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Results from the Pan-STARRS Search for Kilonovae: Contamination by Massive Stellar Outbursts

T0 review · 3 major / 4 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read After a 3.14-year, 29,740-transient Pan-STARRS search, all 11 kilonova candidates turned out to be something else—erupting massive stars accounted for 55% of them.

desk verdict The null result and LBV rate work are solid, but the headline contamination forecast (4±2 per 500 deg^2) is off by roughly a factor of five from their own rate formalism. read the letter →

arxiv 2506.07082 v1 pith:5PCKJT6K submitted 2025-06-08 astro-ph.HE

M. D. Fulton , S. J. Smartt , M. E. Huber , K. W. Smith , K. C. Chambers , M. Nicholl , S. Srivastav , D. R. Young
show 6 more authors
E. A. Magnier C.-C. Lin P. Minguez T. de Boer T. Lowe R. Wainscoat
This is my paper
classification astro-ph.HE
keywords kilonovaPan-STARRStransientsearchluminousbluevariableoutburstsgravitational-waveelectromagneticcounterpartsLSSTfollow-upfast-evolvingtransientsvolumetricratesATLASsurvey
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 reports a wide-field optical search for kilonovae that deliberately did not wait for a gravitational-wave or gamma-ray-burst trigger, and its headline result is a null. Over 3.14 years Pan-STARRS reported 29,740 transients, narrowed these to 175 genuinely faint and nearby events (host galaxies within 200 Mpc, discovery absolute magnitude $M > -16.5$), and flagged 11 as plausible kilonova candidates; follow-up through forced photometry, multi-survey data, and extensive imaging eliminated every one of them. Six of the 11 — 55% — turned out to be rapidly fading outbursts of luminous blue variable stars, massive stars whose sporadic eruptions mimic the fast fade and faint peak of a kilonova. Using a volume-limited ATLAS sample, the paper derives volumetric rates for these outbursts and predicts that LSST-era searches of LIGO-Virgo-KAGRA gravitational-wave skymaps will encounter roughly 2–6 of them per 500 square degrees within a 4-day observing window. The practical upshot is that future kilonova hunters face a countable, manageable background of impostors that can be identified with multiband photometry rather than spectra.

What carries the argument

The carrying object is the kilonova prediction algorithm built on $M$–$\dot M$ locus plots — probability densities, built by Gaussian kernel density estimation, of peak absolute magnitude against rise time, incline rate, decline rates $\Delta2d$, $\Delta5d$, $\Delta10d$, and colour, derived from 17,045 synthetic kilonova light-curve models plus template light curves of contaminant classes (ultra-stripped supernovae, shock-breakout Type IIb, 02cx-like Type Ia, LBV outbursts, intermediate-luminosity red transients, red novae, classical novae). Any transient scoring 50% or higher kilonova likeness in any of these planes was flagged for follow-up; the 11 candidates that emerged define the paper's sample. On the rates side, the load-bearing tool is the ATLAS recovery-efficiency simulation, which places 10,000 simulated light curves into the real observing history of the survey and counts how many produce the minimum seven detections on two or more nights required for a real ATLAS transient, giving a recovery efficiency of $\eta=0.009$ at 50 Mpc for the faintest LBV light curve; dividing the 11 observed LBVs by volume, time, and this efficiency yields the volumetric rates.

What would settle it

Rerun the ATLAS recovery-efficiency simulation with a sample of a dozen or more spectroscopically confirmed faint LBV light curves instead of the single one (AT 2020agp) used here; if the $\eta=0.009$ efficiency at 50 Mpc moves by an order of magnitude, the volumetric rate and the headline prediction of $4\pm2$ LBV outbursts per 500 deg$^2$ shift proportionally. The head-on test comes once LSST begins: count the fast-fading transients inside genuinely triggered O5 gravitational-wave skymap searches, and check whether a 500 deg$^2$, 4-day campaign at $m\approx25$ persistently yields roughly 2–6 such outbursts within 200–400 Mpc.

Watch

Extended reading notes

Core claim

None of the 11 fast-evolving transients that passed the kilonova selection criteria was a viable kilonova. Six were luminous blue variable (LBV) outbursts — two confirmed spectroscopically and four judged likely from their photometry — and the remainder were a Galactic cataclysmic variable, a sub-luminous Type Ia supernova with a prominent early-excess feature, an ultra-stripped supernova candidate, and other stellar or supernova-like sources. The paper's quantitative claim is that LBV eruptions are a significant but manageable contaminant: from 11 spectroscopically classified LBVs in the ATLAS 100 Mpc volume-limited sample it derives volumetric rates of $R = (6\pm3)\times10^{5}$ Gpc$^{-3}$ yr$^{-1}$ for faint outbursts ($M_{\rm peak}\simeq-11.8$) and $R = (1\pm0.4)\times10^{4}$ Gpc$^{-3}$ yr$^{-1}$ for bright ones ($M_{\rm peak}\simeq-15$). It converts these into the expectation that an LSST search reaching $m\approx25$ will find $4\pm2$ faint LBV outbursts per 500 deg$^2$ in a 4-day window within the 200–400 Mpc volumes typical of binary-neutron-star mergers in observing run O5, plus about $5\pm1$ bright ones out to 1 Gpc. The paper further claims the impostors can be rejected photometrically: at $\geq6$ days after peak, kilonova AT 2017gfo reddens in $r-i$ and $r-z$ while the LBV precursor to SN 2021qvw remains blue.

Load-bearing premise

The load-bearing premise is that the ATLAS recovery-efficiency simulation, anchored on a single faint LBV light curve with an efficiency of only $\eta=0.009$ at 50 Mpc, correctly measures how often faint LBV outbursts are detected; the derived volumetric rate and every predicted contamination number scale linearly with that efficiency.

Editorial extensions

If this is right

  • Untriggered kilonova searches will keep being dominated by impostors: within 200 Mpc the paper finds the contaminant rate exceeds the kilonova rate by one to two orders of magnitude, so pre-discovery forced photometry is mandatory before any candidate is believed.
  • LSST-era searches of O5 gravitational-wave skymaps can budget for the background: about 4 ± 2 faint LBV outbursts per 500 deg² in a 4-day window within 200–400 Mpc is small enough that LBVs will not swamp a typical search, but one- or two-detector events with skymaps of ~1000 deg² or more will be noticeably contaminated.
  • LBV impostors can be rejected without spectra by tracking colour: at ≥6 days after peak, the kilonova AT 2017gfo reddens in r-i and r-z while the SN 2021qvw LBV precursor stays blue, so multiband r-i-z follow-up settles the classification quickly.
  • The local volumetric rate of faint LBV eruptions is a few times the core-collapse supernova rate, which makes massive-star eruptions one of the most numerous classes of faint local transients and a population any complete local-volume census must contend with.

Reading between the lines

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

  • An automated 'repeat eruption at the same position' flag would remove most of this contamination class before any human review: the decisive evidence against nearly every LBV candidate here was a second outburst or pre-rise flicker in forced photometry, so a classifier that queries archival variability could suppress the 55% impostor fraction before telescope time is spent.
  • The headline '2–6 per 500 deg²' is best read as an order-of-magnitude estimate: the prediction scales linearly with the single-light-curve efficiency ($\eta = 0.009$), so measuring more faint-LBV light curves is the cheapest way to tighten every number in the paper.
  • The two-object colour comparison (AT 2017gfo versus the SN 2021qvw precursor) demonstrates a separation that a larger sample could calibrate into a quantitative decision boundary; the natural next step is multiband light curves of a handful of spectroscopically confirmed faint LBVs.
  • If LSST-era gravitational-wave follow-up operates at the Silver-strategy depth ($m \approx 25$), these numbers imply the first real kilonova may arrive buried among a few LBV impostors, making triage speed — not raw sensitivity — the practical bottleneck of the LSST era.
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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 / 4 minor

Summary. The paper reports a 3.14-year optical search for kilonova-like transients in Pan-STARRS data without gravitational-wave or gamma-ray burst triggers. Of 29,740 reported transients, 175 had host distances within 200 Mpc and discovery absolute magnitudes fainter than M = -16.5, and 11 were selected by a kilonova prediction algorithm as plausible candidates. Using Pan-STARRS, ATLAS, and ZTF forced photometry, the authors eliminate all 11 as kilonovae, attributing 55% of the sample to luminous blue variable (LBV) outbursts. From an ATLAS volume-limited sample they derive volumetric rates for faint and bright LBV outbursts, and they forecast that LSST-era searches of LIGO-Virgo-KAGRA O5 skymaps will find 4 +/- 2 faint LBV outbursts per 500 square degrees in a 4-day window within 200-400 Mpc, with about 5 +/- 1 brighter LBVs out to 1 Gpc. The paper concludes that LBV outbursts are manageable contaminants that can be identified photometrically.

Significance. If the rate estimates and contamination forecast are correct, this is a valuable empirical result for kilonova searches in the Rubin/LSST era. The paper's strengths include a clearly described multi-survey search, the use of forced photometry from three independent surveys, a transparent candidate-by-candidate elimination, public release of the photometric data, and a concrete prediction that can be tested by future observations. The central null result that none of the 11 fast-evolving candidates is a kilonova is well supported by the presented light curves and historical activity. However, the quantitative contamination forecast contains an arithmetic inconsistency with the paper's own rate formalism, and the faint-LBV rate rests on a very small recovery-efficiency simulation; these issues must be addressed before the prediction can be used for observational planning.

major comments (3)
  1. [Section 4.2, Eq. A1 and Table 2] The stated prediction of 4 +/- 2 faint LBV outbursts per 500 square degrees in a 4-day window within 200-400 Mpc does not reproduce from the paper's own equations. Using R_faint = (6 +/- 3) x 10^5 Gpc^-3 yr^-1, the shell volume (4*pi/3)[(0.4 Gpc)^3 - (0.2 Gpc)^3] = 0.235 Gpc^3, the sky fraction 500/41253 = 0.0121, and the time 4/365.25 yr = 0.01095 yr gives approximately 19 events, about five times the quoted 4 +/- 2. The bright-LBV estimate of 5 +/- 1 out to 1 Gpc is independently consistent with the same formula, so the problem is specific to the faint-LBV calculation. Because the conclusion in Section 5 that LBVs are 'not an overwhelming contaminant source' is based on the 4 +/- 2 number, this discrepancy is load-bearing. The authors should correct the calculation or explicitly identify any additional factor (e.g., a detection-efficiency correction or a magnitude-limited volume) that reduces the expectation to 4 +/- 2, and they should state whether the figure and abstract need corresponding revision.
  2. [Appendix A, Figure A1 and Table 2] The faint LBV volumetric rate is derived from a single simulated light curve (AT 2020agp, M_peak = -11.8) with a recovery efficiency of eta = 0.009 at 50 Mpc, applied to a sample of nine faint LBV events. Because R = N/(epsilon V T), the inferred rate is inversely proportional to eta, so even a modest change in the assumed light-curve shape, the 'minimum seven detections' recovery criterion, or the finite cadence of ATLAS would change the rate proportionally. The quoted uncertainty of 6 +/- 3 x 10^5 Gpc^-3 yr^-1 therefore likely underestimates the model uncertainty. Since the contamination forecast in Section 4.2 is directly proportional to this rate, the authors should add a sensitivity test that varies the faint LBV template and the recovery criterion, or at minimum state explicitly how the forecast scales with eta.
  3. [Section 4.2 and Figure 13] The contamination forecast is presented without an explicit definition of the plotted quantity or any stated LSST detection-efficiency factor. The text says the numbers are computed from the volumetric rates in Table 2 and that dating the explosion epoch to within four days makes them 'a reasonable estimate,' but it does not say whether a survey-efficiency correction, a magnitude cut, or a limiting-distance cut is included. If the y-axis of Figure 13 is a pure rate integral N = R V T (sky fraction), then at 400 Mpc the faint curve should give about 20 events per 500 deg^2 per 4 days, not 4 +/- 2. If the figure instead includes an implicit efficiency or apparent-magnitude cutoff, that factor must be stated so the figure can be reproduced.
minor comments (4)
  1. [Section 3.1 and Table 1] The paper reports that LBVs account for 55% of the 11 candidates, but only AT 2017dau and SN 2021qvw are spectroscopically confirmed LBVs; the other four are classified as LBVs from photometric behavior (multiple bursts, pre-rise activity, or flickering). The text is transparent about this, but the table and abstract could more explicitly distinguish 'spectroscopically confirmed LBVs' from 'likely LBVs based on photometry.'
  2. [Abstract and Section 5] The abstract quotes '2-6 massive stellar outbursts per 500 deg^2,' while Section 5 quotes '4 +/- 2 faint LBV outbursts per 500 deg^2.' These are consistent in range, but the abstract does not mention that the number refers to faint LBV-type outbursts specifically; clarifying this would avoid confusion.
  3. [Table 2] The rate entries are formatted as '60 +/- 30 x 10^4' and '1 +/- 0.4 x 10^4,' which is easy to misread. Using a consistent superscript notation such as '(6 +/- 3) x 10^5' would improve readability.
  4. [Throughout] Several typos and formatting inconsistencies appear, including 'Ligo-Virgo-Kagra' in the abstract, 'ATLAS100Mpc' in the abstract, 'Legacy Survey of Space and time,' and a missing full reference details for Huber et al. (2017). These do not affect the science but should be cleaned up in revision.

Circularity Check

0 steps flagged · score 0.0 of 10

No circularity: the LBV contamination forecast is an extrapolation of an independently measured ATLAS rate, not a reduction to its own inputs.

full rationale

The paper's central claims are (i) a null result for kilonovae among 11 fast-evolving transients, and (ii) a quantitative forecast of LBV contamination for LSST-era GW follow-up. Neither reduces to its inputs by construction. The kilonova prediction algorithm (Section 2.4) uses synthetic kilonova models from Nicholl et al. (2021) and contaminant templates only to flag candidates; the elimination of the 11 candidates is carried out with independent data (historical forced photometry, spectra, multi-survey light curves, recurrence of outbursts), so the null result is not an artifact of the template library. The LBV volumetric rates in Section 4.1 and Table 2 are measured from the ATLAS Local Volume Survey via Eq. A1, R = N/(epsilon V T), with the recovery efficiency eta obtained from an ATLAS-specific simulation (McBrien 2021) that is external to the fitted rates; the rate is not fitted to the target LSST contamination number. Section 4.2 then multiplies these measured rates by the O5 shell volume, sky fraction, and observing window, which is a legitimate extrapolation rather than a self-definitional prediction. The self-citations (e.g., Smartt et al. 2019; Fulton et al. 2023; Nicholl et al. 2021) are methodological context, not load-bearing uniqueness arguments. We do flag an apparent arithmetic inconsistency in Section 4.2: the quoted 4±2 faint LBV events per 500 deg^2 within 200-400 Mpc does not reproduce from Eq. A1 and Table 2 (6e5 Gpc^-3 yr^-1 x 0.235 Gpc^3 x 500/41253 x 4/365.25 yr ~ 19 events), while the 5±1 bright-LBV estimate is consistent; this is a correctness/consistency concern, not circularity, and does not affect the circularity score.

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

The paper's quantitative prediction rests on the ATLAS efficiency simulation (Appendix A) and on photometric classification of LBVs. No free parameters are fit to force the central result; the LBV rate is measured from ATLAS data. The kilonova selection model is a domain assumption inherited from prior work.

assumptions (3)
  • domain assumption The ATLAS efficiency simulation accurately models detection and human scanning of faint LBV outbursts.
    Appendix A: The faint LBV recovery efficiency is taken from the simulation; the volumetric rate and hence the contamination prediction scale inversely with this efficiency.
  • domain assumption The kilonova selection criteria (M > -16.5, D_L <= 200 Mpc, R_g <= 50 kpc) would capture most kilonovae that Pan-STARRS could detect.
    Section 2.3: These cuts are based on AT 2017gfo and theoretical models; if kilonovae can be brighter or farther, the null result would not constrain them.
  • domain assumption Photometric identification of LBV outbursts is reliable without spectra for most candidates.
    Section 3.1: Four of the six LBV contaminants are classified as plausible LBVs from photometric behavior (multiple outbursts, flickering) rather than spectra.

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Cite this review

Pith. "Pith review of Results from the Pan-STARRS Search for Kilonovae: Contamination by Massive Stellar Outbursts." pith.science (2026). https://pith.science/paper/5PCKJT6K

@misc{pith2026250607082,
  author       = {Pith},
  title        = {Pith review of: Results from the Pan-STARRS Search for Kilonovae: Contamination by Massive Stellar Outbursts},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/5PCKJT6K}},
  note         = {Machine review of arXiv:2506.07082}
}
read the original abstract

We present results from the Pan-STARRS optical search for kilonovae without the aid of gravitational wave and gamma-ray burst triggers. The search was conducted from 26 October 2019 to 15 December 2022. During this time, we reported 29,740 transients observed by Pan-STARRS to the IAU Transient Name Server. Of these, 175 were Pan-STARRS credited discoveries that had a host galaxy within 200 Mpc and had discovery absolute magnitudes M > -16.5. A subset of 11 transients was plausibly identified as kilonova candidates by our kilonova prediction algorithm. Through a combination of historical forced photometry, extensive follow-up, and aggregating observations from multiple sky surveys, we eliminated all as kilonova candidates. Rapidly evolving outbursts from massive stars (likely to be Luminous Blue Variable eruptions) accounted for 55% of the subset's contaminating sources. We estimate the rate of such eruptions using the ATLAS 100 Mpc volume-limited survey data. As these outbursts appear to be significant contaminants in kilonova searches, we estimate contaminating numbers when searching gravitational wave skymaps produced by the LIGO-Virgo-Kagra science collaboration during the Rubin era. The Legacy Survey of Space and time, reaching limiting magnitudes of m = 25, could detect 2-6 massive stellar outbursts per 500 deg^2 within a 4-day observing window, within the skymaps and volumes typical for binary neutron star mergers projected for Ligo-Virgo-Kagra Observing run 5. We conclude that while they may be a contaminant, they can be photometrically identified.

Figures

Figures reproduced from arXiv: 2506.07082 by the authors.

Figure 1
Figure 1. Tree diagram depicting the breakdown of transients detected by Pan￾STARRS throughout the Pan-STARRS Search for Kilonovae. Classification status refers to spectroscopic classification only. scores are averaged across all filters involved and normalised into a single “likelihood score” ranging between 0% and 100% for each 𝑀 − 𝑀¤ locus plot. In this kilonova search, an input that scored a kilonova resemblance of 50% or… view at source ↗
Figure 2
Figure 2. The discoveries of transients, mostly supernovae, are summarised in these plots: (A) histogram of discovery apparent mag. (B) histogram of discovery absolute mag. (C) histogram of brightest apparent mag. (D) histogram of brightest absolute mag. (E) histogram of distances using 𝐻0. (F) histogram of projected offsets from host galaxy centres. (G) bar chart of host morphologies. (H) bar chart of spectral classification… view at source ↗
Figure 3
Figure 3. 𝑀 − 𝑀¤ locus plot of peak brightness versus decline rate in the 𝑤PS filter for the 11 fast-evolving transients identified in the Pan-STARRS sample. Our full kilonovae model distribution has been converted into a probability density function using a Gaussian kernel density estimation. It is represented by contours, where the area enclosed by darker lines depicts a higher concentration of models. Overlaid is known kil… view at source ↗
Figures from the paper (9 more)
Figure 4
Figure 4. Figure 4: The 𝑤PS filter light curves of the fastest outburst measured for the 11 fast-evolving transients. Phase is with respect to the outburst peak measured from the combined Pan-STARRS and ATLAS forced photometry if ATLAS data were available. The constructed 𝑤PS filter light…
Figure 5
Figure 5. Figure 5: A mosaic of the 11 fast-evolving transients within their hosts. These GRB colour composites were created using the 𝑤PS target image obtained for each transient at their brightest epoch and 𝑔PS and 𝑖PS reference images from the Pan-STARRS 3𝜋 survey. Each composite is ce…
Figure 7
Figure 7. Figure 7: Top panel: Pan-STARRS photometry of the first 14 days of the SN 2021qvw outburst. Bottom panel: The full Pan-STARRS 3𝜎 light curve of SN 2021qvw displaying the initial outburst and the later SN explosion. Square markers on the 𝑤PS filter represent synthetic values deri…
Figure 9
Figure 9. Figure 9: The full ATLAS + Pan-STARRS light curve for AT 2021thr. Data points with downward-pointing arrows represent limits at 3𝜎. The dashed lines highlight the possible undulations observed in both telescope systems. light curve, with a more gradual fade overall (1.6 mag fade…
Figure 8
Figure 8. Figure 8: Top panel: The Pan-STARRS 𝑔𝑟 𝑖𝑧𝑤PS and ATLAS 𝑐𝑜A filter light curve for AT 2021sjs. Data points with downward-pointing arrows represent limits at 3𝜎. The dashed lines highlight the fast-decaying trend. Bottom panel: A 𝑤PS filter reference image constructed on MJD 57122…
Figure 10
Figure 10. Figure 10: The Pan-STARRS 𝑤PS filter light curve for AT 2021yll. Data points with downward-pointing arrows represent limits at 3𝜎. The high am￾plitude, short-scale flickering occurred approximately 300 days after the Pan￾STARRS discovery. The grey-shaded region highlights the fa…
Figure 11
Figure 11. Figure 11: Top panel: The full ATLAS + Pan-STARRS light curve for AT 2021aanx. Data points with downward-pointing arrows represent lim￾its at 3𝜎. The dashed lines highlight the fast-evolving trend. Bottom panel: The combined 𝑤PS+ 𝑜ATLAS filter light curve of AT 2021aanx plotted …
Figure 12
Figure 12. Figure 12: The Pan-STARRS 𝑤PS filter light curve for AT 2022kjm displaying the fast outburst measured at discovery (shaded in grey) and the low-level ac￾tivity observed three years prior. Data points with downward-pointing arrows represent limits at 3𝜎. The fast outburst is a co…
Figure 13
Figure 13. Figure 13: The predicted number of LBV events per 500 deg2 per 4-day pe￾riod, determined from the maximum and minimum volumetric rates depicted in [PITH_FULL_IMAGE:figures/full_fig_p015_13.png]

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Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.