Pith. sign in

REVIEW 3 major objections 5 minor 3 cited by

A ZTF Search for Circumstellar Debris Transits in White Dwarfs: Six New Candidates, one with Gas Disk Emission, identified in a Novel Metric Space

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

Pith's one-line read Six white dwarfs with transiting planetary debris are found by ranking photometric variability and confirming metal pollution in follow-up spectra, including one object whose transit reddens the starlight.

desk verdict A useful catalog paper with a promising but under-supported reddening claim; the six candidates mostly hold up, but the WD J1013-0427 color-dependence needs a proper error analysis. read the letter →

arxiv 2502.05502 v2 pith:UBA4HML5 submitted 2025-02-08 astro-ph.SR astro-ph.EP

classification astro-ph.SRastro-ph.EP
keywords whitedwarfstransitingdebrisdisksmetalpollutionZwickyTransientFacilityvariabilitymetricscircumstellargasdiskaccretionrates
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 claims to have found six new white dwarfs whose light is dimmed by transiting debris from disrupted planetary bodies, growing the known sample from eight to fourteen systems. The search works by ranking roughly 56,000 white dwarfs within 500 parsecs by a photometric variability score, then using a two-axis metric space built from von Neumann statistics and Pearson skew to pick out light curves with the irregular, dip-like shape typical of debris transits. One candidate, WD J1013−0427, stands out: its transit is shallower in red light than in blue light, the first time reddening during a debris transit has been seen, which the authors interpret as extinction by dust grains smaller than about 0.3 micrometres. The same star shows double-peaked metal emission lines from an eccentric gas disk inside the Roche limit, making it the first system with both a gas disk and transiting debris. The paper also reports that transiting-debris white dwarfs tend to accrete metal at higher rates than the general polluted-white-dwarf population.

What carries the argument

The load-bearing novelty is a two-dimensional metric space built from the von Neumann statistic, $\eta = (\delta/\sigma)^2$, which measures the randomness of a time series, and the Pearson second skew coefficient, $S_P = (e_m - m)/\sigma$, which distinguishes dimming from brightening events. Transiting-debris systems cluster in the third quadrant ($\eta \lesssim 1.8$, $S_P < 0$), which is sparsely populated by other variable white dwarfs, so the quadrant acts as a quick filter before spectroscopy. The candidates are pulled from the top 1% of a combined variability rank $R = V_G + V_{\mathrm{ZTF}}$ computed from Gaia and ZTF photometry after polynomial detrending and median-absolute-deviation normalization. Long-duration dips are fit with an asymmetric hyperbolic secant function, and the color-dependent depths of WD J1013−0427 are interpreted with Mie-scattering radiative transfer models and an optically-thick-disk covering-fraction model.

What would settle it

Continued high-cadence monitoring of the six candidates over several years: a candidate whose dips never recur, or whose Lomb-Scargle analysis later reveals a stable period consistent with binary rotation or pulsation, would fail the transiting-debris classification. For WD J1013−0427 specifically, a second long dip observed simultaneously in $g$ and $r$ with no color difference would falsify the small-grain extinction interpretation.

Watch

Extended reading notes

Core claim

The paper's central claim is that six white dwarfs—WD J0923+7326, WD J1302+1650, WD J1650+1443, WD J1944+4557, WD J1237+5937, and WD J1013−0427—are strong candidates for hosting transiting planetary debris, on the evidence of high photometric variability in ZTF and Gaia light curves combined with metal absorption lines in follow-up spectra. For WD J1013−0427 the variability shows a statistically significant color dependence: the transit depth in the ZTF-$r$ band is shallower than in the $g$ band, which the authors read as the first observed reddening during a debris transit and model as extinction by small dust grains (radius $\lesssim 0.3\,\mu\mathrm{m}$). The same object displays double-peaked Ca II, O I, and Mg I emission lines, which a Keplerian disk model fits with an optically thick, eccentric gas disk extending roughly 0.2 to 0.5 solar radii from the star. As a population statement, the paper finds that transiting-debris systems have higher inferred metal accretion rates than typical metal-polluted white dwarfs.

Load-bearing premise

Candidates are certified as transiting debris on the strength of aperiodic photometric variability plus metal absorption lines, with no debris orbital period measured for any of the six; if the variability of even one object turns out to be rotation, pulsation, or binarity, that object's candidacy collapses.

Editorial extensions

If this is right

  • The known census of transiting-debris white dwarfs grows from eight to fourteen systems, roughly doubling the sample available for population studies.
  • WD J1013−0427 offers the first empirical handle on the grain-size distribution of the occulting material; if the reddening interpretation holds, grains $\lesssim 0.3\,\mu\mathrm{m}$ must survive at wide orbits where they are not sublimated.
  • The $\eta$–$S_P$ quadrant filter is a cheap, survey-ready way to shortlist transiting-debris candidates in large time-domain datasets, a use the authors explicitly expect in future surveys.
  • The higher accretion rates of transiting-debris systems, if confirmed, could serve as a selection criterion for finding more such systems in large spectroscopic datasets.
  • Four of the six candidates vary on timescales of months to years, suggesting a subclass of long-timescale debris activity that surveys with short temporal baselines would miss.

Reading between the lines

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

  • If the reddening-transit interpretation survives, WD J1013−0427 becomes a testbed for dust survival physics: sub-micron grains normally sublimate quickly near a 21,900 K white dwarf, so their inferred presence requires either a very recent collisional event or a shielding mechanism not discussed in the paper.
  • The paper's naive occurrence-rate lower bound of about 0.03% sits more than an order of magnitude below theoretical predictions; closing that gap may require accounting for long dormant phases, which would bias surveys toward catching only the currently active systems.
  • The same $\eta$–$S_P$ metric space could be turned around and applied to other variable-star classes—young stellar objects, post-common-envelope binaries, or variable planetary nebulae—wherever dip-shaped or outburst-shaped light curves define the class.
  • A second transit of WD J1013−0427, if caught by an all-sky survey with both $g$- and $r$-band coverage, would directly test whether the long dip is a single collisional event or a recurring disk feature with a period of at least 20 years.
Share X Bluesky LinkedIn Reddit HN

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. The paper reports a systematic search for white dwarfs with transiting circumstellar debris, combining the Gaia eDR3 white dwarf catalog with ZTF DR10 photometry for sources within 500 pc. The authors define a variability rank from Gaia and ZTF metrics, introduce a two-dimensional metric space based on the von Neumann statistic and Pearson skew, select the top 1% most variable objects, visually screen their light curves, and follow up promising candidates with optical spectroscopy and high-speed photometry. They present six new transiting-debris candidates, report that three show short-timescale dips in high-speed light curves, and identify WD J1013-0427 as especially notable because it allegedly shows a color-dependent transit (reddening) and double-peaked metal emission lines from an eccentric optically thick gas disk. They also compare accretion rates of transiting-debris systems to the general metal-polluted white dwarf population and report a serendipitous long-duration outbursting AM CVn system.

Significance. If the results hold, the paper would substantially grow a rare class of objects from eight published systems to fourteen candidates, and WD J1013-0427 would be the first white dwarf debris system showing both a color-dependent transit and a gaseous debris disk. The search methodology, including the eta-S_P metric space and systematic recovery of all previously known systems, is a useful contribution for future surveys. The gas-disk modeling and the accretion-rate comparison are also valuable. However, the most novel physical claim, the first reddening during a debris transit and the inferred small dust grain population, rests on a statistical comparison of transit depths whose uncertainties are not established. The candidate catalog itself remains largely defensible, but the headline discovery needs stronger support.

major comments (3)
  1. [§4.1.6, §5.1, Figs. 9–10] The claim that WD J1013-0427 shows a statistically significant color-dependent transit is not established. The inferred depths (D_ZTF-g=0.296, D_ATLAS-c=0.218, D_ZTF-r=0.166, D_ATLAS-o=0.166) come from AHS fits to sparse, multi-year ZTF and ATLAS light curves, but the text never states the uncertainty on each depth, how errors are propagated from the fits in Fig. 9, or the significance level of the g-minus-r difference. Figure 10 explicitly says the authors suspect underestimation of the depth errors and therefore show 2-sigma error bars, which contradict the unqualified 'statistically significant' language in §4.1.6. The light curves are likely affected by correlated systematics from forced photometry, weather, and calibration; least-squares fit errors will underestimate the true uncertainty. Because the reddening interpretation, the small-grain radius inference, and the 'first reddening during transit' claim all rest on this single comparison, the authors must provide a robust noise model or resampling-based uncertainty estimate and report the significance quantitatively. If the depth difference is not significant, the headline physical discovery is unsupported, even though the six-candidate catalog would remain intact.
  2. [§4.1.3 (WD J1650+1443)] The candidate status of WD J1650+1443 is much weaker than the paper's summary suggests. The text states that its variability rank is dominated by the Gaia metric V_G=11.5 while the ZTF metric is only V_ZTF=1.9, which is not strongly variable compared with similar objects, and that no variability is seen in the CHIMERA light curves. Since the selection rationale is 'metal pollution along with high photometric variability,' this object does not currently satisfy the variability criterion. The possible explanation of a quiescent phase in transiting debris systems is plausible, but because Gaia epochal photometry is unavailable, the high V_G could also be an artifact. The paper should either present this object as a lower-confidence candidate or clearly separate the spectroscopic evidence from the currently non-detected photometric variability.
  3. [§4.1.4 (WD J1944+4557)] For WD J1944+4557, the text reports that the Ca II K absorption cannot be reproduced by photospheric models and that the absorption is likely circumstellar rather than photospheric. This weakens the 'metal pollution' confirmation that is used to classify the object as a transiting-debris candidate. The short-timescale dips and sporadic variability provide independent photometric evidence, but the manuscript should explicitly state that this candidate lacks confirmed photospheric metals and should not be grouped with the other candidates without this caveat. The current wording in §4, which says 'the metal pollution along with the high photometric variability strongly indicates the transiting debris nature of these white dwarfs,' is too strong for this object.
minor comments (5)
  1. [§5.1, Fig. 10] The caption of Figure 10 says 'Suspecting underestimation of the inferred depth errors' while the main text asserts statistical significance; this contradiction must be resolved in revision, ideally with a quantitative significance statement.
  2. [Appendix A] The paper acknowledges an incorrect astrometric excess-noise cut that excludes about 5,171 sources, or roughly 4% of the sample. This is honestly disclosed, but the main text should briefly mention this limitation when stating the sample size, since a small number of transiting-debris candidates could have been missed.
  3. [Throughout] There are several typographical errors that should be corrected, including 'duraration' (§5.1.1), 'Terial restrial' (§4.1.6), 'genarate' (§5.3), 'abundnaces' (§6), and 'V on Neumann' (§2.6).
  4. [§2.6] The description of the eta-S_P metric space as a 'novel discovery tool' should be tempered, since the third quadrant was identified retrospectively using known transiting-debris systems and then used as a prioritization aid rather than as the sole discovery criterion.
  5. [Table 5] The accretion rates are reported without statistical errors; the text explains that the true uncertainties may be larger than the abundance uncertainties, but it would be helpful to state this caveat directly in the table caption.

Circularity Check

1 steps flagged · score 2.0 of 10

Candidate discovery is self-contained and independently evidenced; only the eta–SP metric-space validation is mildly self-referential because third-quadrant preference was applied before the metric's discovery power was asserted.

  1. other [Section 2.6, with the selection preference restated in Section 4]
    "The transiting debris systems, with irregular dip-like variability, predominantly occupy the third quadrant (lower left) in this space. Figure 2 also includes the new candidates found in this work, details about which shall be discussed later in this paper (§4.1). We see that the quadrant containing the transiting debris candidates is less contaminated by other kinds of variables. This suggests that the η–SP metric space can help with more efficient identification of white dwarfs with transiting debris-like light curves."

    The quadrant was defined retrospectively from known transiting-debris systems, and the new candidates were preferentially selected from the same quadrant: “we also checked the position of the object in the η–SP space and gave preference to objects lying in the third quadrant.” Therefore the new candidates' placement in that quadrant, and the assertion that the quadrant is ‘less contaminated’ and that the metric space is validated, is partly constructed by the selection rather than an independent test. This is a mild, non-fatal circularity because the six candidate claims still rest on independent ZTF variability and metal-line spectroscopy; the metric-space preference was only prioritization, not proof.

full rationale

The central claims do not reduce to their inputs. The six candidates were chosen from the top 1% variability rank using Gaia/ZTF metrics, visually inspected for irregular aperiodic variability, and spectroscopically confirmed as metal-polluted white dwarfs; this chain is independent of the target conclusion. The first-reddening claim for WD J1013-0427 is a fitted AHS depth comparison plus a radiative-transfer interpretation, not a prediction built into the input; its weakness is statistical (the paper itself suspects underestimated depth errors) rather than circular. WD J1944+4557's possibly circumstellar Ca II line is an acknowledged interpretation issue, not circularity. The only mildly self-referential element is the eta-SP quadrant: it was calibrated on known systems and then used to prioritize follow-up, so using the new candidates' quadrant positions to validate the metric space is not an independent out-of-sample test. Overall, the search is self-contained against external benchmarks, including recovery of all eight previously known transiting debris systems, so the appropriate finding is minor circularity rather than a fatal reduction.

Assumptions & free parameters 6 free parameters · 8 assumptions · 2 invented entities

The paper's main claims rest on a series of fitted model parameters and standard astrophysical assumptions. The selection thresholds and boundary of the eta-SP quadrant are chosen by hand; the transit depths, grain size parameters, and gas disk parameters are fitted to observations. The interpretation of metal pollution as debris accretion and the accretion-diffusion equilibrium are adopted from prior literature. No new theoretical entities are introduced beyond the inferred circumstellar disks and grains, both of which have direct observational handles.

free parameters (6)
  • Top 1% variability rank threshold R = 560 sources
    The sample of interest is defined as the sources with the top 1% highest variability rank R after detrending; this cut is chosen by hand and determines which objects are considered for follow-up (Section 2.5).
  • eta-SP quadrant boundary = eta < 1.9, S_P < 0
    Objects with eta < 1.9 and negative Pearson skew are preferentially selected as transiting debris candidates; the boundary is based on the location of previously known systems and new candidates (Figure 2, Section 2.6).
  • AHS transit model parameters (depth, phi1, phi2) = e.g., WD J1302+1650 depth about 20%, WD J1237+5937 ingress 25 d and egress 117 d
    The long-timescale dips are fit with the asymmetric hyperbolic secant function (Eq. 8) to infer depths and ingress/egress timescales; these fitted values support the long-timescale variability claims (Figure 7, Sections 4.1.2 and 4.1.5).
  • Dust grain size parameters (r_max or r_eff) and refractive index choices = best match r_max around 0.2-0.3 micron (power law), r_eff below 0.15 micron (Hansen); n=1.7+0.03i (Si-like) or 2+2.5i…
    The small-grain claim is based on comparing observed r-band normalized transit depths with models over a grid of grain size parameters and two refractive indices; a heuristic best-match is chosen, not a formal fit (Section 5.1.1).
  • Gas disk model parameters: e, a_in, a_out, phi, log C1, log C2, alpha, i, v_c = e=0.27, a_in=19 R_WD, a_out=48 R_WD, i=1.38 rad (about 79 deg), alpha=-0.37
    The double-peaked Ca II line is fit with an eccentric Keplerian disk model via MCMC; these fitted parameters support the claim that the gas disk is compact, eccentric, and nearly edge-on, though degeneracies are acknowledged (Table 6, Section 5.2).
  • Interstellar reddening E(B-V) = 0.005 to 0.062 mag for the candidates
    E(B-V) is a free parameter in the spectral and photometric atmosphere fits; it affects the derived stellar parameters and abundances but is not central to the transit claim (Section 4.1).
assumptions (8)
  • domain assumption Metal pollution in white dwarfs is produced by accretion of disrupted planetary debris.
    This standard interpretation underlies the link between metal absorption lines and transiting debris (Section 1).
  • domain assumption Accretion-diffusion equilibrium: accretion rate equals surface diffusion rate for each metal.
    Used to compute accretion rates from photospheric abundances (Section 4.1).
  • domain assumption Unseen metals are scaled to bulk Earth abundance ratios relative to Ca or Mg.
    Adopted from Allègre et al. (2001) and Zuckerman et al. (2010) to estimate total accretion rates (Section 4.1).
  • ad hoc to paper The variability metrics V_G and V_ZTF, after polynomial detrending and MAD normalization, rank variability independent of magnitude.
    The detrending and normalization procedures are defined in this paper; the top 1% cut then selects the sample (Section 2.4).
  • ad hoc to paper The dust is optically thin and uniformly covers the white dwarf disk (Model 1), or the disk is optically thick with power-law optical depth (Model 2).
    These radiative transfer models are assumed to interpret the color-dependent transit depths; the paper finds the optically thin model more suitable (Section 5.1).
  • ad hoc to paper The gas disk is Keplerian, thin, optically thick for Ca II, with constant calcium column density and photon density proportional to r^-alpha.
    These assumptions underlie the emission line model; the paper notes constant N_Ca may not be ideal (Section 5.2).
  • domain assumption Grain size distribution follows a power law with p=3.5 or a Hansen distribution with nu_eff=0.1 micron.
    Taken from Mathis et al. (1977) and Hansen (1971) via Croll et al. (2014) and Hallakoun et al. (2017) (Section 5.1.1).
  • domain assumption ZTF and Gaia photometric quality cuts remove contaminated sources; manual image inspection completes decontamination.
    Selection relies on the quality cuts and visual inspection (Section 2).
invented entities (2)
  • Eccentric optically thick gas disk around WD J1013-0427 independent evidence
    purpose: Explains the double-peaked Ca II, O I, and Mg I emission lines and the line profile asymmetry
    The gas disk is inferred from emission lines observed at five epochs; it is a physical interpretation of direct spectroscopic evidence, not a purely ad hoc entity. Its parameters are constrained by MCMC but with degeneracies.
  • Population of small dust grains (radius below 0.3 micron) in the occulting material around WD J1013-0427 independent evidence
    purpose: Explains the reddening (shallower r-band than g-band depth) during the long transit
    The color-dependent transit depths provide the observational handle; future multi-band photometry can test the small-grain interpretation.

how reviews work

0 comments
Cite this review

Pith. "Pith review of A ZTF Search for Circumstellar Debris Transits in White Dwarfs: Six New Candidates, one with Gas Disk Emission, identified in a Novel Metric Space." pith.science (2026). https://pith.science/paper/UBA4HML5

@misc{pith2026250205502,
  author       = {Pith},
  title        = {Pith review of: A ZTF Search for Circumstellar Debris Transits in White Dwarfs: Six New Candidates, one with Gas Disk Emission, identified in a Novel Metric Space},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/UBA4HML5}},
  note         = {Machine review of arXiv:2502.05502}
}
abstract

White dwarfs (WDs) showing transits from orbiting planetary debris provide significant insights into the structure and dynamics of debris disks. This is a rare class of objects with only eight published systems. In this work, we perform a systematic search for such systems within 500 pc in the Gaia-eDR3 catalog of WDs using the light curves from the Zwicky Transient Facility (ZTF) and present six new candidates. Our selection process targets the top 1% most photometrically variable sources identified using a combined variability metric from ZTF and Gaia eDR3 photometry, boosted by a metric space we define using von Neumann statistics and Pearson-Skew as a novel discovery tool to identify these systems. This is followed by optical spectroscopic observations of visually selected variables to confirm metal pollution. Four of the six systems show long-timescale photometric variability spanning several months to years, resulting either from long-term evolution of transit activity or dust and debris clouds at wide orbits. Among them, WD J1013-0427 shows an indication of reddening during the long-duration dip. Interpreting this as dust extinction makes it the first system to indicate an abundance of small dust grains (radius $\lesssim$$0.3~{\rm \mu m}$) in the occulting material. The same object also shows metal emission lines that map an optically thick eccentric gas disk orbiting within the star's Roche limit. For each candidate, we infer the abundances of the photospheric metals and estimate accretion rates. We show that transiting debris systems tend to have higher inferred accretion rates compared to the general population of metal-polluted WDs. Growing the number of these systems will further illuminate such comparative properties in the near future. Separately, we also serendipitously discovered an AM CVn showing a very long-duration outburst $-$ only the fourth such system to be known.

Figures

Figures reproduced from arXiv: 2502.05502 by the authors.

Figure 1
Figure 1. Summary of the metrics detrending and selection cut. Left and Middle panels: The Vδ and Vσ for the ZTF objects as a function of their respective magnitudes for g (left) and r (middle) bands. The dashed line shows the eight-degree polynomial fit to the overall trend with magnitude. The solid line shows the individual top 1% cuts with the exponential fit to the trend in the metric spread (with magnitude, after subtrac… view at source ↗
Figure 2
Figure 2. Position of the ZTF light curves in the η–SP space for all the white dwarfs within top 1% R (orange points), and the known variable types within that list: Binaries (green circles), Pulsators (black circles), CVs (brown points), and the previously known (blue points and triangles) and new candidate (red stars) transiting de￾bris systems. The transiting debris systems tend to lie in the third quadrant (η<1.9 and SP <… view at source ↗
Figure 3
Figure 3. The ZTF light curves for the new transiting debris can￾didates and the long-duration outbursting AM CVn. We present the light curves from a more recent ZTF data release (DR21, span: 2018 March to 2024 February), but we mark the end of DR10, which rep￾resents the portion of the light curves that has been used for the sample selection. spectroscopic observations of seven highly promising candi￾dates, primarily using D… view at source ↗
Figures from the paper (14 more)
Figure 4
Figure 4. Figure 4: Position of the white dwarfs in Gaia CMD. The same presentation scheme as in [PITH_FULL_IMAGE:figures/full_fig_p009_4.png]
Figure 5
Figure 5. Figure 5: The spectra of the new transiting debris candidates (top six panels) and the AM CVn (bottom panel). Out of the several observations, only the best signal-to-noise spectrum is shown here. For each of the transiting debris candidates, we also over-plot the best-fit white…
Figure 6
Figure 6. Figure 6: The follow-up high-speed photometric light curves for the five new transiting debris candidates. Three of the six candidates: WD J0923+7326, WD J1302+1650, and WD J1944+4557 show clear short timescale dips and transits, strongly suggestive of ongoing debris activity. T…
Figure 7
Figure 7. Figure 7: The AHS (Equation 8) fit to the ZTF light curves of WD J1302+1650 and WD J1237+5937. The inferred parameters, namely the transit depth, epoch of transit, and the ingress and egress durations (in days) have been provided in the figure. third quadrant of the η–SP space. …
Figure 8
Figure 8. Figure 8: ZTF, ATLAS, and CRTS (last six seasons for ease of presentation) light curves for WD J1013−0427. For the purpose of this figure, the ATLAS data has been binned for better visualization of the dip. The two transit marks show the median ZTF-r and g band magnitudes for th…
Figure 9
Figure 9. Figure 9: The light curves of WD J1013−0427 fit with Equation 8. Top panel: A combined fit of the data from all the surveys to obtain the overall transit shape. Central four panels: The fit to the data from ZTF and ATLAS individually. The parameters derived from the combined fit…
Figure 10
Figure 10. Figure 10: The observed (black points) and analytic (Equation 12, colored lines) transit depths relative to that of ZTF-r for Si-like (left panel) and Fe-like (right panel) grains for the transits of WD J1013−0427 shown in [PITH_FULL_IMAGE:figures/full_fig_p019_10.png]
Figure 11
Figure 11. Figure 11: The dust column density estimations from the observed median transit depths over a range of grain-size parameters for Si-like (left panel) and Fe-like (right panel) grains for the transits of WD J1013−0427 shown in [PITH_FULL_IMAGE:figures/full_fig_p019_11.png]
Figure 12
Figure 12. Figure 12: The observed (black points) and analytic (Equation 12, colored lines) transit depths excess to that of ZTF-r for two rep￾resentative values of τr,0 and four integer values of α. As with [PITH_FULL_IMAGE:figures/full_fig_p021_12.png]
Figure 13
Figure 13. Figure 13: The emission lines detected in the spectra of WD J1013−0427: magnesium (Mg I, left), oxygen (O I, center), and calcium (Ca II, right). In the panel for Mg I, we also show the detected Si II absorption around a He line to caution the readers not to confuse the net ‘tri…
Figure 14
Figure 14. Figure 14: The MCMC fit of the disk model to the model￾subtracted Ca-II 8662 A emission line profile (from the LRIS ob- ˚ servation on 23rd May 2023) for WD J1013−0427. The velocity vector is then given by: v = vK(r) p 1 + e 2 + 2e cos(β) [− sin(β)ˆx + {e + cos(β)}yˆ] (23) where…
Figure 15
Figure 15. Figure 15: The corner plot for the MCMC run discussed in Section 5.2. Satisfactory constraints are obtained for the three main parameters: eccentricity, e, and the inner and outer semi-major axes, ai and ao. riod. The morphology of the overdense region may then govern the ingres…
Figure 16
Figure 16. Figure 16: Inferred accretion rate as a function of temperature for the transiting debris systems in comparison with the pool of metal polluted white dwarfs from MWDD (Dufour et al. 2017). ‘Dusty’ stands for objects with detected infrared excess. The transiting de￾bris systems t…
Figure 17
Figure 17. Figure 17: Spectral energy distributions of the six new transiting debris candidates. WD J0923+7326 appears to have infrared excess but close inspection shows the possibility of significant blending with two nearby sources. The others either do not have available mid-infrared ph…

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 5 citations worldwide. Full citation record

  1. A Search for Transiting Exocomets in TESS Sectors 1-26

    astro-ph.EP 2025-08 conditional novelty 6.0 of 10

    A TESS primary mission search finds five new exocomet-like transit candidates and estimates a 2.64e-4 per star per year occurrence rate, concluding such transits are rare at 0.1% to 1% depths.

  2. Silicate mineralogy and bulk composition of exoplanetary material in polluted white dwarfs

    astro-ph.EP 2025-07 conditional novelty 6.0 of 10

    New ultraviolet abundances for two white dwarfs, combined with a re-analysis of eight systems, support a tentative correlation between the Mg/Si ratio of accreted exoplanetary material and whether its dust is olivine-...

  3. Bounding destruction timescales of minor planets orbiting white dwarfs with the sesquinary catastrophe

    astro-ph.EP 2025-07 conditional novelty 6.0 of 10

    Minor planets orbiting white dwarfs at 1-4 Roche radii can be destroyed by their own returning impact ejecta on timescales of 10^2 to 10^5 years.

Reference graph

Works this paper leans on

123 extracted references · 14 canonical work pages · cited by 3 Pith papers

  1. [1]

    2001, Earth and Planetary Science Letters, 185, 49, doi: 10.1016/S0012-821X(00)00359-9 Astropy Collaboration, Robitaille, T

    All`egre, C., Manh`es, G., & Lewin, ´E. 2001, Earth and Planetary Science Letters, 185, 49, doi: 10.1016/S0012-821X(00)00359-9 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ocz, B. M., et al. 2018a, AJ, 156, 123, doi: 10.3847/1538-3881...

  2. [2]

    T., Dhillon, V

    Aungwerojwit, A., G¨ansicke, B. T., Dhillon, V . S., et al. 2024, MNRAS, 530, 117, doi: 10.1093/mnras/stae750

  3. [3]

    B., & Bildsten, L

    Bauer, E. B., & Bildsten, L. 2019, ApJ, 872, 96, doi: 10.3847/1538-4357/ab0028 19 http://vizier.cds.unistra.fr/vizier/sed/ B´edard, A., Bergeron, P., Brassard, P., & Fontaine, G. 2020, ApJ, 901, 93, doi: 10.3847/1538-4357/abafbe

  4. [4]

    C., Kulkarni, S

    Bellm, E. C., Kulkarni, S. R., Graham, M. J., et al. 2019, PASP, 131, 018002, doi: 10.1088/1538-3873/aaecbe

  5. [5]

    R., Kong, A

    Bhattacharjee, S., Kulkarni, S. R., Kong, A. K. H., et al. 2025, PASP, 137, 024201, doi: 10.1088/1538-3873/ada702

  6. [6]

    G., Bonsor, A., & Malamud, U

    Brouwers, M. G., Bonsor, A., & Malamud, U. 2022, MNRAS, 509, 2404, doi: 10.1093/mnras/stab3009

  7. [7]

    2025, Nature Astronomy, doi: 10.1038/s41550-024-02446-x

    Budaj, J., Bernhard, K., Jones, D., & Munday, J. 2025, Nature Astronomy, doi: 10.1038/s41550-024-02446-x

  8. [8]

    C., Magnier, E

    Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv e-prints, arXiv:1612.05560. https://arxiv.org/abs/1612.05560

Show all 123 references
  1. [9]

    M., Stauffer, J., Baglin, A., et al

    Cody, A. M., Stauffer, J., Baglin, A., et al. 2014, AJ, 147, 82, doi: 10.1088/0004-6256/147/4/82 30 BHATTACHARJEE ET AL. Figure 17.Spectral energy distributions of the six new transiting debris candidates. WD J0923+7326 appears to have infrared excess but close inspection show...

  2. [10]

    2014, ApJ, 786, 100, doi: 10.1088/0004-637X/786/2/100

    Croll, B., Rappaport, S., DeV ore, J., et al. 2014, ApJ, 786, 100, doi: 10.1088/0004-637X/786/2/100

  3. [11]

    2019, MNRAS, 488, 2503, doi: 10.1093/mnras/stz1759

    Koester, D. 2019, MNRAS, 488, 2503, doi: 10.1093/mnras/stz1759

  4. [12]

    H., Kilic, M., Faedi, F., et al

    Debes, J. H., Kilic, M., Faedi, F., et al. 2012, ApJ, 754, 59, doi: 10.1088/0004-637X/754/1/59

  5. [13]

    H., & Sigurdsson, S

    Debes, J. H., & Sigurdsson, S. 2002, ApJ, 572, 556, doi: 10.1086/340291

  6. [14]

    D., Andrews, J

    Decleir, M., Gordon, K. D., Andrews, J. E., et al. 2022, ApJ, 930, 15, doi: 10.3847/1538-4357/ac5dbe

  7. [15]

    Dennihy, E., Farihi, J., Fusillo, N. P. G., & Debes, J. H. 2020a, ApJ, 891, 97, doi: 10.3847/1538-4357/ab7249

  8. [16]

    2020b, ApJ, 905, 5, doi: 10.3847/1538-4357/abc339

    Dennihy, E., Xu, S., Lai, S., et al. 2020b, ApJ, 905, 5, doi: 10.3847/1538-4357/abc339

  9. [17]

    S., Marsh, T

    Dhillon, V . S., Marsh, T. R., Stevenson, M. J., et al. 2007, MNRAS, 378, 825, doi: 10.1111/j.1365-2966.2007.11881.x

  10. [18]

    J., Djorgovski, S

    Drake, A. J., Djorgovski, S. G., Mahabal, A., et al. 2009, ApJ, 696, 870, doi: 10.1088/0004-637X/696/1/870

  11. [19]

    2017, in Astronomical Society of the Pacific Conference Series, V ol

    Dufour, P., Blouin, S., Coutu, S., et al. 2017, in Astronomical Society of the Pacific Conference Series, V ol. 509, 20th European White Dwarf Workshop, ed. P. E. Tremblay, B. Gaensicke, & T. Marsh, 3, doi: 10.48550/arXiv.1610.00986

  12. [20]

    2010, ApJ, 719, 803, doi: 10.1088/0004-637X/719/1/803

    Dufour, P., Kilic, M., Fontaine, G., et al. 2010, ApJ, 719, 803, doi: 10.1088/0004-637X/719/1/803

  13. [21]

    2016, NewAR, 71, 9, doi: 10.1016/j.newar.2016.03.001

    Farihi, J. 2016, NewAR, 71, 9, doi: 10.1016/j.newar.2016.03.001

  14. [22]

    T., & Koester, D

    Farihi, J., G¨ansicke, B. T., & Koester, D. 2013, Science, 342, 218, doi: 10.1126/science.1239447

  15. [23]

    T., Wyatt, M

    Farihi, J., G¨ansicke, B. T., Wyatt, M. C., et al. 2012, MNRAS, 424, 464, doi: 10.1111/j.1365-2966.2012.21215.x

  16. [24]

    Farihi, J., Zuckerman, B., & Becklin, E. E. 2008, ApJ, 674, 431, doi: 10.1086/521715

  17. [25]

    J., Marsh, T

    Farihi, J., Hermes, J. J., Marsh, T. R., et al. 2022, MNRAS, 511, 1647, doi: 10.1093/mnras/stab3475

  18. [26]

    Clayton, G. C. 2019, ApJ, 886, 108, doi: 10.3847/1538-4357/ab4c3a

  19. [27]

    A., Magnier, E

    Flewelling, H. A., Magnier, E. A., Chambers, K. C., et al. 2020, ApJS, 251, 7, doi: 10.3847/1538-4365/abb82d

  20. [28]

    2013, emcee: The MCMC Hammer, Astrophysics Source Code Library, record ascl:1303.002 G¨ansicke, B

    Foreman-Mackey, D., Conley, A., Meierjurgen Farr, W., et al. 2013, emcee: The MCMC Hammer, Astrophysics Source Code Library, record ascl:1303.002 G¨ansicke, B. T., Marsh, T. R., Southworth, J., &

  21. [29]

    2006, Science, 314, 1908, doi: 10.1126/science.1135033

    Rebassa-Mansergas, A. 2006, Science, 314, 1908, doi: 10.1126/science.1135033

  22. [30]

    2019, ApJ, 882, 106, doi: 10.3847/1538-4357/ab379e Gentile Fusillo, N

    Genest-Beaulieu, C., & Bergeron, P. 2019, ApJ, 882, 106, doi: 10.3847/1538-4357/ab379e Gentile Fusillo, N. P., Tremblay, P.-E., G¨ansicke, B. T., et al. 2019a, MNRAS, 482, 4570, doi: 10.1093/mnras/sty3016 —. 2019b, MNRAS, 482, 4570, doi: 10.1093/mnras/sty3016 Gentile Fusillo, ...

  23. [31]

    M., Brasseur, C

    Ginsburg, A., Sip˝ocz, B. M., Brasseur, C. E., et al. 2019, AJ, 157, 98, doi: 10.3847/1538-3881/aafc33

  24. [32]

    A., Kutra, T., & Wu, Y

    Goksu, O. A., Kutra, T., & Wu, Y . 2024, AJ, 167, 236, doi: 10.3847/1538-3881/ad3216

  25. [33]

    D., Cartledge, S., & Clayton, G

    Gordon, K. D., Cartledge, S., & Clayton, G. C. 2009, ApJ, 705, 1320, doi: 10.1088/0004-637X/705/2/1320

  26. [34]

    D., Clayton, G

    Gordon, K. D., Clayton, G. C., Decleir, M., et al. 2023, ApJ, 950, 86, doi: 10.3847/1538-4357/accb59 NEWWHITEDWARFS WITHTRANSITINGDEBRIS INZTF 31

  27. [35]

    D., Misselt, K

    Gordon, K. D., Misselt, K. A., Bouwman, J., et al. 2021, ApJ, 916, 33, doi: 10.3847/1538-4357/ac00b7

  28. [36]

    A., Hermes, J

    Guidry, J. A., Hermes, J. J., De, K., et al. 2024b, ApJ, 972, 126, doi: 10.3847/1538-4357/ad5be7

  29. [37]

    A., Vanderbosch, Z

    Guidry, J. A., Vanderbosch, Z. P., Hermes, J. J., et al. 2021, ApJ, 912, 125, doi: 10.3847/1538-4357/abee68

  30. [38]

    2017, MNRAS, 469, 3213, doi: 10.1093/mnras/stx924

    Hallakoun, N., Xu, S., Maoz, D., et al. 2017, MNRAS, 469, 3213, doi: 10.1093/mnras/stx924

  31. [39]

    Hansen, J. E. 1971, Journal of the Atmospheric Sciences, 28, 1400, doi: 10.1175/1520-0469(1971)028⟨1400:MSOPLI⟩2.0.CO;2

  32. [40]

    K., Hallinan, G., Milburn, J., et al

    Harding, L. K., Hallinan, G., Milburn, J., et al. 2016, MNRAS, 457, 3036, doi: 10.1093/mnras/stw094

  33. [41]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, Nature, 585, 357, doi: 10.1038/s41586-020-2649-2

  34. [42]

    J., Guidry, J

    Hermes, J. J., Guidry, J. A., Vanderbosch, Z. P., et al. 2025, arXiv e-prints, arXiv:2501.02050, doi: 10.48550/arXiv.2501.02050

  35. [43]

    A., Kiker, T

    Hillenbrand, L. A., Kiker, T. J., Gee, M., et al. 2022, AJ, 163, 263, doi: 10.3847/1538-3881/ac62d8

  36. [44]

    T., Harrison, D

    Hodgkin, S. T., Harrison, D. L., Breedt, E., et al. 2021, A&A, 652, A76, doi: 10.1051/0004-6361/202140735

  37. [45]

    Horne, K., & Marsh, T. R. 1986, MNRAS, 218, 761, doi: 10.1093/mnras/218.4.761

  38. [46]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

  39. [47]

    T., Breedt, E., et al

    Inight, K., G¨ansicke, B. T., Breedt, E., et al. 2023, MNRAS, 524, 4867, doi: 10.1093/mnras/stad2018 Ivezi´c, ˇZ., Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111, doi: 10.3847/1538-4357/ab042c

  40. [48]

    T., et al

    Izquierdo, P., Rodr´ıguez-Gil, P., G¨ansicke, B. T., et al. 2018, MNRAS, 481, 703, doi: 10.1093/mnras/sty2315

  41. [49]

    A., Clemens, D

    Janes, K. A., Clemens, D. P., Hayes-Gehrke, M. N., et al. 2004, in American Astronomical Society Meeting Abstracts, V ol. 204, American Astronomical Society Meeting Abstracts #204, 10.01 Jim´enez-Esteban, F. M., Torres, S., Rebassa-Mansergas, A., et al. 2018, MNRAS, 480, 4505,...

  42. [50]

    2003, ApJL, 584, L91, doi: 10.1086/374036

    Jura, M. 2003, ApJL, 584, L91, doi: 10.1086/374036

  43. [51]

    2007, ApJ, 663, 1285, doi: 10.1086/518767

    Jura, M., Farihi, J., & Zuckerman, B. 2007, ApJ, 663, 1285, doi: 10.1086/518767

  44. [52]

    O., & Winget, D

    Kanaan, A., Kepler, S. O., & Winget, D. E. 2002, A&A, 389, 896, doi: 10.1051/0004-6361:20020485

  45. [53]

    2023, Nature, 622, 251, doi: 10.1038/s41586-023-06573-9

    Kenworthy, M., Lock, S., Kennedy, G., et al. 2023, Nature, 622, 251, doi: 10.1038/s41586-023-06573-9

  46. [54]

    G., Bergeron, P., & Conly, A

    Kilic, M., Kosakowski, A., Moss, A. G., Bergeron, P., & Conly, A. A. 2021, ApJL, 923, L6, doi: 10.3847/2041-8213/ac3b60

  47. [55]

    J., Kepler, S

    Kleinman, S. J., Kepler, S. O., Koester, D., et al. 2013, ApJS, 204, 5, doi: 10.1088/0067-0049/204/1/5

  48. [56]

    2010, Memorie della Societa Astronomica Italiana,, 81, 921

    Koester, D. 2010, Memorie della Societa Astronomica Italiana,, 81, 921

  49. [57]

    T., & Farihi, J

    Koester, D., G¨ansicke, B. T., & Farihi, J. 2014, A&A, 566, A34, doi: 10.1051/0004-6361/201423691

  50. [58]

    O., & Irwin, A

    Koester, D., Kepler, S. O., & Irwin, A. W. 2020, A&A, 635, A103, doi: 10.1051/0004-6361/202037530

  51. [59]

    2021, ApJ, 920, 156, doi: 10.3847/1538-4357/ac1354

    Lai, S., Dennihy, E., Xu, S., et al. 2021, ApJ, 920, 156, doi: 10.3847/1538-4357/ac1354

  52. [60]

    M., Lattanzi, M

    Lasker, B. M., Lattanzi, M. G., McLean, B. J., et al. 2008, AJ, 136, 735, doi: 10.1088/0004-6256/136/2/735 Le Bourdais, ´E., Dufour, P., & Xu, S. 2024, arXiv e-prints, arXiv:2410.10948, doi: 10.48550/arXiv.2410.10948

  53. [61]

    A., Chambers, K

    Magnier, E. A., Chambers, K. C., Flewelling, H. A., et al. 2020, ApJS, 251, 3, doi: 10.3847/1538-4365/abb829

  54. [62]

    2021, MNRAS, 501, 3806, doi: 10.1093/mnras/staa3940

    Malamud, U., Grishin, E., & Brouwers, M. 2021, MNRAS, 501, 3806, doi: 10.1093/mnras/staa3940

  55. [63]

    S., Fremling, C., & Kasliwal, M

    Mandigo-Stoba, M. S., Fremling, C., & Kasliwal, M. 2022a, The Journal of Open Source Software, 7, 3612, doi: 10.21105/joss.03612 —. 2022b, DBSP DRP: A Python package for automated spectroscopic data reduction of DBSP data, v1.0.0, Zenodo, doi: 10.5281/zenodo.6241526

  56. [64]

    J., G¨ansicke, B

    Manser, C. J., G¨ansicke, B. T., Gentile Fusillo, N. P., et al. 2020, MNRAS, 493, 2127, doi: 10.1093/mnras/staa359

  57. [65]

    J., G¨ansicke, B

    Manser, C. J., G¨ansicke, B. T., Marsh, T. R., et al. 2016, MNRAS, 455, 4467, doi: 10.1093/mnras/stv2603

  58. [66]

    J., Laher, R

    Masci, F. J., Laher, R. R., Rusholme, B., et al. 2019, PASP, 131, 018003, doi: 10.1088/1538-3873/aae8ac

  59. [67]

    S., Rumpl, W., & Nordsieck, K

    Mathis, J. S., Rumpl, W., & Nordsieck, K. H. 1977, ApJ, 217, 425, doi: 10.1086/155591

  60. [68]

    M., Lang, D., & Schlegel, D

    Meisner, A. M., Lang, D., & Schlegel, D. J. 2018, AJ, 156, 69, doi: 10.3847/1538-3881/aacbcd

  61. [69]

    2011, ApJ, 732, 90, doi: 10.1088/0004-637X/732/2/90

    Melis, C., Farihi, J., Dufour, P., et al. 2011, ApJ, 732, 90, doi: 10.1088/0004-637X/732/2/90

  62. [70]

    2010, ApJ, 722, 1078, doi: 10.1088/0004-637X/722/2/1078

    Melis, C., Jura, M., Albert, L., Klein, B., & Zuckerman, B. 2010, ApJ, 722, 1078, doi: 10.1088/0004-637X/722/2/1078

  63. [71]

    T., et al

    Mullally, F., Kilic, M., Reach, W. T., et al. 2007, ApJS, 171, 206, doi: 10.1086/511858

  64. [72]

    1998, MNRAS, 296, 339, doi: 10.1046/j.1365-8711.1998.01314.x

    Naylor, T. 1998, MNRAS, 296, 339, doi: 10.1046/j.1365-8711.1998.01314.x

  65. [73]

    2000, A&AS, 143, 23, doi: 10.1051/aas:2000169

    Ochsenbein, F., Bauer, P., & Marcout, J. 2000, A&AS, 143, 23, doi: 10.1051/aas:2000169

  66. [74]

    B., & Gunn, J

    Oke, J. B., & Gunn, J. E. 1982, PASP, 94, 586, doi: 10.1086/131027

  67. [75]

    B., Cohen, J

    Oke, J. B., Cohen, J. G., Carr, M., et al. 1995, PASP, 107, 375, doi: 10.1086/133562 Ould Rouis, L. B., Hermes, J. J., G¨ansicke, B. T., et al. 2024, arXiv e-prints, arXiv:2410.06335, doi: 10.48550/arXiv.2410.06335

  68. [76]

    2023, AJ, 166, 5, doi: 10.3847/1538-3881/accc25 32 BHATTACHARJEE ET AL

    Owens, D., Xu, S., Manjavacas, E., et al. 2023, AJ, 166, 5, doi: 10.3847/1538-3881/accc25 32 BHATTACHARJEE ET AL

  69. [77]

    G., Collins, K

    Paegert, M., Stassun, K. G., Collins, K. A., et al. 2021, arXiv e-prints, arXiv:2108.04778, doi: 10.48550/arXiv.2108.04778 pandas development team, T. 2020, pandas-dev/pandas: Pandas, latest, Zenodo, doi: 10.5281/zenodo.3509134

  70. [78]

    Perley, D. A. 2019, PASP, 131, 084503, doi: 10.1088/1538-3873/ab215d

  71. [79]

    2020a, The Journal of Open Source Software, 5, 2308, doi: 10.21105/joss.02308

    Prochaska, J., Hennawi, J., Westfall, K., et al. 2020a, The Journal of Open Source Software, 5, 2308, doi: 10.21105/joss.02308

  72. [80]

    2020b, pypeit/PypeIt: Release 1.0.0, v1.0.0, Zenodo, doi: 10.5281/zenodo.3743493

    Prochaska, J., Hennawi, J., Cooke, R., et al. 2020b, pypeit/PypeIt: Release 1.0.0, v1.0.0, Zenodo, doi: 10.5281/zenodo.3743493

  73. [81]

    D., & Xu, S

    Putirka, K. D., & Xu, S. 2021, Nature Communications, 12, 6168, doi: 10.1038/s41467-021-26403-8

  74. [82]

    L., Kaye, T., et al

    Rappaport, S., Gary, B. L., Kaye, T., et al. 2016, MNRAS, 458, 3904, doi: 10.1093/mnras/stw612

  75. [83]

    W., et al

    Redfield, S., Farihi, J., Cauley, P. W., et al. 2017, ApJ, 839, 42, doi: 10.3847/1538-4357/aa68a0

  76. [84]

    2021, A&A, 647, A184, doi: 10.1051/0004-6361/202140289

    Reindl, N., Schaffenroth, V ., Filiz, S., et al. 2021, A&A, 647, A184, doi: 10.1051/0004-6361/202140289

  77. [85]

    2023, A&A, 677, A29, doi: 10.1051/0004-6361/202346865

    Reindl, N., Islami, R., Werner, K., et al. 2023, A&A, 677, A29, doi: 10.1051/0004-6361/202346865

  78. [86]

    W., et al

    Riello, M., De Angeli, F., Evans, D. W., et al. 2021, A&A, 649, A3, doi: 10.1051/0004-6361/202039587

  79. [87]

    2018, ztfquery, a python tool to access ZTF data, doi, Zenodo, doi: 10.5281/zenodo.1345222

    Rigault, M. 2018, ztfquery, a python tool to access ZTF data, doi, Zenodo, doi: 10.5281/zenodo.1345222

  80. [88]

    2003, A&A, 404, 301, doi: 10.1051/0004-6361:20030330 Rivera Sandoval, L

    Ritter, H., & Kolb, U. 2003, A&A, 404, 301, doi: 10.1051/0004-6361:20030330 Rivera Sandoval, L. E., & Maccarone, T. J. 2019, MNRAS, 483, L6, doi: 10.1093/mnrasl/sly205 Rivera Sandoval, L. E., Maccarone, T. J., Cavecchi, Y ., Britt, C., &

  81. [89]

    2021, MNRAS, 505, 215, doi: 10.1093/mnras/stab1246 Rivera Sandoval, L

    Zurek, D. 2021, MNRAS, 505, 215, doi: 10.1093/mnras/stab1246 Rivera Sandoval, L. E., Maccarone, T. J., & Pichardo Marcano, M. 2020, ApJL, 900, L37, doi: 10.3847/2041-8213/abb130

  82. [90]

    S., Fremling, C., & Kasliwal, M

    Roberson, M. S., Fremling, C., & Kasliwal, M. M. 2021, DBSP DRP: DBSP Data Reduction Pipeline, Astrophysics Source Code Library, record ascl:2108.020. http://ascl.net/2108.020

  83. [91]

    2024, MNRAS, 533, 1756, doi: 10.1093/mnras/stae1859

    Robert, A., Farihi, J., Van Eylen, V ., et al. 2024, MNRAS, 533, 1756, doi: 10.1093/mnras/stae1859

  84. [92]

    2010, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference

    Rockosi, C., Stover, R., Kibrick, R., et al. 2010, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference

  85. [93]

    7735, Ground-based and Airborne Instrumentation for Astronomy III, ed

    Series, V ol. 7735, Ground-based and Airborne Instrumentation for Astronomy III, ed. I. S. McLean, S. K. Ramsay, & H. Takami, 77350R, doi: 10.1117/12.856818

  86. [94]

    C., Mr´oz, P., Kulkarni, S

    Rodriguez, A. C., Mr´oz, P., Kulkarni, S. R., et al. 2022, ApJ, 927, 150, doi: 10.3847/1538-4357/ac51cc

  87. [95]

    K., Bonsor, A., Xu, S., et al

    Rogers, L. K., Bonsor, A., Xu, S., et al. 2024, MNRAS, 527, 6038, doi: 10.1093/mnras/stad3557

  88. [96]

    D., Kepler, S

    Romero, A. D., Kepler, S. O., Hermes, J. J., et al. 2022, MNRAS, 511, 1574, doi: 10.1093/mnras/stac093

  89. [97]

    M., Tucker, M

    Rowan, D. M., Tucker, M. A., Shappee, B. J., & Hermes, J. J. 2019, MNRAS, 486, 4574, doi: 10.1093/mnras/stz1116

  90. [98]

    F., Meisner, A

    Schlafly, E. F., Meisner, A. M., & Green, G. M. 2019, ApJS, 240, 30, doi: 10.3847/1538-4365/aafbea

  91. [99]

    I., Bolte, M., Epps, H

    Sheinis, A. I., Bolte, M., Epps, H. W., et al. 2002, PASP, 114, 851, doi: 10.1086/341706

  92. [100]

    W., Young, D

    Shingles, L., Smith, K. W., Young, D. R., et al. 2021, Transient Name Server AstroNote, 7, 1

  93. [101]

    2021, ApJ, 911, 25, doi: 10.3847/1538-4357/abc262

    Steele, A., Debes, J., Xu, S., Yeh, S., & Dufour, P. 2021, ApJ, 911, 25, doi: 10.3847/1538-4357/abc262

  94. [102]

    2023, MNRAS, 526, 3815, doi: 10.1093/mnras/stad2867

    Swan, A., Farihi, J., Melis, C., et al. 2023, MNRAS, 526, 3815, doi: 10.1093/mnras/stad2867

  95. [103]

    2024, MNRAS, 530, 2076, doi: 10.1093/mnras/stae953

    Tran, V ., De, K., & Hillenbrand, L. 2024, MNRAS, 530, 2076, doi: 10.1093/mnras/stae953

  96. [104]

    E., Ludwig, H

    Tremblay, P. E., Ludwig, H. G., Steffen, M., & Freytag, B. 2013, A&A, 559, A104, doi: 10.1051/0004-6361/201322318 van Sluijs, L., & Van Eylen, V . 2018, MNRAS, 474, 4603, doi: 10.1093/mnras/stx3068

  97. [105]

    2022, zvanderbosch/phot2lc: phot2lc v1.7.0 release, v1.7.0, Zenodo, doi: 10.5281/zenodo.6459216

    Vanderbosch, Z. 2022, zvanderbosch/phot2lc: phot2lc v1.7.0 release, v1.7.0, Zenodo, doi: 10.5281/zenodo.6459216

  98. [106]

    J., Dennihy, E., et al

    Vanderbosch, Z., Hermes, J. J., Dennihy, E., et al. 2020, ApJ, 897, 171, doi: 10.3847/1538-4357/ab9649

  99. [107]

    P., Hermes, J

    Vanderbosch, Z. P., Hermes, J. J., Winget, D. E., et al. 2022, ApJ, 927, 158, doi: 10.3847/1538-4357/ac4caf

  100. [108]

    P., Rappaport, S., Guidry, J

    Vanderbosch, Z. P., Rappaport, S., Guidry, J. A., et al. 2021, ApJ, 917, 41, doi: 10.3847/1538-4357/ac0822

  101. [109]

    A., Rappaport, S., et al

    Vanderburg, A., Johnson, J. A., Rappaport, S., et al. 2015, Nature, 526, 546, doi: 10.1038/nature15527

  102. [110]

    2020, AJ, 160, 252, doi: 10.3847/1538-3881/abbe20

    Vincent, O., Bergeron, P., & Lafreni`ere, D. 2020, AJ, 160, 252, doi: 10.3847/1538-3881/abbe20

  103. [111]

    E., et al

    Virtanen, P., Gommers, R., Oliphant, T. E., et al. 2020, Nature Methods, 17, 261, doi: 10.1038/s41592-019-0686-2

  104. [112]

    2023, ApJ, 944, 23, doi: 10.3847/1538-4357/acaf5a

    Wang, L., Zhang, X., Wang, J., et al. 2023, ApJ, 944, 23, doi: 10.3847/1538-4357/acaf5a

  105. [113]

    G., Farihi, J., G¨ansicke, B

    Wilson, T. G., Farihi, J., G¨ansicke, B. T., & Swan, A. 2019, MNRAS, 487, 133, doi: 10.1093/mnras/stz1050

  106. [114]

    2019a, AJ, 158, 242, doi: 10.3847/1538-3881/ab4cee

    Xu, S., Dufour, P., Klein, B., et al. 2019a, AJ, 158, 242, doi: 10.3847/1538-3881/ab4cee

  107. [115]

    2016, ApJL, 816, L22, doi: 10.3847/2041-8205/816/2/L22

    Xu, S., Jura, M., Dufour, P., & Zuckerman, B. 2016, ApJL, 816, L22, doi: 10.3847/2041-8205/816/2/L22

  108. [116]

    2020, ApJ, 902, 127, doi: 10.3847/1538-4357/abb3fc

    Xu, S., Lai, S., & Dennihy, E. 2020, ApJ, 902, 127, doi: 10.3847/1538-4357/abb3fc

  109. [117]

    2018, MNRAS, 474, 4795, doi: 10.1093/mnras/stx3023

    Xu, S., Rappaport, S., van Lieshout, R., et al. 2018, MNRAS, 474, 4795, doi: 10.1093/mnras/stx3023

  110. [118]

    2019b, AJ, 157, 255, doi: 10.3847/1538-3881/ab1b36

    Xu, S., Hallakoun, N., Gary, B., et al. 2019b, AJ, 157, 255, doi: 10.3847/1538-3881/ab1b36

  111. [119]

    K., et al

    Xu, S., Yeh, S., Rogers, L. K., et al. 2024, AJ, 167, 248, doi: 10.3847/1538-3881/ad3737

  112. [120]

    Zuckerman, B., & Becklin, E. E. 1987, Nature, 330, 138, doi: 10.1038/330138a0 NEWWHITEDWARFS WITHTRANSITINGDEBRIS INZTF 33

  113. [121]

    M., & Jura, M

    Zuckerman, B., Koester, D., Melis, C., Hansen, B. M., & Jura, M. 2007, ApJ, 671, 872, doi: 10.1086/522223

  114. [122]

    N., & H¨unsch, M

    Zuckerman, B., Koester, D., Reid, I. N., & H¨unsch, M. 2003, ApJ, 596, 477, doi: 10.1086/377492

  115. [123]

    2010, ApJ, 722, 725, doi: 10.1088/0004-637X/722/1/725

    Zuckerman, B., Melis, C., Klein, B., Koester, D., & Jura, M. 2010, ApJ, 722, 725, doi: 10.1088/0004-637X/722/1/725

Pith tools

Reviewed August 8, 2026 · model on record in the stance chip above.