A, 674, A120, doi: 10.1051/0004-6361/202245237

    Attia, M., Bourrier, V., Delisle, J.-B., & Eggenberger, P. 2023, A&A, 674, A120, doi: 10.1051/0004-6361/202245237

    work page doi:10.1051/0004-6361/202245237 2023

  8. [8]

    H., & Laughlin, G

    Batygin, K., Bodenheimer, P. H., & Laughlin, G. P. 2016, ApJ, 829, 114, doi: 10.3847/0004-637X/829/2/114 Beaugé, C., & Nesvorný, D. 2012, ApJ, 751, 119, doi: 10.1088/0004-637X/751/2/119

    work page doi:10.3847/0004-637x/829/2/114 2016

  9. [9]

    2026, ApJ, 997, 327, doi: 10.3847/1538-4357/ae2f58

    Becker, J. 2026, ApJ, 997, 327, doi: 10.3847/1538-4357/ae2f58

    work page doi:10.3847/1538-4357/ae2f58 2026

  10. [10]

    2022, in American Astronomical Society Meeting Abstracts, Vol

    Bender, C., Ninan, J., Terrien, R., et al. 2022, in American Astronomical Society Meeting Abstracts, Vol. 240, American Astronomical Society Meeting #240, 401.01

    work page 2022

  11. [11]

    2022, ApJL, 925, L5, doi: 10.3847/2041-8213/ac49e9

    Best, S., & Petrovich, C. 2022, ApJL, 925, L5, doi: 10.3847/2041-8213/ac49e9

    work page doi:10.3847/2041-8213/ac49e9 2022

  12. [12]

    2025, Nature, 644, 356, doi: 10.1038/s41586-025-09324-0

    Wu, Y.-L. 2025, Nature, 644, 356, doi: 10.1038/s41586-025-09324-0

    work page doi:10.1038/s41586-025-09324-0 2025

  13. [13]

    C., Granados Contreras, A

    Boley, A. C., Granados Contreras, A. P., & Gladman, B. 2016, ApJL, 817, L17, doi: 10.3847/2041-8205/817/2/L17

    work page doi:10.3847/2041-8205/817/2/l17 2016

  14. [14]

    J., Koch , D., Basri , G., Batalha , N., Brown , T., Caldwell , D., et al

    Borucki, W. J., Koch, D., Basri, G., et al. 2010, Science, 327, 977, doi: 10.1126/science.1185402

    work page doi:10.1126/science.1185402 2010

  15. [15]

    2021, A&A, 654, A152, doi: 10.1051/0004-6361/202141527

    Bourrier, V., Lovis, C., Cretignier, M., et al. 2021, A&A, 654, A152, doi: 10.1051/0004-6361/202141527

    work page doi:10.1051/0004-6361/202141527 2021

  16. [16]

    2023, A&A, 669, A63, doi: 10.1051/0004-6361/202245004

    Bourrier, V., Attia, M., Mallonn, M., et al. 2023, A&A, 669, A63, doi: 10.1051/0004-6361/202245004

    work page doi:10.1051/0004-6361/202245004 2023

  17. [17]

    2017, MNRAS, 467, 971, doi: 10.1093/mnras/stx144

    Brahm, R., Jordán, A., Hartman, J., & Bakos, G. 2017, MNRAS, 467, 971, doi: 10.1093/mnras/stx144

    work page doi:10.1093/mnras/stx144 2017

  18. [18]

    2019, AJ, 158, 45, doi: 10.3847/1538-3881/ab279a

    Brahm, R., Espinoza, N., Jordán, A., et al. 2019, AJ, 158, 45, doi: 10.3847/1538-3881/ab279a

    work page doi:10.3847/1538-3881/ab279a 2019

  19. [19]

    D., Wittenmyer, R

    Brahm, R., Nielsen, L. D., Wittenmyer, R. A., et al. 2020, AJ, 160, 235, doi: 10.3847/1538-3881/abba3b

    work page doi:10.3847/1538-3881/abba3b 2020

  20. [20]

    J., et al

    Brahm, R., Ulmer-Moll, S., Hobson, M. J., et al. 2023, AJ, 165, 227, doi: 10.3847/1538-3881/accadd

    work page doi:10.3847/1538-3881/accadd 2023

  21. [21]

    2025, ApJL, 995, L43, doi: 10.3847/2041-8213/ae2603

    Brahm, R., Trifonov, T., Jordán, A., et al. 2025, ApJL, 995, L43, doi: 10.3847/2041-8213/ae2603

    work page doi:10.3847/2041-8213/ae2603 2025

  22. [22]

    and Shibahashi , H

    Bressan, A., Marigo, P., Girardi, L., et al. 2012, MNRAS, 427, 127, doi: 10.1111/j.1365-2966.2012.21948.x

    work page doi:10.1111/j.1365-2966.2012.21948.x 2012

  23. [23]

    P., Marcy, G

    Butler, R. P., Marcy, G. W., Williams, E., et al. 1996, PASP, 108, 500, doi: 10.1086/133755

    work page doi:10.1086/133755 1996

  24. [24]

    A., Clayton G

    Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245, doi: 10.1086/167900

    work page doi:10.1086/167900 1989

  25. [25]

    2018, MNRAS, 477, 5104, doi: 10.1093/mnras/sty894 Castro-González, A., Bourrier, V., Lillo-Box, J., et al

    Casassus, S., Avenhaus, H., Pérez, S., et al. 2018, MNRAS, 477, 5104, doi: 10.1093/mnras/sty894 Castro-González, A., Bourrier, V., Lillo-Box, J., et al. 2024, A&A, 689, A250, doi: 10.1051/0004-6361/202450957

    work page doi:10.1093/mnras/sty894 2018

  26. [26]

    K., et al

    Chontos, A., Huber, D., Grunblatt, S. K., et al. 2024, arXiv e-prints, arXiv:2402.07893, doi: 10.48550/arXiv.2402.07893

    work page doi:10.48550/arxiv.2402.07893 2024

  27. [27]

    Correia, A. C. M., Bourrier, V., & Delisle, J. B. 2020, A&A, 635, A37, doi: 10.1051/0004-6361/201936967

    work page doi:10.1051/0004-6361/201936967 2020

  28. [28]

    D., Shectman, S

    Crane, J. D., Shectman, S. A., & Butler, R. P. 2006, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 6269, Ground-based and Airborne Instrumentation for Astronomy, ed. I. S. McLean & M. Iye, 626931, doi: 10.1117/12.672339

    work page doi:10.1117/12.672339 2006

  29. [29]

    D., Shectman, S

    Crane, J. D., Shectman, S. A., Butler, R. P., et al. 2010, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 7735, Ground-based and Airborne Instrumentation for Astronomy III, ed. I. S

    work page 2010

  30. [30]

    McLean, S. K. Ramsay, & H. Takami, 773553, doi: 10.1117/12.857792

    work page doi:10.1117/12.857792

  31. [31]

    D., Shectman, S

    Crane, J. D., Shectman, S. A., Butler, R. P., Thompson, I. B., & Burley, G. S. 2008, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 7014, Ground-based and Airborne Instrumentation for Astronomy II, ed. I. S. McLean & M. M. Casali, 701479, doi: 10.1117/12.789637

    work page doi:10.1117/12.789637 2008

  32. [32]

    2019, A&A, 631, A28, doi: 10.1051/0004-6361/201935944

    Dalal, S., Hébrard, G., Lecavelier des Étangs, A., et al. 2019, A&A, 631, A28, doi: 10.1051/0004-6361/201935944

    work page doi:10.1051/0004-6361/201935944 2019

  33. [33]

    I., & Johnson, J

    Dawson, R. I., & Johnson, J. A. 2018, ARA&A, 56, 175, doi: 10.1146/annurev-astro-081817-051853

    work page internal anchor Pith review doi:10.1146/annurev-astro-081817-051853 2018

  34. [34]

    2023, AJ, 166, 112, doi: 10.3847/1538-3881/ace105

    Dong, J., & Foreman-Mackey, D. 2023, AJ, 166, 112, doi: 10.3847/1538-3881/ace105

    work page doi:10.3847/1538-3881/ace105 2023

  35. [35]

    2018, Proceedings of the National Academy of Science, 115, 266, doi: 10.1073/pnas.1711406115

    Dong, S., Xie, J.-W., Zhou, J.-L., Zheng, Z., & Luo, A. 2018, Proceedings of the National Academy of Science, 115, 266, doi: 10.1073/pnas.1711406115

    work page doi:10.1073/pnas.1711406115 2018

  36. [36]

    El-Badry, K., Rix, H.-W., & Heintz, T. M. 2021, MNRAS, 506, 2269, doi: 10.1093/mnras/stab323

    work page doi:10.1093/mnras/stab323 2021

  37. [37]

    2019, MNRAS, 490, 2262, doi: 10.1093/mnras/stz2688

    Espinoza, N., Kossakowski, D., & Brahm, R. 2019, MNRAS, 490, 2262, doi: 10.1093/mnras/stz2688

    work page doi:10.1093/mnras/stz2688 2019

  38. [38]

    I., Zhu, W., & Petrovich, C

    Espinoza-Retamal, J. I., Zhu, W., & Petrovich, C. 2023a, AJ, 166, 231, doi: 10.3847/1538-3881/ad00b9

    work page doi:10.3847/1538-3881/ad00b9

  39. [39]

    I., Brahm, R., Petrovich, C., et al

    Espinoza-Retamal, J. I., Brahm, R., Petrovich, C., et al. 2023b, ApJL, 958, L20, doi: 10.3847/2041-8213/ad096d

    work page doi:10.3847/2041-8213/ad096d 2041

  40. [40]

    I., Stefánsson, G., Petrovich, C., et al

    Espinoza-Retamal, J. I., Stefánsson, G., Petrovich, C., et al. 2024, AJ, 168, 185, doi: 10.3847/1538-3881/ad70b8

    work page doi:10.3847/1538-3881/ad70b8 2024

  41. [41]

    I., Jordán, A., Brahm, R., et al

    Espinoza-Retamal, J. I., Jordán, A., Brahm, R., et al. 2025, AJ, 170, 70, doi: 10.3847/1538-3881/ade22e

    work page doi:10.3847/1538-3881/ade22e 2025

  42. [42]

    2007, ApJ, 669, 1298, doi: 10.1086/521702

    Fabrycky, D., & Tremaine, S. 2007, ApJ, 669, 1298, doi: 10.1086/521702

    work page doi:10.1086/521702 2007

  43. [43]

    2017, AJ, 154, 220, doi: 10.3847/1538-3881/aa9332 19

    Foreman-Mackey, D., Agol, E., Angus, R., & Ambikasaran, S. 2017, AJ, 154, 220, doi: 10.3847/1538-3881/aa9332 19

    work page doi:10.3847/1538-3881/aa9332 2017

  44. [44]

    2020, ApJ, 892, 111, doi: 10.3847/1538-4357/ab7b63

    Francis, L., & van der Marel, N. 2020, ApJ, 892, 111, doi: 10.3847/1538-4357/ab7b63

    work page doi:10.3847/1538-4357/ab7b63 2020

  45. [45]

    J., Petigura, E

    Fulton, B. J., Petigura, E. A., Blunt, S., & Sinukoff, E. 2018, PASP, 130, 044504, doi: 10.1088/1538-3873/aaaaa8 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al. 2023, A&A, 674, A1, doi: 10.1051/0004-6361/202243940

    work page doi:10.1088/1538-3873/aaaaa8 2018

  46. [46]

    B., Stern, H

    Gelman, A., Carlin, J. B., Stern, H. S., et al. 2014, Bayesian Data Analysis

    work page 2014

  47. [47]

    1966, Icarus, 5, 375, doi: 10.1016/0019-1035(66)90051-0

    Goldreich, P., & Soter, S. 1966, Icarus, 5, 375, doi: 10.1016/0019-1035(66)90051-0

    work page doi:10.1016/0019-1035(66)90051-0 1966

  48. [48]

    1980, ApJ, 241, 425, doi: 10.1086/158356

    Goldreich, P., & Tremaine, S. 1980, ApJ, 241, 425, doi: 10.1086/158356

    work page doi:10.1086/158356 1980

  49. [49]

    2022, A&A, 668, A172, doi: 10.1051/0004-6361/202244182

    Grouffal, S., Santerne, A., Bourrier, V., et al. 2022, A&A, 668, A172, doi: 10.1051/0004-6361/202244182

    work page doi:10.1051/0004-6361/202244182 2022

  50. [50]

    2025, A&A, 701, A173, doi: 10.1051/0004-6361/202555487

    Grouffal, S., Santerne, A., Bourrier, V., et al. 2025, A&A, 701, A173, doi: 10.1051/0004-6361/202555487

    work page doi:10.1051/0004-6361/202555487 2025

  51. [51]

    2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Halverson, S., Terrien, R., Mahadevan, S., et al. 2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9908, Ground-based and Airborne Instrumentation for Astronomy VI, ed. C. J

    work page 2016

  52. [52]

    Simard, & H

    Evans, L. Simard, & H. Takami, 99086P, doi: 10.1117/12.2232761

    work page doi:10.1117/12.2232761

  53. [53]

    B., & Batygin, K

    Handley, L. B., & Batygin, K. 2026, arXiv e-prints, arXiv:2601.04140, doi: 10.48550/arXiv.2601.04140

    work page doi:10.48550/arxiv.2601.04140 2026

  54. [54]

    B., Howard, A

    Handley, L. B., Howard, A. W., Rubenzahl, R. A., et al. 2025, AJ, 169, 212, doi: 10.3847/1538-3881/adb71b

    work page doi:10.3847/1538-3881/adb71b 2025

  55. [55]

    2010, ApJ, 709, 458, doi: 10.1088/0004-637X/709/1/458

    Hirano, T., Suto, Y., Taruya, A., et al. 2010, ApJ, 709, 458, doi: 10.1088/0004-637X/709/1/458

    work page doi:10.1088/0004-637x/709/1/458 2010

  56. [56]

    2020, ApJL, 899, L13, doi: 10.3847/2041-8213/aba6eb

    Hirano, T., Krishnamurthy, V., Gaidos, E., et al. 2020, ApJL, 899, L13, doi: 10.3847/2041-8213/aba6eb

    work page doi:10.3847/2041-8213/aba6eb 2020

  57. [57]

    2021, Proceedings of the National Academy of Science, 118, e2017418118, doi: 10.1073/pnas.2017418118

    Hjorth, M., Albrecht, S., Hirano, T., et al. 2021, Proceedings of the National Academy of Science, 118, e2017418118, doi: 10.1073/pnas.2017418118

    work page doi:10.1073/pnas.2017418118 2021

  58. [58]

    W., Marcy, G

    Howard, A. W., Marcy, G. W., Johnson, J. A., et al. 2010, Science, 330, 653, doi: 10.1126/science.1194854

    work page doi:10.1126/science.1194854 2010

  59. [59]

    Hunter, J. D. 2007, Computing in Science and Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

    work page doi:10.1109/mcse.2007.55 2007

  60. [60]

    M., Twicken, J

    Jenkins, J. M., Twicken, J. D., McCauliff, S., et al. 2016, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 9913, Software and Cyberinfrastructure for Astronomy IV, ed. G. Chiozzi & J. C. Guzman, 99133E, doi: 10.1117/12.2233418 Jordán, A., Brahm, R., Espinoza, N., et al. 2019, AJ, 157, 100, doi: 10.3847/1538-3881/aafa79

    work page doi:10.1117/12.2233418 2016

  61. [61]

    W., et al

    Kanodia, S., Mahadevan, S., Ramsey, L. W., et al. 2018, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 10702, Ground-based and Airborne Instrumentation for Astronomy VII, ed. C. J

    work page 2018

  62. [62]

    Simard, & H

    Evans, L. Simard, & H. Takami, 107026Q, doi: 10.1117/12.2313491

    work page doi:10.1117/12.2313491

  63. [63]

    Kipping, D. M. 2013, MNRAS, 435, 2152, doi: 10.1093/mnras/stt1435

    work page doi:10.1093/mnras/stt1435 2013

  64. [64]

    H., Winn, J

    Knudstrup, E., Albrecht, S. H., Winn, J. N., et al. 2024, A&A, 690, A379, doi: 10.1051/0004-6361/202450627

    work page doi:10.1051/0004-6361/202450627 2024

  65. [65]

    2015, PASP, 127, 1161, doi: 10.1086/683602

    Kreidberg, L. 2015, PASP, 127, 1161, doi: 10.1086/683602

    work page internal anchor Pith review doi:10.1086/683602 2015

  66. [66]

    Lammers, C., & Winn, J. N. 2026, AJ, 171, 18, doi: 10.3847/1538-3881/ae21de Lightkurve Collaboration, Cardoso, J. V. d. M., Hedges, C., et al. 2018, Lightkurve: Kepler and TESS time series analysis in Python„ Astrophysics Source Code Library http://ascl.net/1812.013

    work page doi:10.3847/1538-3881/ae21de 2026

  67. [67]

    Lin, D. N. C., & Papaloizou, J. 1986, ApJ, 309, 846, doi: 10.1086/164653

    work page doi:10.1086/164653 1986

  68. [68]

    M., & Millholland, S

    Louden, E. M., & Millholland, S. C. 2024, ApJ, 974, 304, doi: 10.3847/1538-4357/ad74ff

    work page doi:10.3847/1538-4357/ad74ff 2024

  69. [69]

    2015, ApJL, 798, L44, doi: 10.1088/2041-8205/798/2/L44

    Marino, S., Perez, S., & Casassus, S. 2015, ApJL, 798, L44, doi: 10.1088/2041-8205/798/2/L44

    work page doi:10.1088/2041-8205/798/2/l44 2015

  70. [70]

    Martioli, E., Hébrard, G., Correia, A. C. M., Laskar, J., & Lecavelier des Etangs, A. 2021, A&A, 649, A177, doi: 10.1051/0004-6361/202040235

    work page doi:10.1051/0004-6361/202040235 2021

  71. [71]

    Masuda, K., & Winn, J. N. 2020, AJ, 159, 81, doi: 10.3847/1538-3881/ab65be

    work page doi:10.3847/1538-3881/ab65be 2020

  72. [72]

    2003, The Messenger, 114, 20

    Mayor, M., Pepe, F., Queloz, D., et al. 2003, The Messenger, 114, 20

    work page 2003

  73. [73]

    2016, A&A, 589, A75, doi: 10.1051/0004-6361/201528065

    Mazeh, T., Holczer, T., & Faigler, S. 2016, A&A, 589, A75, doi: 10.1051/0004-6361/201528065

    work page doi:10.1051/0004-6361/201528065 2016

  74. [74]

    1924, Astrophysical Journal, 60, 22-31 (1924), 60

    McLaughlin, D. 1924, Astrophysical Journal, 60, 22-31 (1924), 60

    work page 1924

  75. [75]

    2023, MNRAS, 521, 1066, doi: 10.1093/mnras/stad543

    Mistry, P., Pathak, K., Lekkas, G., et al. 2023, MNRAS, 521, 1066, doi: 10.1093/mnras/stad543

    work page doi:10.1093/mnras/stad543 2023

  76. [76]

    2014, AJ, 148, 81, doi: 10.1088/0004-6256/148/5/81

    Munari, U., Henden, A., Frigo, A., et al. 2014, AJ, 148, 81, doi: 10.1088/0004-6256/148/5/81

    work page doi:10.1088/0004-6256/148/5/81 2014

  77. [77]

    2011, Nature, 473, 187, doi: 10.1038/nature10076

    Teyssandier, J. 2011, Nature, 473, 187, doi: 10.1038/nature10076

    work page doi:10.1038/nature10076 2011

  78. [78]

    I., & Lin, D

    Ogilvie, G. I., & Lin, D. N. C. 2007, ApJ, 661, 1180, doi: 10.1086/515435

    work page doi:10.1086/515435 2007

  79. [79]

    2020, A&A, 643, A25, doi: 10.1051/0004-6361/202038583

    Palle, E., Oshagh, M., Casasayas-Barris, N., et al. 2020, A&A, 643, A25, doi: 10.1051/0004-6361/202038583

    work page doi:10.1051/0004-6361/202038583 2020

  80. [80]

    Á., & Lindegren, L

    Perryman, M., Hartman, J., Bakos, G. Á., & Lindegren, L. 2014, ApJ, 797, 14, doi: 10.1088/0004-637X/797/1/14

    work page doi:10.1088/0004-637x/797/1/14 2014

Showing first 80 references.