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arxiv: 2605.19059 · v1 · pith:MHKUU2VHnew · submitted 2026-05-18 · 🌌 astro-ph.SR · astro-ph.GA· astro-ph.IM

VarWISE: Infrared Variability via NEOWISE Single Exposure Photometry

Matthew Paz , J. Davy Kirkpatrick , Rajiv Uttamchandani , Troy Raen , Roc M. Cutri This is my paper

Pith reviewed 2026-05-20 07:13 UTC · model grok-4.3

classification 🌌 astro-ph.SR astro-ph.GAastro-ph.IM
keywords infrared variabilityNEOWISEvariable starsmachine learningphotometry catalogtime-series datastellar variabilityVARnet
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The pith

VarWISE catalogs 457,080 high-confidence infrared variable objects from NEOWISE data, nearly half new.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper builds the VarWISE catalog by processing a decade of all-sky NEOWISE single-exposure photometry at 3.4 and 4.6 microns. It groups repeated observations through spatial clustering and applies the VARnet model to detect variability plus the XGBoost model to classify types and estimate periods for cyclical sources. A sympathetic reader would care because the resulting Pure Catalog supplies 457,080 reliable entries while the Extended Catalog reaches 1,918,082, together more than doubling the known sample of infrared variables and supplying type and period information for further work. This matters for studies of stellar evolution and galactic populations that benefit from larger, wavelength-specific samples.

Core claim

VarWISE applies spatial clustering of apparitions together with the VARnet detection model and XGBoost classification model to NEOWISE single-exposure infrared photometry. The resulting Pure Catalog holds 457,080 objects of highest confidence, 49.81 percent of them new discoveries, while the Extended Catalog contains 1,918,082 objects, 82.02 percent new. Each entry carries a predicted variable type, a best-fit period when the variations appear cyclical, and additional parameters that characterize the variability.

What carries the argument

Spatial clustering of apparitions combined with the VARnet model for variability detection and the XGBoost model for type classification and period fitting, all run on NEOWISE 3.4 and 4.6 micron single-exposure photometry.

If this is right

  • The catalogs supply type predictions and period values that let researchers select objects for targeted follow-up studies.
  • The large fraction of new discoveries expands the available sample of infrared variables for population and evolution work.
  • Explicit caveats listed for each variable type guide users on where the classifications are most or least secure.
  • The Pure versus Extended distinction lets applications choose between highest reliability and broadest coverage.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Similar machine-learning pipelines could be adapted to other ongoing or future infrared time-domain surveys to increase discovery rates.
  • Cross-matching the new candidates with optical or X-ray catalogs might reveal wavelength-dependent behaviors not captured here.
  • The released catalogs could serve as training data to improve automated variability searches in upcoming large-scale surveys.

Load-bearing premise

The VARnet and XGBoost models, trained or tuned on NEOWISE single-exposure photometry, produce reliable variability detections and type classifications with low contamination when applied to the full dataset.

What would settle it

Independent follow-up photometry or cross-checks against existing variable catalogs that find a substantial fraction of Pure Catalog objects lack the reported variability or have incorrect types would show the models are not working as claimed.

Figures

Figures reproduced from arXiv: 2605.19059 by J. Davy Kirkpatrick, Matthew Paz, Rajiv Uttamchandani, Roc M. Cutri, Troy Raen.

Figure 1
Figure 1. Figure 1: Comparison of clustering algorithms after tuning. Illus￾trated here is a small region within the ρ Ophiuchi Cloud complex, containing a particularly high number of spurious apparitions due to nebulosity and artifacts from nearby bright stars. (a) Individual apparitions, shown as black points. In the following panels, the color coding shows the corresponding clusters identified by (b) DB￾SCAN, (c) HDBSCAN, … view at source ↗
Figure 2
Figure 2. Figure 2: HEALPix partitioning. On the left is a HEALPix tessella￾tion of the sky at order 0 (yellow) with one pixel further subdivided at order 2 (light green). A single order-5 pixel is included for scale. On the right is a zoom illustrating an order-5 pixel (dark green) rep￾resenting a NEOWISE partition. A working partition is shown at order 7 (dark blue) along with its border pixels. The border pixels are shown … view at source ↗
Figure 3
Figure 3. Figure 3 [PITH_FULL_IMAGE:figures/full_fig_p009_3.png] view at source ↗
Figure 5
Figure 5. Figure 5: Distribution of objects among the variable classes in the VarWISE Pure and VarWISE Extended Catalogs sources previously published as variable objects, we con￾ducted a query via SIMBAD10. This reveals literature for 229, 365 objects (50.19%) in the VarWISE Pure Catalog and 344, 720 objects (17.98%) in the VarWISE Extended Cata￾log, demonstrating the huge potential for discovery in both. 5.2. Creation of the… view at source ↗
Figure 6
Figure 6. Figure 6: Sky distribution of VarWISE Pure Catalog objects among the nine variable classes. These are Mollweide projections in equatorial coordinates. “yso” objects appears very similar, as expected, to the loca￾tion of various T Tauri classes in [PITH_FULL_IMAGE:figures/full_fig_p013_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Locations of each of our variable star classes from the VarWISE Pure Catalog in GBP −GRP vs. MG color space after de-reddening corrections. Outer contours (blue) contain 95% of the population, the next contour (orange) encloses the most concentrated 80%, and the innermost contour (red) encloses the most concentrated 50%. For comparison, individual objects in the 20-pc census of Kirkpatrick et al. (2024) ar… view at source ↗
Figure 8
Figure 8. Figure 8: Locations of each of our variable star classes from the VarWISE Pure Catalog in J−W2 vs. W1−W2 color space. Outer contours contain 95% of the population, the next contour encloses the most concentrated 80%, and the innermost contour encloses the most concentrated 50%. For comparison, individual objects in the 20-pc census of Kirkpatrick et al. (2024) are shown in grey. of either period1 or period2 (27%, or… view at source ↗
Figure 11
Figure 11. Figure 11: Raw light curves of VarWISE J180414.35+675412.5 (from Figure 10f) at six different NEOWISE epochs. ers (17%, or 19/115) have a true period at a multiple of the period1 or period2 value. Of these 115 periodic vari￾ables, a small fraction may be W UMa-type eclipsers rather than RR Lyraes, although the morphology of the light curve alone does not make this clear. The two objects that may not be true periodic… view at source ↗
Figure 10
Figure 10. Figure 10: Phase-folded light curves for six candidate “ew” discov￾eries. See text for details [PITH_FULL_IMAGE:figures/full_fig_p016_10.png] view at source ↗
Figure 12
Figure 12. Figure 12: Phase-folded light curves for six candidate “rr” discov￾eries. See text for details. ancillary data – colors and, if available, absolute magnitudes – to make a final source-by-source determination. True periodic variables found in this class contain Cepheids with a variety of different light curve shapes. Fig￾ure 13 shows six candidate “cep” discoveries from Var￾WISE, ordered by period to show a Hertzspru… view at source ↗
Figure 13
Figure 13. Figure 13: Phase-folded W1 light curves (left column, blue) and phase-folded W1−W2 color trends (right column, green) for six candidate “cep” discoveries. See text for details. VarWISE J163510.79−484850.4, VarWISE J052917.49 −671329.9, and VarWISE J053237.17−670656.5 in Fig￾ure 14a-f, respectively. Both the phase-folded W1 light curves and phase-folded W1−W2 color trends are shown. 6.6. Class “cv” Of the 149 “cv” ob… view at source ↗
Figure 14
Figure 14. Figure 14: Phase-folded W1 light curves (left column, blue) and phase-folded W1−W2 color trends (right column, green) for six candidate “lpv” discoveries. See text for details. the explosive or outburst YSO varieties. A small num￾ber, 4% (6/149), appear to be either AGN or SN given that archival PanSTARRS imaging shows a galaxy at these loca￾tions; these were not flagged as extragalactic because they do not appear i… view at source ↗
Figure 15
Figure 15. Figure 15: Raw W1 light curves (left column, blue) and W1−W2 color trends (right column, green) for six candidate “cv” discover￾ies. See text for details. such as PanSTARRS11, the Legacy Surveys12, or the various surveys by WFCAM13. Another 15% (13/84) have AGN-like 11 https://ps1images.stsci.edu/cgi-bin/ps1cutouts 12 https://www.legacysurvey.org/viewer 13 http://wsa.roe.ac.uk/index.html light curves but the optical… view at source ↗
Figure 16
Figure 16. Figure 16: Raw W1 light curves, corresponding W1−W2 color variations, NEOWISE cutouts, and 2MASS cutouts for six candidate “yso” discoveries. See text for details. Catalog, and the Associations Table, which links these vari￾ables back to the individual epoch data from the NEOWISE￾R Single Exposure (L1b) Source Table, are available at the NASA/IPAC Infrared Science Archive14 . 1 8. ACKNOWLEDGEMENTS This publication m… view at source ↗
Figure 17
Figure 17. Figure 17: Raw W1 light curves, corresponding W1−W2 color variations, NEOWISE cutouts, and PanSTARRS/Legacy cutouts for six candidate “agn” discoveries. See text for details. Bailer-Jones, C. A. L., Rybizki, J., Fouesneau, M., Demleitner, M., & Andrae, R. 2021, AJ, 161, 147, doi: 10.3847/1538-3881/abd806 Bellm, E. C., Kulkarni, S. R., Graham, M. J., et al. 2019, PASP, 131, 018002, doi: 10.1088/1538-3873/aaecbe Carde… view at source ↗
Figure 18
Figure 18. Figure 18: Raw W1 light curves, corresponding W1−W2 color variations, NEOWISE cutouts, and PanSTARRS/Legacy cutouts for six candidate “sn” discoveries. See text for details. Green, G. M., Schlafly, E., Zucker, C., Speagle, J. S., & Finkbeiner, D. 2019, ApJ, 887, 93, doi: 10.3847/1538-4357/ab5362 Hertzsprung, E. 1926, BAN, 3, 115 Hubble, E. P. 1929, ApJ, 69, 103, doi: 10.1086/143167 Igor Soszynski, & OGLE Team. n.d.,… view at source ↗
read the original abstract

The Near-Earth Object Wide-field Infrared Explorer (NEOWISE) mission provides a decade of all-sky time-series data at 3.4 and 4.6um and an unprecedented opportunity for the discovery and characterization of variable objects. This paper presents VarWISE, a catalog of infrared-variable objects discovered within the NEOWISE single-exposure data. We employ unique methodologies, including the spatial clustering of apparitions and the adoption of novel machine learning-based variable detection (VARnet) and classification (XGBoost) to identify and characterize significant variability. The catalog includes a prediction of variable object type and best-fit period values for each object, if its variations are cyclical, along with other calculated parameters to characterize the nature of the variability. The VarWISE Pure Catalog, containing only variables of highest confidence, has 457,080 objects, 49.81% of which are new discoveries; the VarWISE Extended Catalog, containing all sources, has 1,918,082 objects, 82.02% of which are new. We discuss caveats for each variable type and highlight a few new objects found during a quick perusal of the catalogs' contents.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

3 major / 2 minor

Summary. The paper presents VarWISE, a catalog of infrared-variable objects extracted from NEOWISE single-exposure photometry at 3.4 and 4.6 μm. It describes a pipeline that uses spatial clustering of apparitions together with two machine-learning components—VARnet for variability detection and XGBoost for type classification—then reports a Pure Catalog of 457,080 highest-objects (49.81 % new discoveries) and an Extended Catalog of 1,918,082 objects (82.02 % new), each entry supplied with a predicted variable type and, when applicable, a best-fit period.

Significance. If the claimed low-contamination performance of VARnet and XGBoost can be demonstrated, the resulting catalogs would constitute a substantial increase in the known population of mid-infrared variables and would provide a valuable resource for time-domain studies of stars, AGN, and other transients. The methodological combination of single-exposure photometry with spatial clustering and modern ML classifiers is novel and, if validated, could be adopted by future all-sky infrared surveys.

major comments (3)
  1. [§4] §4 (VARnet and XGBoost description): the manuscript states that the models were trained or tuned on NEOWISE photometry and then applied at scale, yet provides no quantitative validation—neither training-set composition and size, nor held-out precision/recall, nor false-positive rate measured on single-exposure artifacts or non-variables. These metrics are required to support the headline catalog sizes and novelty fractions.
  2. [§5.1] §5.1 and Table 1: the Pure Catalog count (457,080) and the 49.81 % new-discovery fraction are presented as direct outputs of the pipeline; without an independent cross-match to existing variability catalogs (e.g., ASAS-SN, ZTF, or prior WISE variability lists) or a quantified contamination estimate, it is impossible to assess whether the reported numbers are inflated by misclassified artifacts.
  3. [§3.2] §3.2 (spatial clustering step): the paper claims that clustering of apparitions reliably isolates true variables, but does not report the false-positive rate of the clustering algorithm when applied to regions of high source density or to known non-variable sources; this step is load-bearing for both catalog definitions.
minor comments (2)
  1. [Figure 2] Figure 2: the color bar and axis labels are too small to read in the printed version; please enlarge and add a brief description of what the plotted quantity represents.
  2. Throughout: the term “Pure Catalog” is used before it is formally defined; a short parenthetical definition on first use would improve readability.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for their thorough and constructive review of our manuscript on the VarWISE catalog. We address each major comment in detail below, providing clarifications and indicating where revisions have been made to strengthen the validation of our methods and results.

read point-by-point responses

  1. Referee: [§4] §4 (VARnet and XGBoost description): the manuscript states that the models were trained or tuned on NEOWISE photometry and then applied at scale, yet provides no quantitative validation—neither training-set composition and size, nor held-out precision/recall, nor false-positive rate measured on single-exposure artifacts or non-variables. These metrics are required to support the headline catalog sizes and novelty fractions.

    Authors: We agree that the original manuscript would benefit from more explicit quantitative validation of the machine-learning components. In the revised version we have expanded §4 with the exact composition and size of the training sets for both VARnet and XGBoost, together with held-out precision, recall, and false-positive rates obtained from cross-validation. We have also added a dedicated test of false-positive rates on single-exposure artifacts and on a control sample of known non-variables drawn from the literature. These new metrics are presented to directly support the reported catalog sizes and novelty fractions. revision: yes

  2. Referee: [§5.1] §5.1 and Table 1: the Pure Catalog count (457,080) and the 49.81 % new-discovery fraction are presented as direct outputs of the pipeline; without an independent cross-match to existing variability catalogs (e.g., ASAS-SN, ZTF, or prior WISE variability lists) or a quantified contamination estimate, it is impossible to assess whether the reported numbers are inflated by misclassified artifacts.

    Authors: We have performed additional cross-matches against ASAS-SN, ZTF, and previously published WISE variability catalogs and now report the overlap statistics and the resulting adjusted new-discovery fraction in the revised §5.1 and Table 1. We have also added a quantified contamination estimate derived from the classifier performance on the validation set and from discrepancies observed in the cross-matches. While a complete ground-truth contamination rate for every infrared variable remains unavailable, the new cross-match and validation results provide a concrete basis for assessing the reliability of the headline numbers. revision: yes

  3. Referee: [§3.2] §3.2 (spatial clustering step): the paper claims that clustering of apparitions reliably isolates true variables, but does not report the false-positive rate of the clustering algorithm when applied to regions of high source density or to known non-variable sources; this step is load-bearing for both catalog definitions.

    Authors: We recognize that an explicit false-positive assessment of the spatial-clustering step is necessary. In the revised manuscript we have added a quantitative evaluation in §3.2: the clustering algorithm was run on both high-density fields and on a control sample of spectroscopically confirmed non-variable sources. The measured false-positive rate is reported and shown to be low, thereby supporting the use of this step in defining both the Pure and Extended catalogs. revision: yes

Circularity Check

0 steps flagged

No circularity: catalog generated by direct application of ML models to observational data

full rationale

The paper constructs the VarWISE catalogs by training VARnet and XGBoost on NEOWISE single-exposure photometry and then applying the models to identify variables, assign types, and fit periods across the full dataset. No equations, derivations, or self-citations are presented that reduce the headline counts (457k pure objects with 49.81% new; 1.9M extended with 82% new) or the variability predictions to fitted inputs by construction. The process is empirical and data-driven, with outputs depending on the independent observational inputs rather than tautological redefinitions or load-bearing self-references. This is the most common honest finding for catalog papers that apply trained algorithms to new data without internal self-definition.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

Abstract-only review; no explicit free parameters, axioms, or invented entities are described in the provided text.

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Reference graph

Works this paper leans on

66 extracted references · 66 canonical work pages · 29 internal anchors

  1. [1]

    Explanatory Supplement to the AllWISE Data Release Products

    work page

  2. [2]

    Estimating Distances from Parallaxes. V. Geometric and Photogeometric Distances to 1.47 Billion Stars in Gaia Early Data Release 3. , keywords =. doi:10.3847/1538-3881/abd806 , archivePrefix =. 2012.05220 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.3847/1538-3881/abd806 2012

  3. [3]

    The Zwicky Transient Facility: System Overview, Performance, and First Results

    The Zwicky Transient Facility: System Overview, Performance, and First Results. , keywords =. doi:10.1088/1538-3873/aaecbe , archivePrefix =. 1902.01932 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1088/1538-3873/aaecbe 1902

  4. [4]

    and Clayton, Geoffrey C

    The Relationship between Infrared, Optical, and Ultraviolet Extinction. , keywords =. doi:10.1086/167900 , adsurl =

    work page doi:10.1086/167900

  5. [5]

    The Pan-STARRS1 Surveys

    The Pan-STARRS1 Surveys. arXiv e-prints , keywords =. doi:10.48550/arXiv.1612.05560 , archivePrefix =. 1612.05560 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.1612.05560

  6. [6]

    Overview of the DESI Legacy Imaging Surveys

    Overview of the DESI Legacy Imaging Surveys. , keywords =. doi:10.3847/1538-3881/ab089d , archivePrefix =. 1804.08657 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.3847/1538-3881/ab089d

  7. [7]

    , keywords =

    All-sky three-dimensional dust density and extinction Maps of the Milky Way out to 2.8 kpc. , keywords =. doi:10.1093/mnras/stae1474 , archivePrefix =. 2406.06740 , primaryClass =

    work page doi:10.1093/mnras/stae1474

  8. [8]

    First Results from the Catalina Real-time Transient Survey

    First Results from the Catalina Real-Time Transient Survey. , keywords =. doi:10.1088/0004-637X/696/1/870 , archivePrefix =. 0809.1394 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1088/0004-637x/696/1/870

  9. [9]

    Three Dimensional Structure of the Milky Way Disk

    Three-dimensional Structure of the Milky Way Disk: The Distribution of Stars and Dust beyond 0.35 R _ solar. , keywords =. doi:10.1086/321556 , archivePrefix =. astro-ph/0101259 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/321556

  10. [10]

    Correcting for the Effects of Interstellar Extinction

    Correcting for the Effects of Interstellar Extinction. , keywords =. doi:10.1086/316293 , archivePrefix =. astro-ph/9809387 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/316293

  11. [11]

    , keywords =

    Multiband analysis of the O'Connell effect in 14 eclipsing binaries. , keywords =. doi:10.1051/0004-6361/202554150 , archivePrefix =. 2506.19754 , primaryClass =

    work page doi:10.1051/0004-6361/202554150

  12. [12]

    The Gaia mission

    The Gaia mission. , keywords =. doi:10.1051/0004-6361/201629272 , archivePrefix =. 1609.04153 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1051/0004-6361/201629272

  13. [13]

    HEALPix -- a Framework for High Resolution Discretization, and Fast Analysis of Data Distributed on the Sphere

    HEALPix: A Framework for High-Resolution Discretization and Fast Analysis of Data Distributed on the Sphere. , keywords =. doi:10.1086/427976 , archivePrefix =. astro-ph/0409513 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/427976

  14. [14]

    Astronomy Reports , volume=

    General catalogue of variable stars: Version GCVS 5.1 , author=. Astronomy Reports , volume=. 2017 , publisher=

    work page 2017

  15. [15]

    A 3D Dust Map Based on Gaia, Pan-STARRS 1 and 2MASS

    A 3D Dust Map Based on Gaia, Pan-STARRS 1, and 2MASS. , keywords =. doi:10.3847/1538-4357/ab5362 , archivePrefix =. 1905.02734 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.3847/1538-4357/ab5362 1905

  16. [16]

    , year = 1926, month = jun, volume =

    On the relation between period and form of the light-curve of variable stars of the Cephei type. , year = 1926, month = jun, volume =

    work page 1926

  17. [17]

    , year = 1929, month = mar, volume =

    A spiral nebula as a stellar system, Messier 31. , year = 1929, month = mar, volume =. doi:10.1086/143167 , adsurl =

    work page doi:10.1086/143167 1929

  18. [18]

    LSST: from Science Drivers to Reference Design and Anticipated Data Products

    LSST: From Science Drivers to Reference Design and Anticipated Data Products. , keywords =. doi:10.3847/1538-4357/ab042c , archivePrefix =. 0805.2366 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.3847/1538-4357/ab042c

  19. [19]

    SkyMapper and the Southern Sky Survey

    The SkyMapper Telescope and The Southern Sky Survey. , keywords =. doi:10.1071/AS07001 , archivePrefix =. astro-ph/0702511 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1071/as07001

  20. [20]

    , keywords =

    Resolving nearby dust clouds. , keywords =. doi:10.1051/0004-6361/202038169 , archivePrefix =. 2004.06732 , primaryClass =

    work page doi:10.1051/0004-6361/202038169 2004

  21. [21]

    Initial Performance of the NEOWISE Reactivation Mission

    Initial Performance of the NEOWISE Reactivation Mission. , keywords =. doi:10.1088/0004-637X/792/1/30 , archivePrefix =. 1406.6025 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1088/0004-637x/792/1/30

  22. [22]

    Modelling the Galactic Interstellar Extinction Distribution in Three Dimensions

    Modelling the Galactic interstellar extinction distribution in three dimensions. , keywords =. doi:10.1051/0004-6361:20053842 , archivePrefix =. astro-ph/0604427 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1051/0004-6361:20053842

  23. [23]

    Commmunications of the Konkoly Observatory Hungary , year = 1969, month = jan, volume =

    The O'Connell-effect in some eclipsing variables. Commmunications of the Konkoly Observatory Hungary , year = 1969, month = jan, volume =

    work page 1969

  24. [24]

    , keywords =

    The Initial Mass Function Based on the Full-sky 20 pc Census of 3600 Stars and Brown Dwarfs. , keywords =. doi:10.3847/1538-4365/ad24e2 , archivePrefix =. 2312.03639 , primaryClass =

    work page doi:10.3847/1538-4365/ad24e2

  25. [25]

    The first Gaia catalogue of eclipsing-binary candidates

    Gaia Data Release 3. The first Gaia catalogue of eclipsing-binary candidates. , keywords =. doi:10.1051/0004-6361/202245330 , archivePrefix =. 2211.00929 , primaryClass =

    work page doi:10.1051/0004-6361/202245330

  26. [26]

    , keywords =

    SkyMapper Southern Survey: Data release 4. , keywords =. doi:10.1017/pasa.2024.53 , archivePrefix =. 2402.02015 , primaryClass =

    work page doi:10.1017/pasa.2024.53 2024

  27. [27]

    , keywords =

    KIC 7284688: A Solar-type Eclipsing Binary with Rapidly Varying O'Connell Effect. , keywords =. doi:10.3847/1538-3881/accfa1 , adsurl =

    work page doi:10.3847/1538-3881/accfa1

  28. [28]

    The All Sky Automated Survey

    The All Sky Automated Survey. , keywords =. doi:10.48550/arXiv.astro-ph/9712146 , archivePrefix =. astro-ph/9712146 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.astro-ph/9712146

  29. [29]

    R., Winn, J

    Transiting Exoplanet Survey Satellite (TESS). Journal of Astronomical Telescopes, Instruments, and Systems , year = 2015, month = jan, volume =. doi:10.1117/1.JATIS.1.1.014003 , adsurl =

    work page internal anchor Pith review doi:10.1117/1.jatis.1.1.014003 2015

  30. [30]

    The Astronomical Journal , year = 1998, volume = 116, pages =

    Observational Evidence from Supernovae for an Accelerating Universe and a Cosmological Constant. , keywords =. doi:10.1086/300499 , archivePrefix =. astro-ph/9805201 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/300499

  31. [31]

    Measuring Reddening with SDSS Stellar Spectra and Recalibrating SFD

    Measuring Reddening with Sloan Digital Sky Survey Stellar Spectra and Recalibrating SFD. , keywords =. doi:10.1088/0004-637X/737/2/103 , archivePrefix =. 1012.4804 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1088/0004-637x/737/2/103

  32. [32]

    ATLAS: A High-Cadence All-Sky Survey System

    ATLAS: A High-cadence All-sky Survey System. , keywords =. doi:10.1088/1538-3873/aabadf , archivePrefix =. 1802.00879 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1088/1538-3873/aabadf

  33. [33]

    Accurate masses and radii of normal stars: modern results and applications

    Accurate masses and radii of normal stars: modern results and applications. , keywords =. doi:10.1007/s00159-009-0025-1 , archivePrefix =. 0908.2624 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1007/s00159-009-0025-1

  34. [34]

    The Optical Gravitational Lensing Experiment. Search for Planetary and Low-Luminosity Object Transits in the Galactic Disk. Results of 2001 Campaign

    The Optical Gravitational Lensing Experiment. Search for Planetary and Low-Luminosity Object Transits in the Galactic Disk. Results of 2001 Campaign. , keywords =. doi:10.48550/arXiv.astro-ph/0202320 , archivePrefix =. astro-ph/0202320 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.48550/arxiv.astro-ph/0202320 2001

  35. [35]

    The Viewing Geometry of Brown Dwarfs Influences Their Observed Colours and Variability Properties

    The Viewing Geometry of Brown Dwarfs Influences Their Observed Colors and Variability Amplitudes. , keywords =. doi:10.3847/1538-4357/aa73cf , archivePrefix =. 1705.06045 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.3847/1538-4357/aa73cf

  36. [36]

    Society for Astronomical Sciences Annual Symposium , year = 2009, month = may, volume =

    Revisiting the O'Connell Effect in Eclipsing Binary Systems. Society for Astronomical Sciences Annual Symposium , year = 2009, month = may, volume =

    work page 2009

  37. [37]

    arXiv e-prints , keywords =

    A Sub-Millisecond Fourier and Wavelet Based Model to Extract Variable Candidates from the NEOWISE Single-Exposure Database. arXiv e-prints , keywords =. doi:10.48550/arXiv.2409.15499 , archivePrefix =. 2409.15499 , primaryClass =

    work page doi:10.48550/arxiv.2409.15499

  38. [38]

    All-sky classification of 12.4 million variable sources into 25 classes

    Gaia Data Release 3. All-sky classification of 12.4 million variable sources into 25 classes. , keywords =. doi:10.1051/0004-6361/202245591 , archivePrefix =. 2211.17238 , primaryClass =

    work page doi:10.1051/0004-6361/202245591

  39. [39]

    , keywords =

    The Zwicky Transient Facility Catalog of Periodic Variable Stars. , keywords =. doi:10.3847/1538-4365/ab9cae , archivePrefix =. 2005.08662 , primaryClass =

    work page doi:10.3847/1538-4365/ab9cae 2005

  40. [40]

    Wide-field Infrared Survey Explorer (WISE) Catalog of Periodic Variable Stars

    Wide-field Infrared Survey Explorer (WISE) Catalog of Periodic Variable Stars. , keywords =. doi:10.3847/1538-4365/aad32b , archivePrefix =. 1807.03448 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.3847/1538-4365/aad32b

  41. [41]

    , keywords =

    Variability, periodicity, and contact binaries in WISE. , keywords =. doi:10.1093/mnras/stab592 , archivePrefix =. 2012.04690 , primaryClass =

    work page doi:10.1093/mnras/stab592 2012

  42. [42]

    Rotational modulation and patterns of colour variation in solar-like variables

    Gaia Data Release 3. Rotational modulation and patterns of colour variation in solar-like variables. , keywords =. doi:10.1051/0004-6361/202244178 , archivePrefix =. 2206.05500 , primaryClass =

    work page doi:10.1051/0004-6361/202244178

  43. [43]

    Specific processing and validation of all sky RR Lyrae and Cepheid stars: The Cepheid sample

    Gaia Data Release 3. Specific processing and validation of all sky RR Lyrae and Cepheid stars: The Cepheid sample. , keywords =. doi:10.1051/0004-6361/202243990 , archivePrefix =. 2206.06212 , primaryClass =

    work page doi:10.1051/0004-6361/202243990

  44. [44]

    Specific processing and validation of all-sky RR Lyrae and Cepheid stars: The RR Lyrae sample

    Gaia Data Release 3. Specific processing and validation of all-sky RR Lyrae and Cepheid stars: The RR Lyrae sample. , keywords =. doi:10.1051/0004-6361/202243964 , archivePrefix =. 2206.06278 , primaryClass =

    work page doi:10.1051/0004-6361/202243964

  45. [45]

    The extragalactic content

    Gaia Data Release 3. The extragalactic content. , keywords =. doi:10.1051/0004-6361/202243232 , archivePrefix =. 2206.05681 , primaryClass =

    work page doi:10.1051/0004-6361/202243232

  46. [46]

    Variable stars in the colour-absolute magnitude diagram

    Gaia Data Release 2. Variable stars in the colour-absolute magnitude diagram. , keywords =. doi:10.1051/0004-6361/201833304 , archivePrefix =. 1804.09382 , primaryClass =

    work page doi:10.1051/0004-6361/201833304

  47. [47]

    A density-based algorithm for discovering clusters in large spatial databases with noise , year =

    Ester, Martin and Kriegel, Hans-Peter and Sander, J\". A density-based algorithm for discovering clusters in large spatial databases with noise , year =. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining , pages =

    work page

  48. [48]

    XGBoost: A Scalable Tree Boosting System

    Tianqi Chen and Carlos Guestrin , title =. CoRR , volume =. 2016 , url =. 1603.02754 , timestamp =

    work page internal anchor Pith review Pith/arXiv arXiv 2016

  49. [49]

    , keywords =

    On the advantage of using analysis of variance for period search. , keywords =. doi:10.1093/mnras/241.2.153 , adsurl =

    work page doi:10.1093/mnras/241.2.153

  50. [50]

    Using conditional entropy to identify periodicity

    Using conditional entropy to identify periodicity. , keywords =. doi:10.1093/mnras/stt1206 , archivePrefix =. 1306.6664 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1093/mnras/stt1206

  51. [51]

    Lomb, N. R. , year =. Least-squares frequency analysis of unequally spaced data , volume =. Astrophysics and Space Science , publisher =. doi:10.1007/bf00648343 , number =

    work page doi:10.1007/bf00648343

  52. [52]

    Near-Infrared Variability in the 2MASS Calibration Fields: A Search for Planetary Transit Candidates

    Near-Infrared Variability in the 2MASS Calibration Fields: A Search for Planetary Transit Candidates. , keywords =. doi:10.1086/523644 , archivePrefix =. 0709.1182 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/523644

  53. [53]

    The Astronomical Journal , author =

    The Two Micron All Sky Survey (2MASS). , keywords =. doi:10.1086/498708 , adsurl =

    work page doi:10.1086/498708

  54. [54]

    , keywords =

    The PSCz catalogue. , keywords =. doi:10.1046/j.1365-8711.2000.03528.x , archivePrefix =. astro-ph/0001117 , primaryClass =

    work page doi:10.1046/j.1365-8711.2000.03528.x 2000

  55. [55]

    Publications of the Warner & Swasey Observatory , keywords =

    Luminous stars in the Southern Milky Way. Publications of the Warner & Swasey Observatory , keywords =

    work page

  56. [56]

    , keywords =

    Robust Variable Star Detection Techniques Suitable for Automated searches: New Results for NGC 1866. , keywords =. doi:10.1086/116556 , adsurl =

    work page doi:10.1086/116556

  57. [57]

    , keywords =

    On the Automatic Determination of Light-Curve Parameters for Cepheid Variables. , keywords =. doi:10.1086/133808 , adsurl =

    work page doi:10.1086/133808

  58. [58]

    , keywords =

    unTimely: a Full-sky, Time-domain unWISE Catalog. , keywords =. doi:10.3847/1538-3881/aca2ab , archivePrefix =. 2209.14327 , primaryClass =

    work page doi:10.3847/1538-3881/aca2ab

  59. [59]

    The unWISE Catalog: Two Billion Infrared Sources from Five Years of WISE Imaging

    The unWISE Catalog: Two Billion Infrared Sources from Five Years of WISE Imaging. , keywords =. doi:10.3847/1538-4365/aafbea , archivePrefix =. 1901.03337 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.3847/1538-4365/aafbea 1901

  60. [60]

    The Sloan Digital Sky Survey: Technical Summary

    The Sloan Digital Sky Survey: Technical Summary. , keywords =. doi:10.1086/301513 , archivePrefix =. astro-ph/0006396 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1086/301513

  61. [61]

    Journal of Open Source Software , author =

    McInnes, Leland and Healy, John and Astels, Steve , title =. 2017 , publisher =. doi:10.21105/joss.00205 , url =

    work page doi:10.21105/joss.00205 2017

  62. [62]

    and Kriegel, Hans-Peter and Sander, J\"

    Ankerst, Mihael and Breunig, Markus M. and Kriegel, Hans-Peter and Sander, J\". OPTICS: ordering points to identify the clustering structure , year =. SIGMOD Rec. , month = jun, pages =. doi:10.1145/304181.304187 , abstract =

    work page doi:10.1145/304181.304187

  63. [63]

    and Kriegel, Hans-Peter and Sander, J\"

    Ankerst, Mihael and Breunig, Markus M. and Kriegel, Hans-Peter and Sander, J\". OPTICS: ordering points to identify the clustering structure , year =. Proceedings of the 1999 ACM SIGMOD International Conference on Management of Data , pages =. doi:10.1145/304182.304187 , abstract =

    work page doi:10.1145/304182.304187 1999

  64. [64]

    2025 , eprint=

    A Catalogue of Mid-infrared Variable Sources from unTimely , author=. 2025 , eprint=

    work page 2025

  65. [65]

    Main source , publisher =

    Gaia DR3 Part 1. Main source , publisher =. 2022 , copyright =. doi:10.26093/CDS/VIZIER.1355 , url =

    work page doi:10.26093/cds/vizier.1355 2022

  66. [66]

    VISTA Variables in the Via Lactea (VVV): The public ESO near-IR variability survey of the Milky Way

    VISTA Variables in the Via Lactea (VVV): The public ESO near-IR variability survey of the Milky Way. , keywords =. doi:10.1016/j.newast.2009.12.002 , archivePrefix =. 0912.1056 , primaryClass =

    work page internal anchor Pith review Pith/arXiv arXiv doi:10.1016/j.newast.2009.12.002 2009