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TESS planets in known radial velocity cold Jupiter systems: Hot super Earth occurrence is enhanced by cold Jupiters

T0 review · 3 major / 5 minor · reviewed 2026-08-03 · deepseek-v4-flash

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Pith's one-line read Stars that host a distant Jupiter-mass planet are about eight times more likely to also host a close-in super-Earth, according to a transit survey of 132 known cold-Jupiter systems.

desk verdict The core enhancement factor (~8x) is credible and novel, but the 87% system fraction is an upper limit built on an admitted unknown multiplicity, and the abstract/full-text numbers disagree. read the letter →

arxiv 2602.11017 v2 pith:ZGS3HPMS submitted 2026-02-11 astro-ph.EP

Quanyi Liu , Wei Zhu , Tianjun Gan , Fei Dai This is my paper
classification astro-ph.EP
keywords coldJupitershotsuper-EarthsoccurrenceratesTESSradialvelocityplanetstransitsearchmutualinclinationsplanetformation
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

This paper attempts to measure, directly, how often a star that hosts a distant Jupiter-mass planet (a cold Jupiter) also hosts a close-in super-Earth. Using TESS transit data for 132 Sun-like stars with known radial-velocity cold Jupiters, the authors find five transiting hot super-Earths (planets of 1–4 Earth radii with periods under 10 days) around four stars. After correcting for geometric transit probability and detection sensitivity, they report that cold Jupiters enhance the occurrence rate of hot super-Earths by a factor of 8.1 (68% interval +4.3/−3.2), excluding 'no enhancement' at 99.9% confidence, and that about 87–91% of cold-Jupiter systems host at least one hot super-Earth. If correct, this converts a previously Bayesian conjecture—that nearly all cold-Jupiter hosts also harbor inner super-Earths—into a direct observational measurement, sharpening constraints on planet-formation and system-architecture models.

What carries the argument

The load-bearing quantity is the enhancement factor f = η(HSE|CJ)/η(HSE), estimated from the ratio of the five observed transiting hot super-Earths to N̄ = 0.58, the expected number under the null hypothesis. Equation (4) builds N̄ by summing over orbital-period and radius bins the field occurrence rate times the geometric transit probability p_tr = 0.9 R*/a and the pipeline detection efficiency, the latter measured by injecting 200 synthetic transits around each star and recovering them with a BLS search. The posterior on f is a Gamma distribution arising from a Poisson likelihood for the detection count. The geometric transit probability, which assumes isotropic inner-planet inclinations,

What would settle it

Measure the mutual inclinations between hot super-Earths and their outer cold Jupiters in a statistically meaningful sample—using transit-duration ratios, Rossiter–McLaughlin observations, or astrometry. If typical mutual inclinations are small (≲5°) and RV-selected cold Jupiters are preferentially edge-on, the isotropic-transit assumption fails and the enhancement factor is overestimated; if mutual inclinations are large, the enhancement would be even larger. A pipeline-independent check is to run the same TESS search on a metallicity- and brightness-matched sample of field stars without cold

Watch

Extended reading notes

Core claim

On the paper's own terms, the central discovery is that the conditional occurrence of hot super-Earths in cold-Jupiter systems, η(HSE|CJ), exceeds the field rate η(HSE) by an order of magnitude. The authors compute the expected number of transiting hot super-Earths in their 132-star sample under the null hypothesis of no correlation, N̄ = 0.58, using Kepler-based field occurrence rates and per-star transit and detection efficiencies determined from injection-recovery simulations. With five planets observed, the Poisson-based posterior gives the enhancement factor f = 8.1^{+4.3}_{-3.2}, and P(f ≤ 1) = 0.1%. Dividing the implied conditional occurrence rate by the sample's average multiplicity

Load-bearing premise

The assumption that the inner super-Earths' orbital inclinations are distributed isotropically, so that p_tr = 0.9 R*/a applies unconditionally, is the load-bearing premise: if inner planets preferentially share the cold Jupiter's orbital plane, the assumed transit probability is too low, N̄ is underestimated, and the measured 8.1× enhancement would shrink.

Editorial extensions

If this is right

  • Occurrence-rate models and planet-formation simulations must reproduce an order-of-magnitude enhancement of close-in super-Earths when an outer giant is present, rather than treating the two populations as independent.
  • RV-only surveys systematically miss most inner super-Earths in cold-Jupiter systems; combined transit+RV samples are necessary to measure P(SE|CJ), which explains part of the scatter among earlier correlation studies.
  • The large mutual inclinations seen in the two super-Jupiter systems in this sample show that the inner and outer planets need not be coplanar, so the enhancement is a genuine occurrence effect rather than purely a geometric alignment artifact—though the size of the effect still depends on the inclination distribution.
  • Targeted searches for transits around known RV giant hosts can be an efficient way to build a statistical sample of multi-planet architectures, since each detected inner planet is a nearly guaranteed co-existing system.

Reading between the lines

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

  • If the isotropic-inclination assumption is wrong and inner super-Earths preferentially align with the cold Jupiter's orbital plane (while RV detection favors edge-on giants), the true transit probability is higher than assumed; N̄ would rise and the 8.1× enhancement would shrink. Mutual-inclination measurements could separate a genuine occurrence boost from an architecture-alignment effect.
  • The abstract reports 91% for P(HSE|CJ) while Section 5 and the summary give 87%; the derivation in Eq. (8) uses the sample's average multiplicity, making 87% the better documented figure. The mismatch is not reconciled in the text.
  • The detection-efficiency map rests on injection-recovery without visual validation of recovered signals; the authors argue the sample is clean, but any residual false-positive rate would bias N̄ and hence f. An independent re-analysis of the same 132 light curves with a different pipeline would test the robustness.
  • The apparent enhancement in the metal-poor subsample (1 of 43 systems) suggests the correlation may not be purely metallicity-driven; extending this TESS-based approach to a larger sample of giants found astrometrically at low metallicity would test whether the boost persists.
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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

3 major / 5 minor

Summary. This paper constructs a sample of 132 Sun-like stars with RV-detected cold Jupiters, performs a uniform TESS transit search for inner hot super-Earths (1–4 R⊕, P<10 d), and validates two candidates around HD 50554. After injection-recovery completeness and geometric transit probabilities, 5 detected HSEs are compared with an expected field background of Nbar=0.58 from Kepler occurrence rates. A Poisson/Gamma model gives an enhancement factor f=8.1^{+4.3}_{-3.2} with P(f≤1)=0.1%. Dividing the conditional occurrence rate η=1.09 by an assumed multiplicity 5/4 yields a system fraction P(HSE|CJ)≈87%. The paper also explores metallicity and mass sub-samples.

Significance. If correct, this is a direct, well-defined measurement of the inverted conditional probability P(SE|CJ), strongly supporting a positive SE–CJ correlation and providing a useful constraint on formation and dynamical-evolution models. Strengths include the clean RV-selected CJ sample with explicit exclusion criteria, a uniform TESS BLS search with injection-recovery completeness, careful validation of the HD 50554 candidates using photometry, RV, and Gaia astrometry, and transparent Poisson statistics with robustness checks against two independent field occurrence maps and alternative CJ definitions. The core enhancement-factor result is largely independent of the multiplicity step; the system-fraction claim is not.

major comments (3)
  1. [§5, Eq. (8) and §6.1] The system fraction P(HSE|CJ)≈87% is obtained by dividing η(HSE|CJ)=1.09 by the raw observed multiplicity 5/4=1.25. The text admits the average multiplicity of hot super-Earths is not known. Because 5/4 counts only transiting HSEs actually detected and ignores non-transiting companions and detection incompleteness, it is a lower bound on the true mean multiplicity among HSE hosts. Since P(HSE|CJ)=η/m, using a lower bound for m yields an upper bound on the system fraction: m=2 gives about 55%, and the value ~3 cited in the text gives about 36%. The 87% claim, highlighted in the abstract and §6.1, is therefore not supported as an estimate. Please provide a completeness-corrected multiplicity estimate or explicitly present the result as a sensitivity/upper bound. The supplied abstract's 91% versus §5's 87% must also be reconciled.
  2. [§3.2, Eq. (2)] The geometric transit probability assumes isotropic inner HSE inclinations. If inner orbits are preferentially aligned with the RV-detected CJ, and if RV detection favors sin i≈1, the effective p_tr is larger than 0.9 R*/a, raising Nbar in Eq. (4) and lowering f. The text acknowledges this possibility and cites large mutual inclinations in π Men and HD 50554, but it does not quantify the effect. Please add a numerical sensitivity test (e.g., a mutual-inclination distribution or a uniform upward factor on p_tr) and propagate the resulting change into f and the formal significance.
  3. [§5, Eq. (6)] The posterior for f treats Nbar=0.58 as fixed. Nbar inherits uncertainty from the external Kepler occurrence map and from the injection-recovery efficiency map, yet the quoted 68% interval and the p<0.001 statement reflect only Poisson counting noise in N=5. Please marginalize over the uncertainty in Nbar, or at least show how P(f≤1) changes under conservative upward revisions of Nbar (e.g., the 1.3× metallicity correction and a factor-of-two alignment correction). This is needed to support the formal 99.9% claim.
minor comments (5)
  1. [Abstract/full text] The opening abstract block reports f=6.5^{+3.1}_{-2.3} and a 91% system fraction, while the full-text abstract, §5, and §6.1 report f=8.1^{+4.3}_{-3.2} and 87%. These headline numbers must be aligned before publication.
  2. [Eq. (6)] The Gamma posterior shape parameter is written as N_NSE+1; this should be N_HSE+1.
  3. [§6.1] The summary states 'radii of 1.3M⊕ and 1.4M⊕'; the units should be R⊕.
  4. [§6.2.3] The mass quoted for π Men b, ≈14 M_J, appears inconsistent with the inclination of ≈54° cited in the same paragraph and with published RV minimum masses. Please verify the value and source.
  5. [Figure 3 / Table 3] The right-panel colorbar label 'Pdet Ptr' should read 'Pdet × Ptr'. In Table 3, the format of the mass upper limits (Mp <5.3 and <10.4 M⊕) is unclear and should be clarified.

Circularity Check

0 steps flagged · score 1.0 of 10

No significant circularity: the enhancement factor is anchored to external Kepler occurrence rates; the 87% system fraction is assumption-sensitive but not a circular fit.

full rationale

The central enhancement claim is anchored externally, not to the paper's own inputs. The null expectation in Eq. (4) is computed using 'the HSE occurrence rate distribution given in Figure 3 of Zhu & Dong (2021), which was derived from the Kepler sample,' and the paper cross-checks with 'the HSE occurrence rates from Figure 6 of Petigura et al. (2018).' Neither rate is fitted to the 132-system RV-CJ sample, so the Poisson comparison of N_HSE=5 against Nbar=0.58 is an independent statistical test. Although Zhu & Dong (2021) shares an author with this paper, it is an externally derived Kepler occurrence rate and therefore counts as independent evidence under the review rules; the self-overlap is not load-bearing. The secondary 87% system fraction in Eq. (8) does use an in-sample value — 'Although the average multiplicity of hot super Earths is not known, we can take the observed average multiplicity of our sample (5/4 = 1.25) as an appropriate estimate' — but this is an explicitly stated sensitivity, not a hidden calibration: the relation P(HSE|CJ)=eta/m is displayed, and m is not fitted to P itself. Changing m changes the system fraction without changing the measured enhancement factor f, so the paper's main result does not reduce to this assumption. The isotropic-inclination assumption in Eq. (2) could bias f if inner HSEs are preferentially aligned with the CJ orbits, but that is a physical modeling assumption, not a definitional/self-citational reduction. The abstract/full-text 91% versus 87% discrepancy is an internal consistency issue, not circularity. Overall, no derivation step is equivalent to its inputs by construction, and the paper is self-contained against external Kepler benchmarks; score is therefore low.

Assumptions & free parameters 3 free parameters · 6 assumptions · 0 invented entities

No new physical entities are introduced. The central claim depends on external empirical inputs (Kepler field rates), a geometric inclination assumption, and an in-sample multiplicity estimate.

free parameters (3)
  • Kepler field HSE occurrence map η(HSE) = 0.135 (Zhu & Dong 2021); alternative 0.115 (Petigura et al. 2018)
    Used in Eq. (4) to compute the expected background count N_bar=0.58; changing this map changes f from 8.1 to 10.7.
  • Metallicity dependence β = 0.6
    Adopted from Petigura et al. 2018 to scale HSE occurrence by ~1.3 for Δ[Fe/H]≈0.2; not derived in this paper.
  • Average HSE multiplicity in CJ systems = 1.25 (5/4)
    Observed multiplicity of the 4 detected systems; used in §5/Eq. (8) to convert η(HSE|CJ) to P(HSE|CJ)≈87%. A field-like multiplicity of ~3 would give a much lower system fraction.
assumptions (6)
  • domain assumption Kepler field HSE occurrence rate applies to the bright TESS RV-CJ sample after a small metallicity correction.
    Eq. (4) uses η from Zhu & Dong (2021)/Petigura et al. (2018); §5 discusses metallicity as the main suspected bias, but other population differences are not tested.
  • domain assumption Orbital inclinations of inner HSEs are isotropically distributed and independent of the RV-selected cold Jupiter inclination.
    Eq. (2) p_tr = 0.9 R*/a; §3.2 and §6.2.3 acknowledge mutual inclinations may be large but do not quantify the effect on N_bar.
  • domain assumption The detected transit candidates are genuine planets.
    Four are previously confirmed; TOI-6965.01 is validated using TESS photometry, RV upper limits, odd-even checks, and Gaia astrometry in §4, but it remains a statistically validated candidate rather than a mass-measured planet.
  • standard math The Poisson likelihood with a flat prior in Eq. (6) adequately describes the counting statistics.
    Standard treatment for small counts; the main uncertainty is not the counting model but the external inputs to N_bar.
  • ad hoc to paper The HSE multiplicity of CJ systems can be estimated from the detected sample's 5/4 ratio.
    §5, Eq. (8): with only 4 systems this is an in-sample calibration, not an independent measurement.
  • domain assumption Injection-recovery with fixed limb darkening (0.3,0.3) and no validation of injected signals measures detection efficiency.
    §3.2: unvalidated injected signals are assumed not to bias the completeness map; the three sinusoidal-variation targets are retained on the basis of injection tests.

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Pith. "Pith review of TESS planets in known radial velocity cold Jupiter systems: Hot super Earth occurrence is enhanced by cold Jupiters." pith.science (2026). https://pith.science/paper/ZGS3HPMS

@misc{pith2026260211017,
  author       = {Pith},
  title        = {Pith review of: TESS planets in known radial velocity cold Jupiter systems: Hot super Earth occurrence is enhanced by cold Jupiters},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/ZGS3HPMS}},
  note         = {Machine review of arXiv:2602.11017}
}
abstract

The correlation between inner super-Earths (SEs) and outer cold Jupiters (CJs) provides an important constraint on the formation and dynamical evolution of planetary systems. Previous studies have suggested a positive connection between these two populations, particularly around metal-rich stars, and proposed that nearly all CJ-hosting stars may also harbor inner SEs. In this work, we use TESS transits to investigate the occurrence of hot super-Earths (HSE; $1$-$4R_\oplus$, $P<10\mathrm{d}$) in systems with known CJs detected by radial velocity. Out of a statistical sample of 132 CJ systems, we identify five transiting HSEs around four stars, including one new candidate (TOI-6965.01) around HD 50554. To enable statistical analysis, we first validate the two candidates around HD 50554 using TESS photometry, archival RV measurements, and Gaia astrometry. After accounting for detection sensitivity and geometric transit probability, we find that the presence of CJs enhances the occurrence rate of HSEs by a factor of $6.5^{+3.1}_{-2.3}$ relative to field stars, with the case of no enhancement being ruled out at 99.9% confidence level. Taking into account the average multiplicity of HSEs, we find that about 91% of CJ systems host at least one HSE. Our results provide strong supporting evidence for a positive HSE-CJ correlation. We also briefly explore the correlation around metal-poor hosts and for specific sub-populations (e.g., warm super Earths or cold super Jupiters).

Figures

Figures reproduced from arXiv: 2602.11017 by the authors.

Figure 1
Figure 1. Planet mass (or minimum mass) as a function of orbital period for planetary systems hosting cold Jupiters. Gray points represent the full population of confirmed exoplanets from the NASA Exoplanet Archive. The dashed box outlines the parameter space adopted for CJs and HSEs in this work. Colored stars denote systems in our sample that host both a CJ and at least one inner SE detected by TESS: HD 219134, π Mensae, HD… view at source ↗
Figure 2
Figure 2. The distribution of the cold Jupiter host stars in our sample. Left: The histogram of stellar mass. Right: The histogram of TESS magnitude. ties nd and Ntr are the number of in-transit points and the number of transits, respectively (Pont et al. 2006; Hartman & Bakos 2016). We follow the procedure of Kunimoto et al. (2025) in computing each of those pa￾rameters in Equation (1). Out of the 132 systems with RV cold Ju… view at source ↗
Figure 3
Figure 3. The average detection sensitivity map (left panel) and the full completeness (i.e., detection sensitivity & transit probability) map (right panel) as a function of orbital period and planet radius. The number in each cell represents the average detection probability across all 132 targets. The red circles with error bars indicate the five HSEs detected by our pipeline. 333 334 335 336 337 338 339 340 341 Pixel Colum… view at source ↗
Figures from the paper (5 more)
Figure 4
Figure 4. Figure 4: TESS TPF image of HD 50554 (TIC 80224448) observed in Sector 72. Orange squares outline the photomet￾ric apertures. The red cross marks the nominal position of the target star. Red dots denote nearby Gaia sources, and the sizes of dots reflect their magnitude differenc…
Figure 5
Figure 5. Figure 5: The TESS light curves of HD 50554. The top panel shows the flattened TESS light curves from Sectors 44, 45, 71, and 72. Grey points indicate short-cadence data with 2-minute sampling, and black points are 1-hour averages for visualization. Blue and red dashed lines mar…
Figure 6
Figure 6. Figure 6: Radial-velocity analysis of the HD 50554 system plotted by radvel. (a-b) Current public RV time-series and residuals of the full three-planet model. (c–e) Phase-folded RV signals for planets c, d, and b, respectively. The blue curves show the corresponding best-fit orb…
Figure 7
Figure 7. Figure 7: Posterior distributions of the enhancement factor of the occurrence rate of hot SE in the presence of CJ. The two distributions shown in different colors are derived using the occurrence rates of HSEs from Zhu & Dong (2021) and Petigura et al. (2018), respectively. The…
Figure 8
Figure 8. Figure 8: The planetary systems with RV CJs in our sample as a function of host star metallicity. The four systems with transiting HSE discovered by TESS are marked in orange. to make it (Delisle et al. 2025), this requirement is gen￾erally difficult for RV method. One way to na…

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