OrCAS: Origins, Compositions, and Atmospheres of Sub-neptunes. I. Survey Definition

Akihiko Fukui; Alex S. Polanski; Allyson Bieryla; Anna Gagnebin; Arjun B. Savel; Bob Massey; Catherine A. Clark; Chris Stockdale; Claire J. Rogers; Courtney Dressing

REVIEW 3 major objections 5 minor 108 references

OrCAS: Origins, Compositions, and Atmospheres of Sub-neptunes. I. Survey Definition

T0 review · 3 major / 5 minor · reviewed 2026-08-12 · deepseek-v4-flash

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Pith's one-line read A repeatable scorecard selects 26 sub-Neptunes whose masses are within reach and whose atmospheres JWST should study.

desk verdict Solid survey-definition paper with a genuinely new prioritization metric; the per-target feasibility claim leans harder on a deterministic mass-radius relation than the paper acknowledges. read the letter →

arxiv 2411.16836 v1 pith:XFMB5LH3 submitted 2024-11-25 astro-ph.EP

Ian J. M. Crossfield , Alex S. Polanski , Paul Robertson , Joseph Akana Murphy , Emma V. Turtelboom , Rafael Luque , Thomas Beatty , Tansu Daylan

show 56 more authors

Howard Isaacson Jonathan Brande Laura Kreidberg Natalie M. Batalha Daniel Huber Maleah Rhem Courtney Dressing Stephen R. Kane Malik Bossett Anna Gagnebin Maxwell A. Kroft Pranav H. Premnath Claire J. Rogers Karen A. Collins David W. Latham Cristilyn N. Watkins David R. Ciardi Steve B. Howell Arjun B. Savel Perry Berlind Michael L. Calkins Gilbert A. Esquerdo Jessica Mink Catherine A. Clark Michael B. Lund Rachel A. Matson Mark E. Everett Joshua E. Schlieder Elisabeth C. Matthews Steven Giacalone Thomas Barclay Roberto Zambelli Peter Plavchan Taylor Ellingson Michael Bowen Gregor Srdoc Kim K. McLeod Richard P. Schwarz Khalid Barkaoui Jacob Kamler Felipe Murgas Enric Palle Norio Narita Akihiko Fukui Howard M. Relles Allyson Bieryla Eric Girardin Bob Massey Chris Stockdale Pablo Lewin Riccardo Papini Pere Guerra Dennis M. Conti Selcuk Yalcinkaya Ozgur Basturk Ghachoui Mourad

This is my paper · ORCID

classification astro-ph.EP

keywords sub-NeptuneexoplanetsradialvelocitymassmeasurementTESStransitcandidatestransmissionspectroscopyexoplanettargetselectionstatisticalvalidationJWSTplanetoccurrence

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

The paper targets a specific bottleneck: JWST can characterize sub-Neptune atmospheres, but doing so requires a precisely measured planet mass, and the pool of suitable sub-Neptunes with 5-sigma masses is nearly exhausted. OrCAS is a radial-velocity survey that picks TESS planet candidates using a quantitative, repeatable metric, ranking them by how much they offset JWST's demographic bias, how detectable their atmospheres should be, and how cheaply their masses can be measured. Applying that metric as of September 2023, then vetting the top candidates with ground-based photometry, high-resolution imaging, and statistical validation, leaves a sample of 26 systems (31 known planets) with median radius near 2.5 Earth radii and median equilibrium temperature near 800 K. The paper's claim is that this sample is well-validated, unlikely to harbor false positives, promising for transmission spectroscopy, and mass-measurable with a reasonable investment of observing time. If the claim holds, these measurements keep the target pipeline flowing for atmospheric characterization of the most common type of known exoplanet.

What carries the argument

The load-bearing object is the priority metric M = SUR(Rp, P) × TSM / t5σ. SUR is a two-dimensional map built by subtracting a kernel-density estimate of JWST Cycle 1–2 targets from a kernel-density estimate of the intrinsic occurrence distribution; t5σ is the estimated total observing time to reach a 5-sigma mass, derived from a single instrument's exposure-time calculator, an assumed 0.5 m/s noise floor, granulation and oscillation jitter, rotation jitter, and a power-law mass-radius relation. The metric is what makes the survey repeatable and minimally biased. Secondary machinery is the validation pipeline—TRICERATOPS false-positive probability runs on the TESS apertures and high-resolution imaging, plus uniform BATMAN transit fits to TESS photometry with emcee—which turns the top-ranked candidates into the final 26.

What would settle it

Recompute the prioritization using the original period-radius occurrence distribution and compare the resulting ranks; if a substantially different set of 26 targets emerges, or if the final sample's radius-period histogram no longer preferentially fills the JWST under-represented region, the demographic claim fails. Independently, if more than one or two of the 26 validated candidates are later shown to be false positives despite a summed FPP plus NFPP of 0.17, the statistical-validation claim is falsified.

Watch

Extended reading notes

Core claim

The central discovery is a method and a vetted sample. The paper defines the Sub-neptune Under-representation Rate (SUR) as the difference between the intrinsic occurrence of short-period planets and the density of planets actually scheduled for JWST spectroscopy; the target priority M multiplies SUR by the transmission spectroscopy metric (TSM) and divides by the estimated time to reach a 5-sigma radial-velocity mass. The authors then apply this to all TESS Objects of Interest, reject candidates that imaging or photometry shows could be eclipsing binaries or background blends, validate the survivors with a false-positive probability calculation, and fit the TESS light curves uniformly. The resulting 26 systems span planet radii from 1.6 to 4.2 Earth radii, have a median estimated TSM of 56, and have a summed false-positive probability of about 0.17; the companion planets bring the total to 31. On the paper's terms, this is a sample deliberately constructed to correct the under-representation of temperate sub-Neptunes in JWST's target pool while keeping mass measurement costs manageable.

Load-bearing premise

The load-bearing premise is that the self-constructed proxy for the intrinsic occurrence distribution—built from a Kepler sample with fixed cuts on impact parameter, period, stellar radius, and temperature because the original period-radius distribution was unavailable—is close enough to the true occurrence rate that the SUR map correctly identifies which sub-Neptunes the JWST target pool most under-represents.

Editorial extensions

If this is right

If the 26 masses reach at least 5-sigma significance, the sample roughly doubles the number of sub-Neptunes with precise masses that are good transmission-spectroscopy targets and are not already in JWST's Cycle 1–3 pool.
Because the selection metric is published as code and the SUR maps are available in electronic form, future candidates can be ranked the same way, so later mass-radius studies can account for the selection function.
The summed false-positive probability of 0.17 implies roughly one-in-six odds that a single target in the sample is not a real planet, so most of the 26 should survive as genuine sub-Neptunes.
A floor of 30 radial velocities per target guards against the known upward bias from stopping once 5-sigma is reached, so the reported masses should be less biased than early-terminated surveys.
If the survey succeeds, the sample's median 800 K equilibrium temperature puts many targets in the regime where aerosols are expected to be less prevalent, increasing the chance that JWST transmission spectra show molecular features.

Reading between the lines

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

If the masses land as estimated, the homogeneous 1.6–4.2 Earth-radius sample will be a direct test of whether the rocky/icy/gaseous trichotomy seen for small planets around M dwarfs also holds for FGK hosts, because the selection is demographic rather than composition-based.
The SUR construction is sensitive to the choice of occurrence proxy, so the demographic weighting is an empirical hypothesis that updated or original occurrence catalogs can check.
The same metric could be re-run as JWST's target list evolves, or adapted for other missions, for example by replacing TSM with expected spectral information content, which would change the ranking for cloudy planets.
If several targets turn out to be false positives or need many more than 30 radial velocities, that would indicate the time estimator is optimistic; comparing planned versus actual observing cost per target would calibrate the metric for future surveys.

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Editorial analysis

A structured set of objections, weighed in public.

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

Desk Editor's Note

read the letter

Worth a read if you work on RV follow-up or sub-Neptune demographics. The genuinely new piece is the SUR-weighted metric M = SUR x TSM / t5sigma, which explicitly trades demographic under-representation against observing cost, and they ship public code for it. That is a real, reusable contribution. The target sample itself — 26 statistically vetted sub-Neptunes with uniform TESS light-curve fits, ground-based follow-up tabulated, FPP/NFPP sums kept low — is a useful resource for the community. The paper is transparent about its procedures and limitations, which counts for a lot.

The soft spot is the mass-radius handling. Section 3.1 estimates K and t5sigma from the single-valued relation M_P = R_P^2.06, but Section 2.2 itself notes that masses at fixed radius vary by up to a factor of five. Since t5sigma scales roughly as K^{-2}, a target sitting at the low-mass end of the scatter could need many more than the planned ~30 RVs to reach 5 sigma. That directly bears on the central claim that these 26 masses can be measured with a reasonable investment of observing time. It is not a fatal flaw — the paper hedges by saying they may gather more RVs for a subset — but the feasibility forecast is more optimistic than the known scatter justifies, and it should be stress-tested, e.g. by propagating the observed mass-radius scatter through the t5sigma calculation. The reader's concern about the SUR proxy is real but less central: an imperfect demographic weighting weakens the representativeness claim without changing per-target feasibility or atmospheric prospects. The 'Likely Planet' dispositions for a few targets are minor given the summed FPP is only 0.17.

Citation practice looks honest; prior surveys (PFS, TKS, NCORES) are named and the novelty is scoped as a metric plus a validated sample, not a new physics claim. Overall the central argument holds: this is a well-executed survey definition that should enter the literature.

Referee Report

3 major / 5 minor

Summary. The paper presents the survey definition for OrCAS, an RV follow-up program targeting 26 TESS-discovered sub-Neptune candidates with the goal of providing precise masses for future JWST/ARIEL atmospheric characterization. The authors define a repeatable prioritization metric M = SUR × TSM / t5σ (Eq. 1), perform uniform TESS light-curve fits, carry out TRICERATOPS statistical validation, and report the resulting sample's stellar and planetary properties. The central claim, stated in the Conclusion (Section 6), is that the 26 targets are well-validated, unlikely to be false positives, promising for atmospheric spectroscopy, and amenable to mass measurement with a reasonable investment of observing time. The paper also releases code and electronic maps to reproduce the target selection.

Significance. If the sample holds up, the paper is a useful contribution to the small-planet characterization ecosystem: it provides a transparent, code-released prioritization scheme, a homogeneous set of transit fits and ephemerides, and a vetted target list for a high-impact RV program. The public code, electronic occurrence maps, and uniform TESS analysis are commendable and lower the barrier for future demographic studies. However, the headline claim about 'reasonable investment' of observing time depends on a single-valued mass-radius relation that the paper itself acknowledges is inconsistent with the observed factor-of-five scatter in sub-Neptune masses. Because that assumption enters the prioritization metric and the planned 30-RV floor, the central claim needs additional support before the paper can be accepted as is. No circularity issue is apparent: the metric is used for target selection, not to infer a physical result.

major comments (3)

[§3.1, Eq. (1)] The 'reasonable investment' claim rests on t5σ = (5/(K/σ1))^2, computed from a single-valued power law M_p = R_p^2.06 in Earth units. Section 2.2 itself notes that sub-Neptune masses at fixed radius vary by up to a factor of 5 (Wolfgang et al. 2016; Otegi et al. 2020; Parviainen et al. 2024). Since K is approximately proportional to planet mass for these low-mass planets, t5σ scales roughly as M^-2, so a factor-of-2-to-5 lower true mass raises the required number of RVs by roughly 4 to 25 times. The manuscript does not propagate this scatter into the prioritization metric or into the 30-RV floor, and it does not report per-target t5σ values. Consequently, the concluding claim that these masses can be measured with a reasonable investment of observing time is not directly supported. Please recompute t5σ under optimistic and pessimistic mass assumptions (e.g., using the 16th and 84th percentile masses from the cited mass-radius studies), report the resulting RV counts per target, identify any targets requiring substantially more than 30 RVs, or soften the conclusion accordingly. Note also that a target whose true mass is higher than the power-law estimate could have TSM below the 30 threshold despite passing the filter, which affects the atmospheric-prospects claim.
[§3.1] The Sub-neptune Under-representation Rate (SUR) is a multiplicative factor in the prioritization metric M (Eq. 1), but it is constructed from a self-made proxy for the intrinsic occurrence distribution rather than the original Fulton & Petigura (2018) period-radius distribution, which was unavailable from the authors. The manuscript discloses this in the paragraph beginning 'Since the underlying period-radius distribution from that work was not available...', but no cross-check against the original distribution or against alternative occurrence assumptions is given. Because SUR is used to weight the sample toward JWST-underrepresented planets, the 'demographically representative' framing is not quantitatively supported, even though this does not affect the per-target feasibility claims. Please add a robustness test (e.g., varying the CKS cuts or comparing against a published occurrence map) and report how the final rank ordering changes, or explicitly describe SUR as an illustrative weighting rather than a calibrated demographic correction.
[§6 and Table 2] The conclusion describes the 26 targets as 'well-validated,' but Table 2 assigns 'Likely Planet' (LP) rather than 'Validated Planet' (VP) to six of the 26 selected candidates (TOI-1630.01, TOI-1716.01, TOI-1744.01, TOI-1768.01, TOI-1777.01, and TOI-2211.01). The aggregate FPP+NFPP of 0.17 supports 'unlikely to be false positives,' but it does not support 'well-validated' in the Giacalone et al. (2021) taxonomy. Please present the VP/LP breakdown in the conclusion or rephrase the sample description to match the reported validation dispositions.

minor comments (5)

[Figure 2 caption and §3.1] There are several typographical errors: 'sup-Neptunes' in the Figure 2 caption, 'esimating' in §3.1, 'T able 1' and 'T able 2' in table environments, and 'This is paper is based' in the acknowledgments. These should be corrected in a final pass.
[§5.1] The sentence 'characterizing these properties is a key goal of Theme II (Sec. 2.4)' refers to Section 2.4, which is Theme IV (Stellar Activity), not Theme II (Internal Compositions). The theme number should be corrected.
[§3.2] The statement that the total sum of FPP and NFPP across the sample is 0.17 treats false-positive probabilities as approximately additive; this is an informal aggregation and should be flagged as such, since FPP and NFPP are not strictly additive probabilities.
[§3.1, Eq. (1)] The quantity t5σ is defined as a number of RV observations (5/(K/σ1))^2, but the text and Eq. (1) refer to it as 'the estimated time to measure a 5σ mass.' Please clarify the units and, if a time estimate is intended, describe how exposure times per observation are folded in.
[Figure 3] The transit light-curve fits are shown only as binned data with best-fit models; adding a residual panel or rms value for each system would help the reader assess the quality of the uniform fits.

Circularity Check

0 steps flagged · score 2.0 of 10

No material circularity: target prioritization is an explicit external-input metric, and the only self-citations are non-load-bearing practical/data references.

full rationale

The paper's derivation chain is a survey-selection pipeline rather than a physical prediction. The prioritization metric in Eq. (1), M = SUR(Rp,P) x TSM / t5sigma, is built from stated external inputs: a CKS-based occurrence proxy that the paper explicitly flags as a proxy because the Fulton & Petigura distribution was unavailable; a KDE of JWST Cycle 1-2 targets; the Kempton TSM; and a KPF exposure-time estimate with a 0.5 m/s noise floor. The light-curve radii and TRICERATOPS FPP/NFPP values are fits and validations of TESS photometry and ground-based imaging, not outputs of the selection metric. The conclusion's 'reasonable investment of observing time' is indeed a restatement of the t5sigma term that helped select the sample, so it inherits the single-valued M-R power-law assumption and the noise model; however, the paper presents t5sigma as an estimate used for selection, not as an empirical prediction, and explicitly acknowledges that sub-Neptune masses scatter by up to a factor of five and that TSM values will change once masses are measured. No equation is shown to reduce to itself, and no load-bearing argument is carried by a self-citation: the Akana Murphy et al. (2024) minimum-30-RV heuristic and the Polanski et al. (2024) HIRES-mass justification are practical/data references, and the TRICERATOPS validation is a public tool with externally stated thresholds. Accordingly, the minor self-citations do not rise to circularity.

Assumptions & free parameters 5 free parameters · 4 assumptions · 0 invented entities

The central design depends on a few imported assumptions and chosen thresholds: the proxy occurrence map, the single-valued mass-radius relation, the representative JWST target list, and the selection cuts TSM>=30, J>6 mag, and declination>-20 deg. No new physical entities are introduced.

free parameters (5)

Mass-radius power-law exponent = 2.06
Used in Sec. 3.1 to estimate planet mass from radius via Mp = Rp^2.06 (Lissauer et al. 2011). Single-valued, ignores scatter (Wolfgang et al. 2016), so t5sigma estimates are approximate.
KPF internal noise floor = 0.5 m/s
Assumed in Sec. 3.1 based on private communication with KPF Instrument Team; used to compute per-shot RV uncertainty and t5sigma.
TSM threshold = 30
Adopted in Sec. 3.1 to ensure JWST transmission spectroscopy feasibility; a choice that shapes the sample.
J-band magnitude limit = 6 mag
Adopted in Sec. 3.1 to avoid saturation for JWST; a choice that excludes bright but rare stars.
Declination cut = -20 deg
Adopted in Sec. 3.1 for accessibility from Maunakea and WIYN; a choice that removes southern targets.

assumptions (4)

domain assumption The CKS-based proxy occurrence distribution with cuts (b<0.7, P<100d, Rstar<2.1Rsun, Teff 4700-6500K) adequately reproduces the intrinsic Fulton & Petigura (2018) occurrence rate used for SUR.
Sec. 3.1 states the authors constructed their own proxy because the original distribution was unavailable; the validity of SUR and hence the prioritization metric depends on this.
domain assumption The single-valued mass-radius relation Mp = Rp^2.06 holds for all targets.
Sec. 3.1 uses this relation to estimate K and t5sigma; known scatter means actual required observing time may differ.
domain assumption JWST Cycle 1 and 2 target list is representative of JWST's overall target selection for the SUR map.
Sec. 3.1 constructs the JWST sampling density KDE from approved Cycle 1 and 2 targets; if later cycles differ, the under-representation map changes.
domain assumption TRICERATOPS accurately estimates FPP and NFPP using the provided TESS photometry and high-resolution imaging.
Sec. 3.2 relies on TRICERATOPS outputs to validate the candidates; the tool's accuracy is assumed.

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Cite this review

Pith. "Pith review of OrCAS: Origins, Compositions, and Atmospheres of Sub-neptunes. I. Survey Definition." pith.science (2026). https://pith.science/paper/XFMB5LH3

@misc{pith2026241116836,
  author       = {Pith},
  title        = {Pith review of: OrCAS: Origins, Compositions, and Atmospheres of Sub-neptunes. I. Survey Definition},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XFMB5LH3}},
  note         = {Machine review of arXiv:2411.16836}
}

read the original abstract

Sub-Neptunes - volatile-rich exoplanets smaller than Neptune - are intrinsically the most common type of planet known. However, the formation and nature of these objects, as well as the distinctions between sub-classes (if any), remain unclear. Two powerful tools to tease out the secrets of these worlds are measurements of (i) atmospheric composition and structure revealed by transit and/or eclipse spectroscopy, and (ii) mass, radius, and density revealed by transit photometry and Doppler spectroscopy. Here we present OrCAS, a survey to better elucidate the origins, compositions, and atmospheres of sub-Neptunes. This radial velocity survey uses a repeatable, quantifiable metric to select targets suitable for subsequent transmission spectroscopy and address key science themes about the atmospheric & internal compositions and architectures of these systems. Our survey targets 26 systems with transiting sub-Neptune planet candidates, with the overarching goal of increasing the sample of such planets suitable for subsequent atmospheric characterization. This paper lays out our survey's science goals, defines our target prioritization metric, and performs light-curve fits and statistical validation using existing TESS photometry and ground-based follow-up observations. Our survey serves to continue expanding the sample of small exoplanets with well-measured properties orbiting nearby bright stars, ensuring fruitful studies of these systems for many years to come.

Figures

Figures reproduced from arXiv: 2411.16836 by the authors.

**Figure 1.** Number of target systems in each of our science themes: atmospheres (I), interior compositions (II), system architectures (III), and stellar activity (IV). See Sec. 2 and [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗

**Figure 2.** Target prioritization. Left: Planet occurrence rate (Fulton & Petigura 2018), showing that sup-Neptunes and super-Earths are the most common planets on short-period orbits. Center: Gold hexagons show transiting exoplanets targeted by JWST in Cycles 1 & 2 (our survey began before Cycle 3 results were announced); the shading is a Kernel Density Estimate map showing that hot Jupiters and super-Earths were the most comm… view at source ↗

**Figure 3.** Transit light-curve fits to our target sample, showing TESS photometry (black points, binned to a 10-minute cadence) and the best-fit light curves (red line). 2000 1500 1200 1000 800 700 600 500 400 Planet Equilibrium Temperature [K] 1.5 2.0 2.5 3.0 3.5 4.0 Pla n e t R a diu s [R ] 6000 5500 5000 4500 4000 3500 Stellar Effective Temperature [K] 1.5 2.0 2.5 3.0 3.5 4.0 0 1 2 3 4 5 6 7 8 9 Our Sample Relative Occurren… view at source ↗

Figures from the paper (1 more)

**Figure 4.** Figure 4: Our target sample, showing the distribution of fit planet size, temperature, and stellar Teff . Red points are our primary sample, white points are known companions to our targets, dashed lines connect planets orbiting the same target star, and light gray points are ot…

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