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Variability-finding in Rubin Data Preview 1 with LSDB

T0 review · 4 major / 5 minor · reviewed 2026-08-06 · deepseek-v4-flash

Pith's one-line read Two LSDB-based variability pipelines on Rubin Data Preview 1 find an M-dwarf flare and an unclassified eclipsing binary, validating the framework for LSST-scale time-domain analysis.

desk verdict A credible proof-of-concept for LSDB/HATS time-domain work on Rubin DP1, with two plausible new variable objects; the binary's physical characterization is softer than the variability detection itself. read the letter →

arxiv 2506.23955 v2 pith:HEZ47ROP submitted 2025-06-30 astro-ph.IM astro-ph.SR

classification astro-ph.IMastro-ph.SR
keywords time-domainastronomyvariablestarsflareeclipsingbinariesLomb-ScargleperiodogramRubinObservatoryDataPreview1LSDB
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 the first time-domain analysis of Rubin Observatory Data Preview 1 (DP1) carried out with the LSDB framework and the HATS catalog format. The authors build two pipelines, one that fits flare-like Bazin-function light curves and one that searches Lomb-Scargle periodograms for periodic variability, and run them over the DP1 difference-imaging catalog of about 1.1 million objects. They recover known quasars, cataclysmic variables, RR Lyrae stars, and eclipsing binaries, and they report two new findings: an M-dwarf flare and a previously unclassified eclipsing binary that is likely a W Ursae Majoris system with a K-dwarf primary at roughly 5.8 kpc. A sympathetic reader should care because the result is both an early validation that LSDB-style parallel analysis can handle Rubin-scale time-domain data and a demonstration that DP1's dense commissioning cadence can already yield genuinely new variable-object discoveries.

What carries the argument

The load-bearing objects are the HATS (Hierarchical Adaptive Tiling Scheme) catalog format, which stores DP1's objects and their nested forced-photometry light curves in HEALPix-tiled parquet files, and the LSDB framework, which lazily loads those tiles as Dask data frames and lets user functions run in parallel over the whole sky region. The transient search is carried by a Bazin function with exponential rise and fall plus an offset, $f(t) = A e^{-(t-t_0)/\tau_{\rm fall}} / (1 + e^{-(t-t_0)/\tau_{\rm rise}}) + B$, fitted per filter to DIA light curves; the periodicity search is carried by astropy Lomb-Scargle periodograms computed per griz band, with candidate periods required to agree within 0.1% in two bands and to pass a false-alarm-probability cut of $10^{-10}$. For the new eclipsing binary, a single-temperature black-body fit to multi-survey photometry converts fitted solid angle to distance using an interpolated dwarf temperature-radius relation.

What would settle it

Phase-resolved spectroscopy of LSST-DP1-DO-592913913020940296 over its 0.23256-day orbit would directly test the W UMa classification: double-lined radial-velocity variations and equal eclipse depths would support it, while a single-lined or non-variable velocity curve would falsify the binary interpretation. For the M-dwarf flare, re-observing LSST-DP1-DO-609789561081430049 in g and r with minute-cadence photometry, or checking DP2 for a second flare, would confirm the object's flaring nature; a blind injection-recovery test on DP1 images would also quantify how many similar flares the pipeline misses.

Watch

Extended reading notes

Core claim

Working from the HATS-formatted DP1 catalogs, the paper shows that a transient-search pipeline based on per-filter Bazin-function fits and a periodicity pipeline based on multi-band Lomb-Scargle periodograms can identify variable sources across 15 square degrees of LSSTComCam data. The central scientific findings are the detection of a short M-dwarf flare (LSST-DP1-DO-609789561081430049) whose quiescent colors match an M4 dwarf, and the discovery of a previously unclassified eclipsing binary (LSST-DP1-DO-592913913020940296) with a 0.23256-day period whose griz plus Gaia and DES photometry fit a $4700\pm70$ K black body, implying a distance of $5.8\pm0.6$ kpc under a dwarf-star radius assumption and suggesting a W Ursae Majoris classification. Alongside these detections, the paper presents the HATS version of DP1 object and DIA-object catalogs with nested light curves, and positions the whole exercise as a proof of concept for LSDB as the analysis layer for future Rubin data releases.

Load-bearing premise

The variability detections are robust to any single modeling choice, but the paper's characterization of the new eclipsing binary as a K-dwarf W UMa system at $5.8\pm0.6$ kpc assumes that its combined light is a single-temperature black body on a main-sequence dwarf; if the secondary contributes non-negligible flux or the temperature-radius interpolation does not apply, that distance would be biased while the variability finding would stand.

Editorial extensions

If this is right

  • If the pipelines work as described, the same LSDB/HATS stack can be pointed at Data Preview 2 and the first LSST data release without re-architecting the analysis.
  • The recovered set of known quasars, cataclysmic variables, RR Lyrae stars, and eclipsing binaries provides a validation sample for future automated classification of Rubin variables.
  • The 0.23256-day eclipsing binary, if confirmed as W UMa, extends the known population of short-period contact binaries to a faint, distant sample reachable only with deeper photometry.
  • The M-dwarf flare demonstrates that DP1's rapid same-night cadence can catch hour-long stellar flares, opening a DP1-era channel for flare statistics.
  • The released HATS DP1 catalog lets other teams run their own searches on the same data, making the discoveries reproducible rather than one-off.

Reading between the lines

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

  • Because the two pipelines recovered known variables across several classes, a natural next step, not taken in the paper, is to measure their completeness and contamination by injecting synthetic flares and periodic signals into DP1 images or catalogs.
  • The 5.8 kpc distance rests on the dwarf-star temperature-radius interpolation and on treating the unresolved binary as a single-temperature black body; phase-resolved spectroscopy or a more detailed binary model could shift that distance substantially even if the variability detection stands.
  • The same per-band Bazin fitting approach should also catch declining or rising active galactic nuclei in longer-baseline Rubin data, since two quasars in this paper were selected precisely because their near-linear light curves mimic the Bazin shape.
  • If DP2 provides months of LSSTCam data, the method's period window of 5 minutes to 12 hours could be extended to days, at which point the recovered RR Lyrae and contact-binary sample would grow by orders of magnitude.
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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 manuscript presents two variability-finding pipelines applied to Rubin Observatory Data Preview 1 (DP1) stored in HATS format and queried with the LSDB framework. The first pipeline fits constant and Bazin-function models to identify flares and transients; the second uses per-band Lomb-Scargle periodograms with multi-band period agreement and false-alarm thresholds to find periodic variables. The authors report recovery of previously known quasars, cataclysmic variables, RR Lyrae stars, and eclipsing binaries, along with the transient AT2024ahyy, an M-dwarf flare, and a previously unclassified eclipsing binary that they characterize as a K-dwarf W UMa system at a distance of 5.8±0.6 kpc. The HATS versions of the DP1 catalogs and the analysis code are publicly released.

Significance. If the results hold, the paper demonstrates a scalable, reusable approach to time-domain analysis on Rubin precursor data and provides the community with validated HATS-formatted DP1 catalogs. Its concrete strengths are the public code release, the reproducible use of LSDB and nested-pandas for out-of-memory light-curve analysis, and the successful recovery of objects with independent classifications from Catalina, Gaia, and ATLAS. The astrophysical discoveries are modest and are explicitly preliminary; the main value is the software-infrastructure validation. However, the absence of quantitative completeness and false-positive measurements, together with the model-dependent physical characterization of the new binary, currently limits the strength of the discovery claims.

major comments (4)
  1. [§3.2 and Figure 6] The distance and K-dwarf classification of LSST-DP1-DO-592913913020940296 rest on a single-temperature black-body fit to the combined griz, Gaia, and DES photometry of an eclipsing binary. For a W UMa or ellipsoidal binary the observed SED is the sum of two stellar components, so the fitted temperature of 4700±70 K is a flux-weighted composite rather than necessarily the primary's effective temperature. The radius is then taken from a main-sequence dwarf temperature-radius relation (Pecaut & Mamajek 2013), which assumes a single dwarf star. Consequently the quoted distance of 5.8±0.6 kpc is model-dependent and already sits about 2 kpc below the Bailer-Jones et al. (2021) photo-geometric distance of 7.8+1.4−1.0 kpc. The variability detection itself is not affected, but the specific claim of a K-dwarf W UMa at 5.8 kpc needs either a two-component SED model or a clear reframing as a provisional, model-dependent estimate.
  2. [§3 and §4 (overall pipeline evaluation)] The paper does not provide any completeness or false-positive quantification for either pipeline. The selection thresholds are stated (reduced chi-squared cuts for the Bazin fits, FAP<10^-10, period agreement within 0.1% in at least two bands), but the reader is never told how many light curves entered each stage, how many passed the cuts, how many candidates were visually inspected, or how many were rejected as false. Without injected-signal recovery tests or a control sample, the efficiency and contamination rate of the two variability-finding methods cannot be assessed, which weakens the central claim that the pipelines 'find' variable objects.
  3. [§4 and §3.2] The conclusion claims detection of 'previously unclassified eclipsing binary and variable objects' in the plural, but the paper presents no table or machine-readable list of all detected variable objects, their periods, amplitudes, or cross-identifications. Only a handful of examples are shown in Figures 1-6. For a paper whose contribution includes releasing catalogs and reporting discoveries, a complete candidate list with the selection stage at which each object was found is necessary to support the discovery claims and to allow community follow-up.
  4. [§3.1] The flare pipeline relies on 'visual inspection to identify flaring objects' without stating the criteria, the number of candidates inspected, or the number of false detections. The paper notes that false detections occur 'typically due to photometric pipeline problems' but does not quantify them. This makes the M-dwarf flare and the other transient detections difficult to reproduce as a pipeline result; please specify the visual-inspection protocol and provide counts of accepted and rejected candidates.
minor comments (5)
  1. [§3.2] The phrase 'the least can be converted to distance' should read 'the latter can be converted to distance', and in Equation (1) the symbols τ_fall and τ_rise should be typeset consistently as subscripts.
  2. [Figure 5 caption] The statement 'DP1's u-band photometry is shifted by one magnitude' is ambiguous; please state whether the offset is for display only, specify the direction and amount of the shift, and apply the same labeling in the figure itself.
  3. [§2] The sentence 'we perform an offline join to append columns to that correspond to Rubin's Butler dimensions' contains a grammatical error and should read 'append columns that correspond'.
  4. [Abstract and §1] The abstract and the Introduction both introduce the two pipelines with nearly identical phrasing; the repetition should be removed for conciseness.
  5. [Figure 1 caption] The right-panel coordinates are listed as Dec=27.98829 in the caption but as δ=−27.98802 in the text; these should be checked and made consistent.

Circularity Check

0 steps flagged · score 0.0 of 10

No significant circularity: the variability detections are independent of the model-dependent physical characterization, and self-citations point to open-source software rather than load-bearing unverified results.

full rationale

I find no significant circularity. The paper's central claims are the detection of variable objects in DP1 using LSDB/HATS pipelines and the release of the HATS catalogs. The flare and periodicity pipelines apply standard statistics (Bazin fits, Lomb-Scargle periodograms, false-alarm probabilities) to DP1 photometry; no fitted parameter is renamed as a prediction, and no equation is defined in terms of the target result. The newly reported objects are matched against independent external catalogs (e.g., Catalina, Gaia, ATLAS, YSE), so the detections are externally anchored. The physical characterization of the new eclipsing binary in Section 3.2 uses a black-body fit to combined photometry and a dwarf temperature-radius relation to estimate distance; this is an explicitly stated model-dependent inference, not a circular reduction, because the solid angle and temperature are fitted from data and the radius is taken from an external empirical relation. The comparison with the Bailer-Jones photo-geometric distance further shows the distance estimate is an independent, falsifiable result rather than an input. Self-citations to LSDB and HATS refer to open-source software and the HATS format, and they do not function as unverified authorities supporting the scientific detections. The acknowledged limitations (single-temperature assumption, dwarf-radius assumption) are correctness risks, not circularity.

Assumptions & free parameters 3 free parameters · 4 assumptions · 0 invented entities

The detection methods are standard statistics and astrophysical models. The only hand-set numbers are analysis thresholds (chi2 cuts, period tolerance, FAP level) and the black-body/dwarf-radius inference for the binary. No new physical entities are introduced.

free parameters (3)
  • Flare-detection reduced chi2 thresholds = chi2_c > 1; chi2_B < 10; chi2_c/chi2_B < 3
    Hand-chosen cuts in §3.1 that define which single-filter light curves pass to visual inspection; no optimization or sensitivity analysis is given.
  • Periodicity search selection cuts = ≥50 total obs; ≥30 in griz; best periods in ≥2 bands within 0.1%; FAP < 1e-10; exclude 1/4 and 1/3 day
    Hand-chosen thresholds in §3.2 that determine the periodic candidates presented.
  • Black-body fit temperature and radius-to-distance conversion = T_eff = 4700 ± 70 K; distance = (R/R_sun)^2 * 10.0 ± 0.7 kpc ≈ 5.8 ± 0.6 kpc with R/R_sun ≈ 0.73
    Fitted to combined LSST/Gaia/DES photometry in §3.2; the distance depends on an assumed dwarf temperature-radius interpolation, so the quoted distance is model-dependent.
assumptions (4)
  • domain assumption Bazin function is an adequate parametric model for flare and outburst light curves
    Used in §3.1 to model all transients including quasars with near-linear decay; this assumption drives which objects pass the chi2-based selection.
  • standard math Lomb-Scargle periodogram and Baluev false-alarm probabilities as implemented in astropy are appropriate for these unevenly sampled light curves
    Used in §3.2 for periodicity search; the method assumes sinusoidal or quasi-periodic signals.
  • domain assumption The combined light of the candidate eclipsing binary can be approximated by a single-temperature black body, and the dwarf temperature-radius relation applies
    Used in §3.2 to estimate temperature and distance; if the secondary star contributes significantly or the star is not a dwarf, the inferred parameters are biased.
  • domain assumption The pre-transient DIA flux of AT2024ahyy can be shifted to zero to align with DECam photometry
    Applied in Figure 3 to compare DP1 DIA fluxes with DECam AB magnitudes; the zero-point shift assumes the DIA pre-transient flux is constant and correctly measured.

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Cite this review

Pith. "Pith review of Variability-finding in Rubin Data Preview 1 with LSDB." pith.science (2026). https://pith.science/paper/HEZ47ROP

@misc{pith2026250623955,
  author       = {Pith},
  title        = {Pith review of: Variability-finding in Rubin Data Preview 1 with LSDB},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/HEZ47ROP}},
  note         = {Machine review of arXiv:2506.23955}
}
read the original abstract

The Vera C. Rubin Observatory recently released Data Preview 1 (DP1) in advance of the upcoming Legacy Survey of Space and Time (LSST), which will enable boundless discoveries in time-domain astronomy over the next ten years. DP1 provides an ideal sandbox for validating innovative data analysis approaches for the LSST mission, whose scale challenges established software infrastructure paradigms. This note presents a pair of such pipelines for variability-finding using powerful software infrastructure suited to LSST data, namely the HATS (Hierarchical Adaptive Tiling Scheme) format and the LSDB framework, developed by the LSST Interdisciplinary Network for Collaboration and Computing (LINCC) Frameworks team. This article presents a pair of variability-finding pipelines built on LSDB, the HATS catalog of DP1 data, and preliminary results of detected variable objects, two of which are novel discoveries.

Figures

Figures reproduced from arXiv: 2506.23955 by the authors.

Figure 1
Figure 1. Quasars found in DP1 with our transient search pipeline. Left: LSST-DP1-DO￾611256447031836758. Right: LSST-DP1-DO-611255278800732178. Observations with magnitude error larger than 0.2 are not shown. As shown, in most bands the light curves are approximately linear, which is why they can be well fit with Eq. 1. 60625 60630 60635 60640 60645 60650 60655 MJD 15.0 15.5 16.0 16.5 17.0 17.5 18.0 18.5 19.0 PSF mag CRTS J03… view at source ↗
Figure 2
Figure 2. Cataclysmic variable outbursts detected in DP1. Left: LSST-DP1-DO-609788736447709201 / CRTS J033349.8−282244. Right: LSST-DP1-DO-614437609048899879 / ZTF19acecitx. In both cases, the rising and falling parts of the light curve are observed in multiple filters. fluxes are zero, we find that it has 111 observations with signal-to-noise ratio larger than three. The first detection has “direct” (non-DIA) r-band magnitud… view at source ↗
Figure 3
Figure 3. DP1 and YSE DECam photometry of LSST-DP1-DO-609781520902651937 / AT2024ahyy. Left: AB magnitude. Right: bandfluxes, with DP1 difference bandflux pre-transient photometry shifted to zero before MJD 60640, and DECam AB magnitudes being converted to nJy. Semi-transparent points mark measurements with signal-to-noise ratio smaller than three, where the noise term includes the uncertainty in the pre-transient flux estima… view at source ↗
Figures from the paper (3 more)
Figure 4
Figure 4. Figure 4: M dwarf flare LSST-DP1-DO-609789561081430049. Left panel: full light curve, the detected flare is shown with a gray line at MJD 60646. Right panel: an hour of observations at MJD 60646 covering the flare. the eight observations during the flare span about 10 minutes. T…
Figure 5
Figure 5. Figure 5: Examples of periodic variables in the DP1 data enriched with Catalina Sky Survey, Gaia and ATLAS light curves. Top row: RR Lyrae. Central and bottom rows: eclipsing binaries. Note that DP1’s u-band photometry is shifted by one magnitude. Finally, we release the HATS ve…
Figure 6
Figure 6. Figure 6: Period-folded eclipsing binary LSST-DP1-DO-592913913020940296, with a half-period sine fit (dashed line), period P = 0.23256 days. Acknowledgments LINCC Frameworks is supported by Schmidt Sciences. This publication is based in part on pro￾prietary Rubin Observatory dat…

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Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

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Reference graph

Works this paper leans on

34 extracted references · 6 canonical work pages · cited by 2 Pith papers

  1. [1]

    , " * write output.state after.block = add.period write newline

    ENTRY address archivePrefix author booktitle chapter doi edition editor eprint howpublished institution journal key month number organization pages publisher school series title misctitle type volume year version url label extra.label sort.label short.list INTEGERS output.state before.all mid.sentence after.sentence after.block FUNCTION init.state.consts ...

  2. [2]

    write newline

    " write newline "" before.all 'output.state := FUNCTION format.url url empty "" new.block "" url * "" * if FUNCTION format.eprint eprint empty "" archivePrefix empty "" archivePrefix "arXiv" = new.block " " eprint * " " * new.block " " eprint * " " * if if if FUNCTION format.doi doi empty "" " " doi * " " * if FUNCTION format.pid doi empty eprint empty ur...

  3. [3]

    - [1] #1 = = ^ ^ ^ .\!\!^ d .\!\!^ h .\!\!^ m .\!\!^ s .\!\!^ @mss

    thebibliography [1] 20pt to REFERENCES 6pt =0pt -12pt 10pt plus 3pt =0pt =0pt =1pt plus 1pt =0pt =0pt -12pt =13pt plus 1pt =20pt =13pt plus 1pt \@M =10000 =-1.0em =0pt =0pt 0pt =0pt =1.0em @enumiv\@empty 10000 10000 `\.\@m \@noitemerr \@latex@warning Empty `thebibliography' environment \@ifnextchar \@reference \@latexerr Missing key on reference command E...

  4. [4]

    Abbott , T. M. C., Adam \'o w , M., Aguena , M., et al. 2021, title The Dark Energy Survey Data Release 2 , , 255, 20, 10.3847/1538-4365/ac00b3

  5. [5]

    M., Lim , P

    Astropy Collaboration , Price-Whelan , A. M., Lim , P. L., et al. 2022, title The Astropy Project: Sustaining and Growing a Community-oriented Open-source Project and the Latest Major Release (v5.0) of the Core Package , , 935, 167, 10.3847/1538-4357/ac7c74

  6. [6]

    Bailer-Jones , C. A. L., Rybizki , J., Fouesneau , M., Demleitner , M., & Andrae , R. 2021, title Estimating Distances from Parallaxes. V. Geometric and Photogeometric Distances to 1.47 Billion Stars in Gaia Early Data Release 3 , , 161, 147, 10.3847/1538-3881/abd806

  7. [7]

    Baluev , R. V. 2008, title Assessing the statistical significance of periodogram peaks , , 385, 1279, 10.1111/j.1365-2966.2008.12689.x

  8. [8]

    2009, title The core-collapse rate from the Supernova Legacy Survey , , 499, 653, 10.1051/0004-6361/200911847

    Bazin , G., Palanque-Delabrouille , N., Rich , J., et al. 2009, title The core-collapse rate from the Supernova Legacy Survey , , 499, 653, 10.1051/0004-6361/200911847

Show all 34 references
  1. [9]

    2025, title Using LSDB to enable large-scale catalog distribution, cross-matching, and analytics , arXiv e-prints, arXiv:2501.02103, 10.48550/arXiv.2501.02103

    Caplar , N., Beebe , W., Branton , D., et al. 2025, title Using LSDB to enable large-scale catalog distribution, cross-matching, and analytics , arXiv e-prints, arXiv:2501.02103, 10.48550/arXiv.2501.02103

  2. [10]

    2023, title Gaia Data Release 3

    Clementini , G., Ripepi , V., Garofalo , A., et al. 2023, title Gaia Data Release 3. Specific processing and validation of all-sky RR Lyrae and Cepheid stars: The RR Lyrae sample , , 674, A18, 10.1051/0004-6361/202243964

  3. [11]

    L., Barger , A

    Cowie , L. L., Barger , A. J., & Hu , E. M. 2010, title Low-Redshift Ly Selected Galaxies from GALEX Spectroscopy: A Comparison with Both UV-Continuum Selected Galaxies and High-Redshift Ly Emitters , , 711, 928, 10.1088/0004-637X/711/2/928

  4. [12]

    J., G \"a nsicke , B

    Drake , A. J., G \"a nsicke , B. T., Djorgovski , S. G., et al. 2014, title Cataclysmic variables from the Catalina Real-time Transient Survey , , 441, 1186, 10.1093/mnras/stu639

  5. [13]

    J., Djorgovski , S

    Drake , A. J., Djorgovski , S. G., Catelan , M., et al. 2017, title The Catalina Surveys Southern periodic variable star catalogue , , 469, 3688, 10.1093/mnras/stx1085

  6. [14]

    Gaia Collaboration , Vallenari , A., Brown , A. G. A., et al. 2023, title Gaia Data Release 3. Summary of the content and survey properties , , 674, A1, 10.1051/0004-6361/202243940

  7. [15]

    B., Yun , M

    Gim , H. B., Yun , M. S., Owen , F. N., et al. 2019, title Nature of Faint Radio Sources in GOODS-North and GOODS-South Fields. I. Spectral Index and Radio-FIR Correlation , , 875, 80, 10.3847/1538-4357/ab1011

  8. [16]

    P., Bechtol, K., Bellm, E., et al

    Guy, L. P., Bechtol, K., Bellm, E., et al. 2025, Rubin Observatory Plans for an Early Science Program, 10.5281/zenodo.15558559

  9. [17]

    R., Millman, K

    Harris, C. R., Millman, K. J., van der Walt, S. J., et al. 2020, title Array programming with NumPy , Nature, 585, 357, 10.1038/s41586-020-2649-2

  10. [18]

    N., Tonry , J

    Heinze , A. N., Tonry , J. L., Denneau , L., et al. 2018, title A First Catalog of Variable Stars Measured by the Asteroid Terrestrial-impact Last Alert System (ATLAS) , , 156, 241, 10.3847/1538-3881/aae47f

  11. [19]

    Hunter, J. D. 2007, title Matplotlib: A 2D graphics environment, Computing in Science & Engineering, 9, 90, 10.1109/MCSE.2007.55

  12. [20]

    F., Salnikov , A., et al

    Jenness , T., Bosch , J. F., Salnikov , A., et al. 2022, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 12189, Software and Cyberinfrastructure for Astronomy VII, 1218911, 10.1117/12.2629569

  13. [21]

    F., Hawley , S

    Kowalski , A. F., Hawley , S. L., Hilton , E. J., et al. 2009, title M Dwarfs in Sloan Digital Sky Survey Stripe 82: Photometric Light Curves and Flare Rate Analysis , , 138, 633, 10.1088/0004-6256/138/2/633

  14. [22]

    Lomb , N. R. 1976, title Least-Squares Frequency Analysis of Unequally Spaced Data , , 39, 447, 10.1007/BF00648343

  15. [23]

    A., Allison , J., et al

    LSST Science Collaboration , Abell , P. A., Allison , J., et al. 2009, title LSST Science Book, Version 2.0 , arXiv e-prints, arXiv:0912.0201, 10.48550/arXiv.0912.0201

  16. [24]

    L., Pruzhinskaya , M

    Malanchev , K. L., Pruzhinskaya , M. V., Korolev , V. S., et al. 2021, title Anomaly detection in the Zwicky Transient Facility DR3 , , 502, 5147, 10.1093/mnras/stab316

  17. [25]

    T., Nair , G., Narayan , G., et al

    Murphey , C. T., Nair , G., Narayan , G., et al. 2025, title YSE Transient Discovery Report for 2025-03-13 , Transient Name Server Discovery Report, 2025-975, 1

  18. [26]

    Rubin Observatory

    NSF-DOE Vera C. Rubin Observatory . 2025, title The Vera C. Rubin Observatory Data Preview 1 , , Technical Note RTN-095, Vera C. Rubin Observatory , 10.71929/rubin/2570536

  19. [27]

    2025, title pandas-dev/pandas: Pandas, , v2.3.0 Zenodo, 10.5281/zenodo.15597513

    pandas development team, T. 2025, title pandas-dev/pandas: Pandas, , v2.3.0 Zenodo, 10.5281/zenodo.15597513

  20. [28]

    2022, title The DECam Young Supernova Experiment , Transient Name Server AstroNote, 24, 1

    Rest , A., Dhawan , S., Mandel , K., et al. 2022, title The DECam Young Supernova Experiment , Transient Name Server AstroNote, 24, 1

  21. [29]

    2015, in Proceedings of the 14th Python in Science Conference, ed

    Rocklin, M. 2015, in Proceedings of the 14th Python in Science Conference, ed. K. Huff & J. Bergstra, 130 -- 136

  22. [30]

    Scargle , J. D. 1982, title Studies in astronomical time series analysis. II. Statistical aspects of spectral analysis of unevenly spaced data. , , 263, 835, 10.1086/160554

  23. [31]

    W., Young , D

    Shingles , L., Smith , K. W., Young , D. R., et al. 2021, title Release of the ATLAS Forced Photometry server for public use , Transient Name Server AstroNote, 7, 1

  24. [32]

    L., Denneau , L., Heinze , A

    Tonry , J. L., Denneau , L., Heinze , A. N., et al. 2018, title ATLAS: A High-cadence All-sky Survey System , , 130, 064505, 10.1088/1538-3873/aabadf

  25. [33]

    2021, title A Systematic Search for Outbursting AM CVn Systems with the Zwicky Transient Facility , , 162, 113, 10.3847/1538-3881/ac0622

    van Roestel , J., Creter , L., Kupfer , T., et al. 2021, title A Systematic Search for Outbursting AM CVn Systems with the Zwicky Transient Facility , , 162, 113, 10.3847/1538-3881/ac0622

  26. [34]

    P., & V \'e ron , P

    V \'e ron-Cetty , M. P., & V \'e ron , P. 2006, title A catalogue of quasars and active nuclei: 12th edition , , 455, 773, 10.1051/0004-6361:20065177

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Reviewed August 6, 2026 · model on record in the stance chip above.