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REVIEW 4 major objections 5 minor 72 references

A Search for Transiting Exocomets in TESS Sectors 1-26

T0 review · 4 major / 5 minor · reviewed 2026-08-05 · deepseek-v4-flash

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Pith's one-line read Searching 15.5 million TESS light curves, this paper finds five new exocomet-like transit candidates plus the known Beta Pic event, and derives an efficiency-corrected occurrence rate of 2.64 x 10^-4 star^-1 year^-1, concluding that photome

desk verdict A careful first TESS census with a handful of promising candidates; the headline rate is model-dependent but the rarity conclusion is solid. read the letter →

arxiv 2508.04673 v1 pith:7MBX5KKZ submitted 2025-08-06 astro-ph.EP

Azib Norazman , Grant M. Kennedy , Ann Marie Cody , Daniel Giles , Samuel Gill , Ethan Kruse This is my paper · ORCID
classification astro-ph.EP
keywords exocometsTESStransitphotometryoccurrencerateBetaPictorisskewed-GaussianmodelG-typeexocomethostsgiant-starcandidates
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 reports a systematic search for transiting exocomets in 15.5 million TESS light curves from the primary mission. The authors recover the known exocomet transit around Beta Pic and identify five new candidate systems, concluding that photometrically transiting exocomets are extremely rare at the 0.1%-1% transit-depth level. The search extends the candidate population beyond the young A/F-type stars favored by earlier work: two candidates are consistent with G-type main-sequence hosts and two with evolved giants, the first photometric exocomet candidates around such stars. The efficiency-corrected occurrence rate is 2.64 x $10^{-4}$ $star^{-1}$ $year^{-1}$ for transits roughly 0.25% or deeper, about forty times the Kepler-based rate, a difference the authors attribute to their detection-efficiency correction and to small-number statistics.

What carries the argument

The skewed-Gaussian transit model and its companion asymmetry ratio $\alpha$. Each candidate event is fitted twice, once with a symmetric Gaussian and once with a skew-normal profile built from the normal density phi and its cumulative Phi with skewness $\beta$ (Eq. 8), and the ratio $\alpha$ of the two fit residuals (Eq. 9) decides whether the dip is asymmetric; the sign of $\beta$ fixes the direction, with positive $\beta$ giving the sharp-ingress, gradual-egress shape expected of a comet's trailing tail. The search uses a moving-average test statistic over window widths 0.1-2.5 days with a 2.5-day median-filter detrend, and the occurrence rate (Eq. 11) divides the detection count by the injection-recove

What would settle it

Spectroscopic follow-up of the two probable G-type candidates (TIC 73149665 and TIC 143152957) would settle the host-star claim, and higher-precision photometry of TIC 229790952, already observed in 42 TESS sectors, could confirm whether additional shallow dips recur and distinguish a genuine exocomet from stellar variability. More directly, re-running the injection-recovery analysis with injected transits drawn from a physically motivated comet model rather than a skewed Gaussian would test the assumption on which the occurrence rate rests.

Watch

Extended reading notes

Core claim

The central claim is that single, asymmetric photometric dips, the signature of an exocomet occulting its host star with a trailing dust tail, are very rare in TESS data at the depths this survey can reach. Screening 15,477,322 light curves with an automated single-transit search and an asymmetry measure based on skewed-Gaussian fitting, the authors recover the known Beta Pic event and report five new candidates: three around main-sequence stars (including two probable G-type hosts near 5500-5700 K), one around a K-type giant, and one around a G-type supergiant. Counting these detections with injection-recovery corrections gives a combined occurrence rate of 2.64 x $10^{-4}$ $star^{-1}$ $year^{-1}$ for

Load-bearing premise

The headline rate depends on measuring how many events the pipeline misses by injecting synthetic transits drawn from the same skewed-Gaussian shape model used to select candidates, with the Beta Pic event as template; if real comet transits, especially around faint stars and giants, were shaped differently or were discarded by the median filter or common-time cut, the 2.64 x $10^{-4}$ $star^{-1}$ $year^{-1}$ rate would be biased.

Editorial extensions

If this is right

  • Photometrically transiting exocomets are rare: roughly six events in 15.5 million light curves, giving an efficiency-corrected occurrence rate of 2.64 x 10^-4 star^-1 year^-1 for transits about 0.25% or deeper.
  • Exocomet-like transits are not confined to young A/F stars: two candidates are consistent with G-type main-sequence hosts and two with evolved giants, the first photometric exocomet candidates around such stars.
  • Beta Pic is an outlier: its per-star occurrence rate is at least roughly 1000 times higher than every other candidate, so the system should not be treated as representative of typical stellar hosts.
  • The TESS rate exceeds the Kepler rate by about forty times, but the difference likely reflects small-number statistics and the efficiency correction the Kepler search lacked; a larger detection sample is needed to draw firm conclusions.
  • The reported rate is likely a lower bound, because the pipeline keeps only the most significant dip per light curve and would miss shallower companion transits such as the two Beta Pic events recovered only with dedicated modeling.

Reading between the lines

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

  • If the two G-type candidates are confirmed by spectroscopy, the claimed host-star bias of exocomet detections toward young A/F stars weakens, and targeted searches around Sun-like stars become a viable strategy to test.
  • The occurrence-rate correction assumes real transits share the skewed-Gaussian shape family of the Beta Pic template; re-running the injection-recovery tests with physically motivated coma-and-tail profiles (rather than skew-normal curves) would directly test whether the large correction factors, up to about 90 in the faintest bins, are unbiased.
  • The common-time cut removed entire clusters of candidate events flagged as pipeline artifacts; if any of those were real, the true rate is higher than 2.64 x 10^-4 star^-1 year^-1, making the headline number a lower bound for all asymmetric shapes, not just the favored one.
  • Giant-star hosts may represent a distinct physical channel: because the sublimation radius expands as a star evolves, equal-depth transits around a larger star imply larger or more actively outgassing bodies, a scenario that multi-sector monitoring of TIC 229790952 (42 sectors available) could test by catching repeat events.
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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 / 5 minor

Summary. The paper presents an automated search for single, asymmetric exocomet-like transits in TESS primary-mission light curves (Sectors 1–26, 15.5 million light curves). The pipeline uses a moving-average test statistic, fits symmetric and skewed Gaussian profiles, and applies a sequence of cuts on SNR, duration, depth, skewness, and asymmetry ratio, followed by extensive manual vetting. The authors recover the known β Pic exocomet transit and report five new candidates, including three main-sequence stars (one F-type, two probable G-types) and two giant/supergiant stars. They use injection–recovery tests to estimate detection efficiency and derive a total occurrence rate of 2.64 × 10⁻⁴ star⁻¹ yr⁻¹ excluding β Pic, nearly 40 times higher than the earlier Kepler rate, and conclude that photometrically transiting exocomets are very rare at 0.1–1% depths.

Significance. If the quantitative occurrence rate is robust, this would be the first large-scale TESS census of photometric exocomet transits, with new candidate host types (G-type main-sequence stars and evolved stars) that challenge the A/F-star bias suggested by Kepler. The paper is carefully structured and the vetting is unusually detailed: the authors test a complementary TESS-SPOC sample, perform a time-reversed search, and provide injection-recovery maps over magnitude and depth. The code is publicly available, and the recovery of the known β Pic event is a useful end-to-end validation. The main value lies in the candidate list and the demonstration that a systematic TESS search is feasible; the specific occurrence rate, however, depends on several assumptions that are not yet tested.

major comments (4)
  1. [§3.5, Eq. (8)–(11)] The injection–recovery efficiency f_inj_rec is measured by injecting synthetic transits drawn from the same skew-normal family (Eq. 8) that defines the shape-selection cuts (0 < skewness < 8, α > 1.02). This measures recovery of the assumed model, not of real exocomet transits. Since correction factors reach ~90 (§6.3), even a modest misestimate of f_inj_rec changes the headline rate by a large factor. Please test sensitivity to shape assumptions by injecting alternative tail profiles (e.g., power-law egress, two-component coma+tail, different asymmetry/duration ratios) and recompute the efficiency map and final rate. At minimum, quantify how the occurrence rate shifts if the injection template is varied within plausible bounds.
  2. [§4, Table 1] The thresholds (SNR>5, duration>0.4 d, depth<1%, 0<skewness<8, α>1.02) were developed after experimenting on Sector 6, which contains the known β Pic transit. This tuning means the completeness measured by injection–recovery is not a blind-search completeness; part of the efficiency is fitted to a known positive detection. The paper states that Sectors 9 and 17 were checked, but the thresholds are still informed by β Pic. Please quantify how the candidate list and f_inj_rec change if thresholds are set using only the comparison catalogues (Fig. 4) and not Sector 6, or state explicitly how much of the efficiency correction is attributable to this tuning.
  3. [§6.3, Eq. (11)] No uncertainties are propagated into the occurrence rate. With five detections (excluding β Pic), the Poisson 95% interval spans roughly a factor of several; the injection-recovery map itself has binomial uncertainty (20,000 injections per bin), but no error bars are shown on the efficiency values. The factor-38 contrast with the Kepler rate (6.7 × 10⁻⁶) is therefore not statistically significant without confidence intervals. Please provide Poisson upper/lower limits on N_det and propagate the f_inj_rec uncertainties, or explicitly state that the quoted rates are order-of-magnitude estimates. Also clarify the counting in the text: it says 'summing the three bins' but there are five candidates excluding β Pic; specify exactly how many candidates and bins are included in the 1.95 × 10⁻⁵ star⁻¹ sector⁻¹ value.
  4. [§5, §6.2] The occurrence rate treats all five new candidates as real exocomet transits, but the paper itself notes that some are tentative: TIC 110969638 (G supergiant) could be intrinsic stellar variability (§6.2), TIC 280832588 is described as tentative and fails the asymmetry cut in TESS-SPOC (§5.1.2), and the G-type classifications for two candidates lack spectroscopic confirmation. If one or more are false positives, the rate is overestimated. Please provide a conservative rate obtained by excluding the most uncertain candidate(s), or at least state how the conclusion changes under such an assumption.
minor comments (5)
  1. [Abstract / §6.3] The abstract states the rate is 'much higher' than Kepler's; given the small number statistics and the unpropagated uncertainties, this should be softened to 'higher, though with large uncertainties'.
  2. [§6.3] Reference to 'Fig 6.3' should be 'Fig. 7'.
  3. [§5.2 heading] Typo: 'TIC 2297970952' should be 'TIC 229790952'.
  4. [§1] The citation 'Iglesias et al. (in review)' lacks a full bibliographic entry; please provide an arXiv identifier or update the reference list.
  5. [Figure 7] The axes are labelled in a way that is easy to misread (e.g., '10 3 10 2' appears without superscripts or units). Please add clear axis labels such as 'Transit depth (%)' and 'Magnitude (T mag)' and ensure the colour-bar scale is legible.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the occurrence-rate derivation is not equivalent to its inputs by construction, though the completeness correction is model-dependent.

full rationale

The central derivation is Eq. 11, focc = Ndet/N_T × 1/f_inj_rec. The f_inj_rec correction is obtained in Section 3.5 by injecting synthetic transits drawn from the same skewed-Gaussian model (Eq. 8) used to characterise candidates and seeded with beta Pic parameters. This makes the efficiency estimate internally self-consistent, but it is an explicit morphological assumption, not an identity: focc is not equal to the injection fraction, and the paper does not claim to measure transits outside that shape family. The paper repeatedly acknowledges the rates are lower bounds and small-number limited (Section 7.2: 'our occurrence rates being a lower bound to the true rate'; 'we potentially missed multiple smaller transit events'), so the model-dependence is disclosed rather than disguised as a first-principles result. The recovery of beta Pic is a known-event test, and thresholds were partly explored on Sector 6 which contains beta Pic; this weakens the validation but does not enter the occurrence-rate calculation for the new candidates. Self-citations (Kennedy et al. 2019 for the method and Kepler rate; Zieba et al. 2019 for beta Pic; Yelverton et al. 2019/2020 for SED fitting) are methodological and empirical, not load-bearing uniqueness theorems or unverified premises. No equation in the paper reduces the predicted occurrence rate to its input by construction, and no fitted parameter is relabelled as a prediction. Thus there is no significant circularity.

Assumptions & free parameters 8 free parameters · 6 assumptions · 0 invented entities

The central occurrence rate rests on a chain of hand-tuned cuts and on an efficiency correction whose injected events use the same shape model as the detector. No independent confirmation of the five new candidates is provided, and the paper itself notes that spectral types and the nature of the giant-star events are uncertain.

free parameters (8)
  • Transit duration minimum = 0.4 days
    Chosen by comparing candidate durations with eclipsing binary and TOI catalogues; assumes shorter transits are binaries rather than exocomets (Section 4).
  • Transit depth maximum = 1%
    Called an arbitrary practical threshold in Section 4; excludes deeper dipper-like events and shapes the occurrence rate sample.
  • Signal-to-noise minimum = 5
    Follows Kennedy et al. (2019); affects which events enter the candidate list (Section 4).
  • Asymmetry threshold = alpha > 1.02
    Set by inspecting subsets of candidate alpha values, slightly more generous than the 1.05 used in Kennedy et al. (2019) (Section 4.2).
  • Skewness upper limit = 8
    Set from visual assessment of where skewed Gaussian fits represent discontinuities or noise rather than real events (Section 4.2).
  • Common-time transit removal threshold = 10 times the MAD of 100-bin counts per sector
    Chosen to remove clustered events attributed to pipeline issues; may also remove real transits (Section 4.1).
  • Median filter window = 2.5 days
    Chosen to preserve exocomet shapes while removing stellar variability; affects which durations and depths survive (Section 3.2).
  • Injected synthetic transit shape = Skewed Gaussian based on the beta Pic detection
    Used for injection-recovery completeness; if real exocomet shapes differ, the efficiency correction and occurrence rate are biased (Section 3.5).
assumptions (6)
  • domain assumption Exocomet photometric transits have sharp ingress and gradual egress, corresponding to positive skewness.
    Adopted from Lecavelier Des Etangs et al. (1999) and used for the shape cuts in Section 3.4.
  • ad hoc to paper The skewed Gaussian distribution is an adequate shape model for real exocomet transits.
    Used in Eq. 8 for candidate selection and injection-recovery; no independent validation for the broad population is provided (Sections 3.4 and 3.5).
  • domain assumption Common-time transits are instrumental artefacts and can be removed without removing real exocomet events.
    Justified in Section 4.1 by comparison with other pipelines and Cody et al. (in prep.), but the possibility of losing real events is acknowledged.
  • domain assumption Transits longer than 0.4 days and shallower than 1% are more likely exocomets than binaries or dippers.
    Used in Section 4 to set the duration and depth cuts based on catalog comparisons and the beta Pic event.
  • domain assumption eleanor-lite PCA flux and the MAD quality filter preserve real exocomet transits.
    The cleaning steps in Section 3.1 rely on this; the beta Pic recovery is the main validation.
  • domain assumption Each surviving candidate is a genuine astrophysical transit rather than an instrumental or stellar-variability false positive.
    The occurrence rate in Section 6.3 counts all vetted candidates as real exocomets; no false-positive rate correction is applied.

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Cite this review

Pith. "Pith review of A Search for Transiting Exocomets in TESS Sectors 1-26." pith.science (2026). https://pith.science/paper/7MBX5KKZ

@misc{pith2026250804673,
  author       = {Pith},
  title        = {Pith review of: A Search for Transiting Exocomets in TESS Sectors 1-26},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/7MBX5KKZ}},
  note         = {Machine review of arXiv:2508.04673}
}
abstract

We present a search for single photometric exocomet transits using a magnitude-limited sample of stars observed by the TESS primary mission. These events are asymmetric, with a sharp ingress and more gradual egress expected because the comet tail trails behind the coma. Our goals are to estimate the occurrence rate of exocomet transits, and given sufficient numbers comment on whether the host stars are biased towards being A/F spectral types, as suggested by a previous survey with Kepler data. We recovered the previously identified exocomet transit with TESS around $\beta$ Pic (TIC 270577175) and identified three additional main sequence systems with exocomet-like transits (TIC 280832588, TIC 73149665, and TIC 143152957). We also identified one exocomet candidate around a giant star (TIC 229790952) and one around a probable supergiant (TIC 110969638). We find a total occurrence rate of $2.64\times10^{-4}$ star$^{-1}$ year$^{-1}$, much higher than Kepler's rate of $6.7 \times 10^{-6}$ star$^{-1}$ year$^{-1}$. Some of this difference may be because our rate includes a correction for detection efficiency, where the Kepler search did not. However, with only a handful of detections in each survey, the rates are also very uncertain. In contrast to the Kepler search, we find two candidate hosts that may be G types, but the spectral types would be better supported with spectroscopic follow-up. Primarily, we conclude that exocomet-like transits are very rare at 0.1%-1% transit depth levels, and that higher precision photometry to detect and characterise shallower transits effectively is the most likely path to more detections and stronger statistical conclusions.

Figures

Figures reproduced from arXiv: 2508.04673 by the authors.

Figure 1
Figure 1. An example of applying the MAD filter to a light curve. The left plot shows the MAD(t) values across the Sector 1, Camera 1 combination, where the red line is the median MAD(t) value, and the yellow line represents the MAD threshold. The right plot shows the light curve of TIC 126786455, where the blue line is the original light curve, the orange light curve removes the non-zero quality flags only, and the black lig… view at source ↗
Figure 2
Figure 2. The light curve of TIC 110969638 (top panel), its corresponding test-statistic 𝑇𝑚,𝑛, (middle panel - the colourbar shows the 𝑇 value across the light curve), and the background flux activity of that light curve (lower panel). There is an evident transit event at BTJD 1513 with a 𝑇𝑚𝑖𝑛 = -16.92, corresponding to an SNR = 6.43 with equation 3. Changes in the background flux that correlate with a transit could indicate … view at source ↗
Figure 3
Figure 3. Two-dimensional detection efficiency maps for our search method across the magnitude and depth range. Each magnitude bin consists of 20,000 injected transits. The sensitivities in plot (a) take into account the transit search if the injected transit was recovered within a 5-hour window of the injection time, and plot (b) uses the criteria for plot (a) and our thresholds applied in the analysis steps of the pipeline.… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Distribution of the candidates in Sector 6 showing the transit duration against the log transit depth. The candidates are coloured in blue, transits from the TESS eclipsing binary catalogue in (Kruse et al. 2021) are coloured in orange, TOI transits from EXO-FOP (Akeso…
Figure 5
Figure 5. Figure 5: Light curves of the exocomet candidates centred on the transit time. The black line is the best-fit skewed Gaussian model, and the orange line is the symmetric Gaussian model. All panels apart from 𝛽 Pic share the same y-axis range to show their respective transit dept…
Figure 6
Figure 6. Figure 6: A Gaia HR diagram showing all stars with eleanor-lite light curves in our search sample, and our exocomet candidates overplotted on them. The background colour is the number of stars per bin from the search sample, where each bin contains a minimum of 100 stars. The ba…
Figure 7
Figure 7. Figure 7: Estimations of exocomet occurrence rates in the TESS primary mission, where the detection rate values shown are for a given magnitude at given depth. The units for these occurrence rates are per star per TESS sector (star−1 sector−1 ). The black crosses highlight the l…

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Pith tools

Reviewed August 5, 2026 · model on record in the stance chip above.