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The Occurrence Rate of Nearby Planetary Companions to Hot Jupiters

T0 review · 4 major / 4 minor · reviewed 2026-08-03 · deepseek-v4-flash

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Pith's one-line read At least about 8% of hot Jupiters carry a nearby small companion, implying a comparable fraction formed via calm disk migration or in situ rather than violent high-eccentricity migration.

desk verdict A careful, much larger TESS search for close-in companions to hot Jupiters gives a 7.6% occurrence rate, but the headline number is conditional on a well-aligned mutual-inclination prior—the same six detections imply ~37% under isotropic inclinations. read the letter →

arxiv 2601.13302 v2 pith:FEATIUEW submitted 2026-01-19 astro-ph.EP

Lizhou Sha , Andrew M. Vanderburg , Chelsea X. Huang , Samuel Christian , Kevin Burdge , Nicholas Saunders , Khalid Barkaoui , Alexander Belinski
show 28 more authors
Serge Bergeron Zoë L. de Beurs Allyson Bieryla Karen A. Collins Giuseppe Conzo Gareb Fernández-Rodríguez Akihiko Fukui Davide Gandolfi Tristan Guillot Joel D. Hartman Kai Ikuta David W. Latham Jerome P. de Leon Bob Massey Gabriel Murawski Felipe Murgas Norio Narita Mohammad Odeh Enric Palle Hannu Parviainen Gabrielle Ross Richard P. Schwarz Gregor Srdoc Chris Stockdale Samuel N. Quinn Ian A. Waite Francis P. Wilkin George Zhou
This is my paper
classification astro-ph.EP
keywords HotJupitersexoplanetcompanionsoccurrenceratetransitsearchTESSmigrationmutualinclinationplanetformation
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

Hot Jupiters were long thought to be loners: a close-in giant planet should eject any smaller neighbors during violent high-eccentricity migration. This paper searches five years of TESS light curves for small transiting planets near roughly 1,850 hot Jupiters, finds six such companions, and corrects for how many would be missed. The authors report an intrinsic occurrence rate of (7.6 +5.5/-3.8)% for nearby companions with periods 0.25–10 days and radii 1–4 Earth radii. Because high-eccentricity migration would destroy such companions, this rate is a strict lower limit on the fraction of hot Jupiters formed by disk migration or in situ assembly. The result matters because it turns a decades-old 'loneliness' argument—previously read as evidence for violent migration—into a quantitative formation-channel constraint.

What carries the argument

The analysis rests on a uniform BLS transit search whose detection probability is calibrated by injecting simulated planets into real TESS light curves and fitting the recovery fraction as a scaled gamma cumulative distribution function of transit signal-to-noise. Each hot Jupiter is treated as a Bernoulli trial; simulated companions drawn from priors on radius, period, and mutual inclination (Rayleigh with scale 1.8°, adopted from Kepler multi-planet systems) determine whether a companion would transit and be detected, yielding an effective sample size. The beta-binomial posterior then converts the six detections and effective sample size into the occurrence rate. The assumed mutual-inclina

What would settle it

A transit-timing-variation survey of a complete, well-characterized sample of TESS hot Jupiters that measures the nearby-companion rate independently of transit geometry—or directly constrains the mutual-inclination distribution—would settle the claim. If such a survey found the true rate is consistent with ~7.6% only under an isotropic (maximally misaligned) inclination prior rather than the Rayleigh prior, the headline rate and its formation-channel interpretation would need revision.

Watch

Extended reading notes

Core claim

Using a uniform box least-squares search of TESS photometry (sectors 1–69) for transiting companions in 1,849 hot Jupiter systems, the paper detects six companions and models each hot Jupiter as a Bernoulli trial. After accounting for transit geometry, pipeline detection efficiency (from injection–recovery), and a ~6% false-positive rate among hot Jupiter candidates, the effective sample size is 87 trials. The resulting beta posterior gives a median occurrence rate of 7.6% with a 90% credible interval +5.5/-3.8 percentage points. The rate depends strongly on the assumed mutual inclination between the hot Jupiter and its companion: it rises to ~37% if companions are isotropically oriented and

Load-bearing premise

The headline 7.6% rate assumes the mutual inclination between a hot Jupiter and its nearby companion follows a narrow Rayleigh distribution with scale 1.8°, borrowed from Kepler's small-planet systems; if real hot Jupiter companions are more misaligned, the same detections imply a rate as high as ~37%.

Editorial extensions

If this is right

  • At least ~8% of hot Jupiters (about one in thirteen) must have formed by dynamically quiet pathways such as disk migration or in situ assembly, since high-eccentricity migration would remove inner companions.
  • Because disk-migration simulations suggest only about one-third of close companions survive, the observed rate is consistent with roughly 20% of hot Jupiters forming by disk migration—making quiet formation several times more common than the raw count implies.
  • The transit-based rate and the TTV-based rate can be reconciled only if hot Jupiters and their nearby companions are mostly mutually aligned, ruling out formation scenarios that produce nearly perpendicular orbits.
  • The apparent excess of grazing transits among the nine known hot Jupiter systems with nearby companions hints at a small systematic misalignment, possibly a dynamical remnant of migration.
  • Hot Jupiters with nearby companions appear to host cold outer companions at a rate similar to the general hot Jupiter population, complicating the simple picture that outer companions trigger high-eccentricity migration.

Reading between the lines

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

  • If the mutual-inclination prior is ever measured directly—say, via combined transit-timing and Doppler data on the six systems—the same detections could yield a rate anywhere from ~7% to ~37%; the headline number is therefore as much a constraint on hot Jupiter–companion alignment as on formation fraction.
  • The grazing-transit signal, if confirmed with a larger sample, would suggest a population of hot Jupiters that experienced mild dynamical stirring—enough to tilt companion orbits slightly but not enough to eject them—fitting a 'gentle' high-eccentricity migration variant rather than pure disk migration.
  • A targeted search for ultra-short-period planets (P < 1 day) with a relaxed radius cut could test whether the companion population extends to very close-in, tidally evolved orbits, sharpening the formation-channel interpretation.
  • Applying the same uniform search to the full TESS dataset beyond sector 69 and to the extended mission should roughly halve the statistical uncertainty, since the current 90% interval is dominated by the small number of detections.
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Editorial analysis

A structured set of objections, weighed in public.

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

Referee Report

4 major / 4 minor

Summary. The paper searches the first five years of TESS data for short-period transiting companions (0.25 d ≤ P < 10 d, 1 ≤ R_p/R⊕ < 4) to a sample of ~1850 hot Jupiters, using a uniform BLS pipeline, manual vetting, and injection-recovery simulations. From six detections, it derives an occurrence rate of (7.6+5.5/−3.8)% using a beta-binomial posterior with an effective sample size corrected for detection efficiency and false-positive rate. The authors argue this is a lower limit on the fraction of hot Jupiters formed by dynamically quiet mechanisms, compare the rate with a TTV-based estimate to argue that hot Jupiters are mostly aligned with their companions, and assemble evidence that these systems may also host cold outer companions. The paper is careful in its search methodology and completeness treatment, but the headline rate depends strongly on the assumed mutual-inclination prior, and the treatment of known missed companions raises a potential bias.

Significance. If the result holds, this is the largest and most complete measurement of the occurrence rate of nearby companions to hot Jupiters, directly constraining hot Jupiter formation pathways: at least ~8% of hot Jupiters must have formed without dynamically disruptive high-eccentricity migration, and the true fraction could be several times larger after accounting for companion survival. The paper's uniform search, explicit detection-efficiency calibration, and sensitivity analysis are valuable contributions. The main strengths are the large sample (1849 systems), the injection-recovery-based completeness characterization, and the transparent exploration of the mutual-inclination dependence (Section 5.5). The principal weakness is that the headline number is conditional on an externally adopted prior (Rayleigh(1.8°)) that is not independently constrained for hot Jupiters; under an isotropic prior the same detections imply 37%. The paper also excludes known real companions from the detection list because the pipeline missed them, which biases the numerator. These issues must be addressed before the result can be taken at face value.

major comments (4)
  1. [§5.1, §5.5, Fig. 7] The headline occurrence rate (7.6+5.5/−3.8)% is conditional on the mutual-inclination prior ψ∼Rayleigh(1.8°) in Eq. (12c). Section 5.5 shows that replacing this with an isotropic Fisher prior (κ→0) changes the effective sample size from n≈89 to n≈17 and the inferred rate to (37+19/−17)%. Because hot Jupiters are the population whose dynamical history is under test, adopting the alignment distribution from Kepler small-planet systems is not a benign assumption. The abstract and §5.4 quote the conditional number as the occurrence rate, while §7 acknowledges the sensitivity. The TTV comparison in §6.2 is explicitly 'not directly comparable' (mass-selected, period ratio 1.5–4), so it does not independently pin down the alignment distribution. Please either marginalize over the mutual-inclination parameter (e.g., with a hyperprior) or present the headline as conditional and move the sensitivi
  2. [§4] WASP-47 e/d and TOI-4468.02 are real nearby companions in sample hosts (WASP-47 b and TOI-4468.01) that were not detected by the pipeline, and the paper states they 'will not count as detections.' This is not a neutral choice. If these planets fall within the search's period (0.25–10 d) and radius (1–4 R⊕) bounds, they should contribute to the numerator s in Eq. (11). Their exclusion biases the occurrence rate low, and the pipeline's failure to recover them is a direct calibration point for the detection efficiency in §3.4 that should be folded into the completeness estimate. Please re-run the analysis with known companions counted as detections (and the missed-known-companion rate used to validate or revise the gamma-CDF), or provide a quantitative justification for their exclusion.
  3. [§3.4, §5.3, Eq. (10)] The gamma-CDF parameters in Eq. (10) are quoted to 8 decimal places with no uncertainties, and the ESS=92.50 in §5.3 is treated as fixed in the beta posterior Eq. (11). The detection efficiency at low S/N is steep and estimated from a finite number of injections; the fit uncertainty should propagate into the final credible interval. As written, the quoted 90% interval is conditional on the efficiency curve being known exactly. Please propagate the injection-recovery uncertainty (e.g., via bootstrap or MCMC over the gamma parameters) or demonstrate quantitatively that it is negligible compared with the binomial uncertainty.
  4. [§6.2, Abstract] The abstract states that comparing with TTV-derived rates 'suggests that hot jupiters are likely mostly aligned with their nearby companions,' but §6.2 acknowledges the TTV rate 'is not directly comparable' because it is mass-selected over period ratio ≈1.5–4 while this search is radius-selected over 0.25–10 d. The two rates can differ substantially even for a fixed intrinsic alignment distribution because of these selection differences. Since this comparison is the only quantitative argument against the isotropic-prior case (37%), the conclusion of alignment is stronger than the evidence. Please either develop a joint likelihood that accounts for the different selection functions or temper the abstract and conclusions accordingly.
minor comments (4)
  1. [Eq. (10)] The parameters α, θ, C are given to eight decimal places and described as 'machine precision.' Report them with meaningful significant figures and uncertainties.
  2. [§2.1] Typo: 'alerted on or before ut 2024 May 30' should be 'UTC 2024 May 30.'
  3. [§2.2, Eq. (2)] The subtraction of N_FP from both numerator and denominator assumes all eliminated targets are true false positives; this is reasonable but the uncertainty in the inferred FPR_HJ is not propagated. A simple sensitivity test would be useful.
  4. [§6.3] The grazing-transit analysis assumes R_p=1 R_J for all four grazing planets because their radii are poorly constrained. Since the conclusion is only a mild hint (Pr≈7.5%), this is acceptable, but the assumption should be stated as a potential source of systematic uncertainty in the p_i calculation.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the occurrence rate is a transparent conditional estimate anchored to external detection-efficiency calibration and an external Kepler mutual-inclination prior.

full rationale

The rate derivation is self-contained and not circular. The numerator is a fixed set of six independently published/confirmed transiting companions from a uniform BLS search (§4). The denominator is built from injection–recovery (§3.3–3.4), which converts empirical transit S/N into a detection-efficiency CDF (Eq. 7, parameters Eq. 10), and a Monte Carlo ESS over stated priors (§5.1–5.3). No fitted quantity is relabeled as a prediction. The main prior that affects the headline number, ψ ~ Rayleigh(1.8°), is adopted from external Kepler multi-transiting system measurements (Fabrycky et al. 2014) via C. Huang et al. (2016), and the paper explicitly explores alternatives in §5.5, reporting n≈17 and a 37% rate under isotropy. The mutual-inclination sensitivity is a stated limitation, not a hidden circular step: the headline is a conditional estimate, not a claim to have measured alignment. Self-citations appear as detections (e.g., TOI-2000 b from Sha et al. 2023) and pipeline tools (e.g., giants by Saunders et al. 2022), but they are not used to justify the rate or to forbid alternatives; external anchors (Zhou et al. 2019 FPR; TTV rate of Wu et al. 2023, with an explicit 'not directly comparable' caveat) provide independent benchmarks. Therefore no circularity beyond normal citation practice is present.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The paper introduces no new physical entities. Its load-bearing choices are calibration inputs (gamma-CDF parameters from injection-recovery), the mutual-inclination prior, and the population priors defining the companion sample. These are external or fitted modeling choices, not derived from the target result.

free parameters (6)
  • Gamma CDF detection-efficiency parameters α, θ, C = α=9.21719769, θ=1.24222051, C=0.94609528
    Fit to injection-recovery detection fraction versus theoretical transit S/N (§3.4, Eq. 10); these parameters map S/N to detection efficiency and directly set the effective sample size in §5.3.
  • Mutual inclination prior scale σ = 1.8° (Rayleigh)
    Chosen from Kepler multi-transiting systems (Fabrycky et al. 2014) via Huang et al. (2016) in §5.1, Eq. (12c). The headline rate is conditional on this: an isotropic prior gives 37% instead of 7.6% (§5.5).
  • Companion radius prior bounds = U(1,4) R⊕
    Defines the companion population counted in the occurrence rate (§5.1, Eq. 12a). Changing this range changes the completeness calculation and the meaning of the quoted rate.
  • Companion period prior bounds = U(0.25,10) d
    Defines 'nearby' in the occurrence rate (§5.1, Eq. 12b). The lower bound excludes ultra-short-period planets, which are discussed as future work.
  • FPR_Zhou = 10/31 ≈ 0.32
    External false-positive-rate estimate from Zhou et al. (2019) used in Eq. (2) to correct the sample. No uncertainty is propagated into the effective sample size.
  • Assumed radius of grazing companions = 1 R_J
    Used in §6.3, Eq. (18) to estimate grazing probabilities for the four grazing hot Jupiters; their radii are poorly known, so this drives the p=0.19 and the 7.5% 'hint'.
assumptions (5)
  • domain assumption High-eccentricity migration disrupts any nearby companion
    The interpretation of the occurrence rate as a lower limit on quiescent formation (§1, §6.5) depends on HEM being dynamically destructive. If companions can survive HEM, the lower-limit statement weakens.
  • ad hoc to paper Injection-recovery auto-match detection efficiency equals manual-vetting detection efficiency
    §3.3 declares recovery by ephemeris matching (Eq. 4), while real TCEs are manually vetted (§3.2). The paper does not test whether these two procedures yield the same completeness.
  • domain assumption The FPR correction formula (Eq. 2) applies to the TOI hot Jupiter sample
    An FPR estimate from 31 early TESS TOIs is extrapolated to 2684 targets after subtracting eliminated candidates; no uncertainty is propagated into n.
  • domain assumption The beta-binomial model with effective sample size n is valid for heterogeneous detection efficiencies
    Systems with very different completeness are collapsed into a single ESS (§5.3); the true likelihood is a product of different Bernoulli probabilities, so the effective-sample-size approximation is not exact.
  • standard math Stellar parameters from SED fitting and circular orbits are accurate enough for completeness calculations
    Derived M* and R* (§2.3) feed a/R* and transit S/N for every simulated companion; individual stellar parameter uncertainties are not propagated into ESS.

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Cite this review

Pith. "Pith review of The Occurrence Rate of Nearby Planetary Companions to Hot Jupiters." pith.science (2026). https://pith.science/paper/FEATIUEW

@misc{pith2026260113302,
  author       = {Pith},
  title        = {Pith review of: The Occurrence Rate of Nearby Planetary Companions to Hot Jupiters},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/FEATIUEW}},
  note         = {Machine review of arXiv:2601.13302}
}
abstract

Of the > 500 confirmed transiting hot jupiters and approximately 2000 additional candidates today, only ten are known to have nearby companion planets. The survival of nearby companions means that these hot jupiters cannot have migrated to their present location via dynamically disruptive high-eccentricity migration but instead have undergone disk migration or formed in situ. The occurrence rate for these nearby companions, therefore, constrains the relative efficiency of different hot jupiter formation pathways. Here, we perform a uniform box least-squares search for nearby transiting companions to hot jupiters in the first five years of TESS data. Accounting for observational completeness and detection efficiency, we arrive at an occurrence rate of $(7.6^{+5.5}_{-3.8})\%$, which is a lower limit on the fraction of hot jupiters that underwent disk migration or in situ formation. Comparing this rate with that derived from transit-timing variation searches suggests that hot jupiters are likely mostly aligned with their nearby companions, but their apparently higher incidence of grazing transits may point to a slight preferential misalignment. We also synthesize evidence that hot jupiters with nearby companions may have cold companions at a rate similar to that of other hot jupiters. Comprehensive transit, radial velocity, and stellar obliquity measurements in hot jupiter systems with nearby companions will be necessary to fully account for the relative prevalence of proposed hot jupiter formation pathways.

Figures

Figures reproduced from arXiv: 2601.13302 by the authors.

Figure 1
Figure 1. The distribution of the host stars of the selected hot jupiters. Left: The histogram of stellar mass. Right: The color–magnitude diagram. mental stellar parameters modeled by the MESA Isochrones and Stellar Tracks (MIST; A. Dotter 2016;J. Choi et al. 2016), using the associated correction tables to convert bolometric to broadband photometric magnitudes. To better reflect sys￾tematic and model uncertainty, we inflate… view at source ↗
Figure 2
Figure 2. by J. L. Coughlin et al. (2014), confirms that the chosen significance levels in Equation (4) capture the mode of true ephemeris matches in the upper right while excluding the 28 Since the injection–recovery simulation is only used to derive an em￾pirical relationship between theoretical transit S/N and pipeline detection efficiency, the exact choice of stellar parameters here has no bearing on the final occurrence … view at source ↗
Figure 3
Figure 3. Detection fraction as a function of transit S/N. The blue marks are the recovery fraction of injected planets within each S/N bin with error bars representing the Agresti–Coull confidence inter￾val of binomial proportion, and the orange curve is a scaled gamma distribution CDF. The detection fraction asymptotically approaches ≈ 0.95 as the transit S/N → ∞. In order to relate the theoretical S/N to the actual detec￾t… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Transiting planetary systems hosting nearby planetary companions to hot jupiters (𝑃 < 10 d). Non-transiting planets are omitted. The leftmost circle in each row represent the host star, with the mark’s size indicating the stellar radius and fill color the stellar effec…
Figure 5
Figure 5. Figure 5: Overall observational completeness of simulated nearby companions to hot jupiters in bins of the orbital periods and planet radii of the companions (subsection 5.3), expressed as percentages. The observational completeness takes account of both transit probability and …
Figure 6
Figure 6. Figure 6: Posterior distribution of the occurrence rate of nearby companions (0.25 d ≤ 𝑃 < 10 d, 1 ≤ 𝑅p/R⊕ < 4) to hot jupiters. The 90% credible interval about the median is (7.6 +5.5 −3.8 )%, with the median indicated by a solid vertical line and the interval shaded. 3. period…
Figure 7
Figure 7. Figure 7: Occurrence rate of nearby companions (0.25 d ≤ 𝑃 < 10 d, 1 ≤ 𝑅p/R⊕ < 4) to hot jupiters as a function of their orbital alignment, parameterized as the scale parameter 𝜅 of a Fisher distribution prior on their mutual inclination. The posterior of each occurrence rate is…

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Reference graph

Works this paper leans on

71 extracted references · 9 canonical work pages · cited by 5 Pith papers

  1. [1]

    1998, The American Statistician, 52, 119, doi: 10.2307/2685469 Astropy Collaboration, Robitaille, T

    Agresti, A., & Coull, B. 1998, The American Statistician, 52, 119, doi: 10.2307/2685469 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., Sip˝ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astropy Collaboration, Price-Whe...

    doi:10.2307/2685469 1998

  2. [2]

    H., & Laughlin, G

    Batygin, K., Bodenheimer, P. H., & Laughlin, G. P. 2016, ApJ, 829, 114, doi: 10.3847/0004-637X/829/2/114

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

  3. [3]

    C., Vanderburg, A., Adams, F

    Becker, J. C., Vanderburg, A., Adams, F. C., Khain, T., & Bryan, M. 2017, AJ, 154, 230, doi: 10.3847/1538-3881/aa9176

    doi:10.3847/1538-3881/aa9176 2017

  4. [4]

    Schwengeler, H. M. 2015, ApJL, 812, L18, doi: 10.1088/2041-8205/812/2/L18

    doi:10.1088/2041-8205/812/2/l18 2015

  5. [5]

    2022, MNRAS, 516, 75, doi: 10.1093/mnras/stac2179

    Beleznay, M., & Kunimoto, M. 2022, MNRAS, 516, 75, doi: 10.1093/mnras/stac2179

    doi:10.1093/mnras/stac2179 2022

  6. [6]

    2024, A&A, 689, A52, doi: 10.1051/0004-6361/202450974

    Borsato, L., Degen, D., Leleu, A., et al. 2024, A&A, 689, A52, doi: 10.1051/0004-6361/202450974

    doi:10.1051/0004-6361/202450974 2024

  7. [7]

    M., & Bayliss, D

    Bryant, E. M., & Bayliss, D. 2022, AJ, 163, 197, doi: 10.3847/1538-3881/ac58ff

    doi:10.3847/1538-3881/ac58ff 2022

  8. [8]

    J., Christiansen, J

    Burke, C. J., Christiansen, J. L., Mullally, F., et al. 2015, ApJ, 809, 8, doi: 10.1088/0004-637X/809/1/8 Ca˜nas, C. I., Wang, S., Mahadevan, S., et al. 2019, ApJL, 870, L17, doi: 10.3847/2041-8213/aafa1e

    doi:10.1088/0004-637x/809/1/8 2015

Show all 71 references
  1. [9]

    2016, ApJ, 823, 102, doi: 10.3847/0004-637X/823/2/102

    Choi, J., Dotter, A., Conroy, C., et al. 2016, ApJ, 823, 102, doi: 10.3847/0004-637X/823/2/102

    2016 doi

  2. [10]

    L., Clarke, B

    Christiansen, J. L., Clarke, B. D., Burke, C. J., et al. 2015, ApJ, 810, 95, doi: 10.1088/0004-637X/810/2/95

    2015 doi

  3. [11]

    L., Thompson, S

    Coughlin, J. L., Thompson, S. E., Bryson, S. T., et al. 2014, AJ, 147, 119, doi: 10.1088/0004-6256/147/5/119

    2014 doi

  4. [12]

    2016, ApJS, 222, 8, doi: 10.3847/0067-0049/222/1/8

    Dotter, A. 2016, ApJS, 222, 8, doi: 10.3847/0067-0049/222/1/8

    2016 doi

  5. [13]

    C., & Winn, J

    Fabrycky, D. C., & Winn, J. N. 2009, ApJ, 696, 1230, doi: 10.1088/0004-637X/696/2/1230

    2009 doi

  6. [14]

    C., Lissauer, J

    Fabrycky, D. C., Lissauer, J. J., Ragozzine, D., et al. 2014, ApJ, 790, 146, doi: 10.1088/0004-637X/790/2/146

    2014 doi

  7. [15]

    M., Burke, C

    Fausnaugh, M. M., Burke, C. J., Ricker, G. R., & Vanderspek, R. 2020, Research Notes of the American Astronomical Society, 4, 251, doi: 10.3847/2515-5172/abd63a

    2020 doi

  8. [16]

    J., et al

    Grieves, N., Bouchy, F., Armstrong, D. J., et al. 2025, A&A, 693, A144, doi: 10.1051/0004-6361/202348177

    2025 doi

  9. [17]

    M., Seager, S., Huang, C

    Guerrero, N. M., Seager, S., Huang, C. X., et al. 2021, ApJS, 254, 39, doi: 10.3847/1538-4365/abefe1 The Occurrence Rate of Nearby Planetary Companions to Hot Jupiter15

    2021 doi

  10. [18]

    D., & Bakos, G

    Hartman, J. D., & Bakos, G. A. 2016, A&C, 17, 1, doi: 10.1016/j.ascom.2016.05.006

    2016 doi

  11. [19]

    2024, MNRAS, 530, 3934, doi: 10.1093/mnras/stae1076

    He, Y., Wu, D.-H., & Jin, S. 2024, MNRAS, 530, 3934, doi: 10.1093/mnras/stae1076

    2024 doi

  12. [20]

    2022, cuvarbase: fast period finding utilities for GPUs,, Astrophysics Source Code Library, record ascl:2210.030

    Hoffman, J. 2022, cuvarbase: fast period finding utilities for GPUs,, Astrophysics Source Code Library, record ascl:2210.030

    2022

  13. [21]

    J., Col´on, K

    Hord, B. J., Col´on, K. D., Kostov, V., et al. 2021, AJ, 162, 263, doi: 10.3847/1538-3881/ac2602

    2021 doi

  14. [22]

    J., Col´on, K

    Hord, B. J., Col´on, K. D., Berger, T. A., et al. 2022, AJ, 164, 13, doi: 10.3847/1538-3881/ac6f57

    2022 doi

  15. [23]

    Huang, C., Wu, Y., & Triaud, A. H. M. J. 2016, ApJ, 825, 98, doi: 10.3847/0004-637X/825/2/98

    2016 doi

  16. [24]

    Huang, C. X. 2020, TESS Lightcurves From The MIT Quick-Look

    2020

  17. [25]

    Pipeline, STScI/MAST, doi: 10.17909/T9-R086-E880

    doi

  18. [26]

    X., Quinn, S

    Huang, C. X., Quinn, S. N., Vanderburg, A., et al. 2020a, ApJL, 892, L7, doi: 10.3847/2041-8213/ab7302

    doi

  19. [27]

    X., Vanderburg, A., P´al, A., et al

    Huang, C. X., Vanderburg, A., P´al, A., et al. 2020b, Research Notes of the American Astronomical Society, 4, 204, doi: 10.3847/2515-5172/abca2e

    doi

  20. [28]

    X., Vanderburg, A., P´al, A., et al

    Huang, C. X., Vanderburg, A., P´al, A., et al. 2020c, Research Notes of the American Astronomical Society, 4, 206, doi: 10.3847/2515-5172/abca2d

    doi

  21. [29]

    2024, ApJL, 971, L28, doi: 10.3847/2041-8213/ad65fd Kov´acs, G., Zucker, S., & Mazeh, T

    Korth, J., Chaturvedi, P., Parviainen, H., et al. 2024, ApJL, 971, L28, doi: 10.3847/2041-8213/ad65fd Kov´acs, G., Zucker, S., & Mazeh, T. 2002, A&A, 391, 369, doi: 10.1051/0004-6361:20020802

    2024 doi

  22. [30]

    2023, Research Notes of the American Astronomical Society, 7, 28, doi: 10.3847/2515-5172/acbc13

    Kunimoto, M., Tey, E., Fong, W., et al. 2023, Research Notes of the American Astronomical Society, 7, 28, doi: 10.3847/2515-5172/acbc13

    2023 doi

  23. [31]

    2022a, Research Notes of the American Astronomical Society, 6, 235, doi: 10.3847/2515-5172/aca157

    Kunimoto, M., Tey, E., Fong, W., Hesse, K., & Shporer, A. 2022a, Research Notes of the American Astronomical Society, 6, 235, doi: 10.3847/2515-5172/aca157

    doi

  24. [32]

    2022b, Research Notes of the American Astronomical Society, 6, 236, doi: 10.3847/2515-5172/aca158

    Kunimoto, M., Tey, E., Fong, W., et al. 2022b, Research Notes of the American Astronomical Society, 6, 236, doi: 10.3847/2515-5172/aca158

    doi

  25. [33]

    2021, Research Notes of the American Astronomical Society, 5, 234, doi: 10.3847/2515-5172/ac2ef0

    Kunimoto, M., Huang, C., Tey, E., et al. 2021, Research Notes of the American Astronomical Society, 5, 234, doi: 10.3847/2515-5172/ac2ef0

    2021 doi

  26. [34]

    W., Rowe, J

    Latham, D. W., Rowe, J. F., Quinn, S. N., et al. 2011, ApJL, 732, L24, doi: 10.1088/2041-8205/732/2/L24

    2011 doi

  27. [35]

    Lin, D. N. C., Bodenheimer, P., & Richardson, D. C. 1996, Nature, 380, 606, doi: 10.1038/380606a0

    1996 doi

  28. [36]

    2023, MNRAS, 525, L43, doi: 10.1093/mnrasl/slad078

    Maciejewski, G., Golonka, J., Loboda, W., et al. 2023, MNRAS, 525, L43, doi: 10.1093/mnrasl/slad078

    2023 doi

  29. [37]

    1995, Nature, 378, 355, doi: 10.1038/378355a0

    Mayor, M., & Queloz, D. 1995, Nature, 378, 355, doi: 10.1038/378355a0

    1995 doi

  30. [38]

    J., Montet, B

    McKee, B. J., Montet, B. T., Yee, S. W., et al. 2025, ApJ, 981, 106, doi: 10.3847/1538-4357/adac63

    2025 doi

  31. [39]

    McLaughlin, D. B. 1924, ApJ, 60, 22, doi: 10.1086/142826

    1924 doi

  32. [40]

    F., Sasselov, D., et al

    Miller-Ricci, E., Rowe, J. F., Sasselov, D., et al. 2008, ApJ, 682, 593, doi: 10.1086/587634

    2008 doi

  33. [41]

    Morton, T. D. 2015, isochrones: Stellar model grid package,, Astrophysics Source Code Library, record ascl:1503.010

    2015

  34. [42]

    R., et al

    Neveu-VanMalle, M., Queloz, D., Anderson, D. R., et al. 2016, A&A, 586, A93, doi: 10.1051/0004-6361/201526965 NExScI. 2022, Exoplanet Follow-up Observing Program Web

    2016 doi

  35. [43]

    Service, IPAC, doi: 10.26134/EXOFOP5

    doi

  36. [44]

    B., Hubickyj, O., Bodenheimer, P., et al

    Pollack, J. B., Hubickyj, O., Bodenheimer, P., et al. 1996, Icarus, 124, 62, doi: 10.1006/icar.1996.0190

    1996

  37. [45]

    A., & Ford, E

    Rasio, F. A., & Ford, E. B. 1996, Science, 274, 954, doi: 10.1126/science.274.5289.954

    1996 doi

  38. [46]

    E., Quinn, S

    Rodriguez, J. E., Quinn, S. N., Zhou, G., et al. 2021, AJ, 161, 194, doi: 10.3847/1538-3881/abe38a

    2021 doi

  39. [47]

    E., Quinn, S

    Rodriguez, J. E., Quinn, S. N., Vanderburg, A., et al. 2023, MNRAS, 521, 2765, doi: 10.1093/mnras/stad595

    2023 doi

  40. [48]

    Rossiter, R. A. 1924, ApJ, 60, 15, doi: 10.1086/142825

    1924 doi

  41. [49]

    K., Huber, D., et al

    Saunders, N., Grunblatt, S. K., Huber, D., et al. 2022, AJ, 163, 53, doi: 10.3847/1538-3881/ac38a1

    2022 doi

  42. [50]

    E., Bieryla, A., et al

    Schulte, J., Rodriguez, J. E., Bieryla, A., et al. 2024, AJ, 168, 32, doi: 10.3847/1538-3881/ad4a57

    2024 doi

  43. [51]

    M., Huang, C

    Sha, L., Vanderburg, A. M., Huang, C. X., et al. 2023, MNRAS, 524, 1113, doi: 10.1093/mnras/stad1666

    2023 doi

  44. [52]

    J., & Vanderburg, A

    Shallue, C. J., & Vanderburg, A. 2018, AJ, 155, 94, doi: 10.3847/1538-3881/aa9e09

    2018 doi

  45. [53]

    G., Oelkers, R

    Stassun, K. G., Oelkers, R. J., Pepper, J., et al. 2018, AJ, 156, 102, doi: 10.3847/1538-3881/aad050

    2018 doi

  46. [54]

    G., Oelkers, R

    Stassun, K. G., Oelkers, R. J., Paegert, M., et al. 2019, AJ, 158, 138, doi: 10.3847/1538-3881/ab3467

    2019 doi

  47. [55]

    H., Ragozzine, D., Fabrycky, D

    Steffen, J. H., Ragozzine, D., Fabrycky, D. C., et al. 2012, Proceedings of the National Academy of Science, 109, 7982, doi: 10.1073/pnas.1120970109

    2012 doi

  48. [57]

    E., Coughlin, J

    Thompson, S. E., Coughlin, J. L., Hoffman, K., et al. 2018b, ApJS, 235, 38, doi: 10.3847/1538-4365/aab4f9

    doi

  49. [58]

    Vanderburg, A., & Johnson, J. A. 2014, PASP, 126, 948, doi: 10.1086/678764

    2014 doi

  50. [59]

    W., Buchhave, L

    Vanderburg, A., Latham, D. W., Buchhave, L. A., et al. 2016, ApJS, 222, 14, doi: 10.3847/0067-0049/222/1/14

    2016 doi

  51. [60]

    X., Rodriguez, J

    Vanderburg, A., Huang, C. X., Rodriguez, J. E., et al. 2019, ApJL, 881, L19, doi: 10.3847/2041-8213/ab322d

    2019 doi

  52. [61]

    2025, ApJL, 982, L15, doi: 10.3847/2041-8213/adbae6

    Wang, S., Pan, M., Dong, Y., Zhao, G., & Ji, J. 2025, ApJL, 982, L15, doi: 10.3847/2041-8213/adbae6

    2025 doi

  53. [62]

    T., Marcy, G

    Wright, J. T., Marcy, G. W., Howard, A. W., et al. 2012, ApJ, 753, 160, doi: 10.1088/0004-637X/753/2/160

    2012 doi

  54. [63]

    2023, AJ, 166, 267, doi: 10.3847/1538-3881/ad09b0

    Wu, D.-H., & He, Y. 2023, AJ, 166, 267, doi: 10.3847/1538-3881/ad09b0

    2023 doi

  55. [64]

    2023, AJ, 165, 171, doi: 10.3847/1538-3881/acbf3f 16Sha et al

    Wu, D.-H., Rice, M., & Wang, S. 2023, AJ, 165, 171, doi: 10.3847/1538-3881/acbf3f 16Sha et al

    2023 doi

  56. [65]

    W., & Winn, J

    Yee, S. W., & Winn, J. N. 2023, ApJL, 949, L21, doi: 10.3847/2041-8213/acd552

    2023 doi

  57. [66]

    W., Winn, J

    Yee, S. W., Winn, J. N., & Hartman, J. D. 2021, AJ, 162, 240, doi: 10.3847/1538-3881/ac2958

    2021 doi

  58. [67]

    W., Winn, J

    Yee, S. W., Winn, J. N., Hartman, J. D., et al. 2022, AJ, 164, 70, doi: 10.3847/1538-3881/ac73ff

    2022 doi

  59. [68]

    W., Winn, J

    Yee, S. W., Winn, J. N., Hartman, J. D., et al. 2023, ApJS, 265, 1, doi: 10.3847/1538-4365/aca286

    2023 doi

  60. [69]

    2024, ApJS, 275, 32, doi: 10.3847/1538-4365/ad89a6

    Zhang, Z., Wang, W., Ma, X., et al. 2024, ApJS, 275, 32, doi: 10.3847/1538-4365/ad89a6

    2024 doi

  61. [70]

    X., Bakos, G

    Zhou, G., Huang, C. X., Bakos, G. ´A., et al. 2019, AJ, 158, 141, doi: 10.3847/1538-3881/ab36b5

    2019 doi

  62. [71]

    2018, Research Notes of the American Astronomical Society, 2, 160, doi: 10.3847/2515-5172/aade53

    Zhu, W., Dai, F., & Masuda, K. 2018, Research Notes of the American Astronomical Society, 2, 160, doi: 10.3847/2515-5172/aade53

    2018 doi

  63. [72]

    K., & Howard, A

    Zink, J. K., & Howard, A. W. 2023, ApJL, 956, L29, doi: 10.3847/2041-8213/acfdab All Authors and Affiliations Lizhou Sha ,1 Andrew M. V anderburg ,2 Chelsea X. Huang ,3 Samuel Christian ,4 Nicholas Saunders ,5, 6 Khalid Barkaoui ,7, 8, 9 Alexander Belinski ,10, 11 Serge Berger...

    2023 doi

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