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arxiv: 2603.05586 · v2 · submitted 2026-03-05 · 🌌 astro-ph.SR · astro-ph.EP· astro-ph.GA

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The TESS All-Sky Rotation Survey: Periods for 1,046,317 Stars Within 500 pc

Andrew W. Boyle , Luke G. Bouma , Andrew W. Mann
Authors on Pith no claims yet

Pith reviewed 2026-05-15 14:57 UTC · model grok-4.3

classification 🌌 astro-ph.SR astro-ph.EPastro-ph.GA
keywords stellar rotationTESS photometryrotation periodsstellar variabilitynearby starsall-sky catalogstellar ages
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The pith

The TESS All-Sky Rotation Survey catalogs variability periods for 1,046,317 stars within 500 pc, estimating 93 percent as true rotation periods.

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

The paper introduces the TESS All-Sky Rotation Survey catalog of stellar variability periods drawn from TESS photometry for over a million stars brighter than T magnitude 16 and closer than 500 parsecs. The authors estimate that 93 percent of the reported periods represent genuine stellar rotation after applying corrections for common aliases. This dataset multiplies the count of known rotation periods by a factor of four in that volume and by 2.3 within 100 parsecs. The work also includes a practical method for recovering periods up to 25 days from individual TESS sectors. Public release of the light curves and adjustable analysis code lets other researchers tune the catalog for studies of stellar ages, activity, and Galactic structure.

Core claim

We present the TESS All-Sky Rotation Survey (TARS), an all-sky catalog of stellar variability periods for 1,046,317 stars with T < 16 and distances within 500 pc. We estimate that 93% of these periods are rotation periods. This catalog increases the number of rotation period measurements for stars with T < 16 within 100 pc by a factor of 2.3 and within 500 pc by 4.0. We also present a method to correct half-period aliases in TESS data and show that it reliably recovers periods as long as 25 days from a single TESS sector.

What carries the argument

The half-period alias correction method applied to TESS light curves, which recovers reliable periods up to 25 days from single sectors.

If this is right

  • Quadruples the sample of rotation periods available within 500 pc for studies of stellar magnetic evolution.
  • Supplies a homogeneous foundation for mapping stellar ages across the solar neighborhood.
  • Enables improved characterization of exoplanet host stars through their rotation properties.
  • Provides public light curves as an HLSP and code for users to create custom catalogs with chosen completeness thresholds.

Where Pith is reading between the lines

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

  • Cross-matching the periods with Gaia kinematics could sharpen age estimates for field stars without clusters.
  • The alias-correction technique may transfer to other photometric surveys that share TESS-like sampling gaps.
  • Rotation data at this scale could help trace the distribution of young stellar populations across the disk.

Load-bearing premise

The assumption that 93 percent of the detected periods are genuine stellar rotation periods after alias correction rather than other variability or artifacts.

What would settle it

A targeted follow-up campaign obtaining independent rotation measurements for several hundred catalog stars via ground-based photometry or spectroscopy that yields a confirmation rate well below 93 percent.

Figures

Figures reproduced from arXiv: 2603.05586 by Andrew W. Boyle, Andrew W. Mann, Luke G. Bouma.

Figure 1
Figure 1. Figure 1: Selection function. Top left: Sky coverage. We used TESS images from 2018 July–2025 September; the white gap is where TESS did not observe in Sectors 1–96. Top right: Histogram of number of TESS observations per star; numbers above each bin give the star count. The median star has four sectors of TESS data. Lower left: The TESS magnitude T as a function of the distance to each star in our survey, colored b… view at source ↗
Figure 2
Figure 2. Figure 2: Example vetting plot. Probabilities from our systematics and harmonic classifiers are listed. One such vetting plot is available for each of the 39,044,569 light curves through the TARS High-Level Science Product at MAST. An interactive vetting plot explorer is also available online. each light curve into 100 temporal segments, trained the systematics model on each of the other segments, and applied the re… view at source ↗
Figure 3
Figure 3. Figure 3: Systematics masquerade as period detections. [PITH_FULL_IMAGE:figures/full_fig_p006_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Systematics classifier performance vs. rotation period. [PITH_FULL_IMAGE:figures/full_fig_p007_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Half-period harmonics can be identified at the cost of completeness. [PITH_FULL_IMAGE:figures/full_fig_p008_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Validation of our vetting procedure using Kepler, K2, and ZTF. [PITH_FULL_IMAGE:figures/full_fig_p014_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: The default TARS sample as functions of period, temperature, and amplitude. [PITH_FULL_IMAGE:figures/full_fig_p017_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Our harmonic classifier enables reconstruction of open cluster rotation-temperature sequences. [PITH_FULL_IMAGE:figures/full_fig_p018_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Selecting fast rotators (Prot < 13 days) enhances the visibility of clustered populations. Left: Distribution in Galactocentric X and Y coordinates of all stars in the TARS target list satisfying T < 16 and d < 500 pc. The Sun is marked as a yellow point at the origin. Right: The same sky region, restricted to stars with adopted rotation periods Prot < 13 days. After applying this cut, clustered population… view at source ↗
Figure 10
Figure 10. Figure 10: Gaia DR3 variability classifications in period–temperature and color–magnitude space. [PITH_FULL_IMAGE:figures/full_fig_p021_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: The TARS Prot-Teff plane recovers structures seen in longer baseline surveys. Top left: The default TARS catalog with rotational isochrones from NGC-3532 (D. J. Fritzewski et al. 2021), NGC-6811 (J. L. Curtis et al. 2019a), and Ruprecht-147 (J. L. Curtis et al. 2020) overplotted. The structure in this diagram is discussed in Section 6.6. Top right: The sample of Kepler rotators from A. McQuillan et al. (2… view at source ↗
Figure 12
Figure 12. Figure 12: Photometric binarity is common at fast periods. [PITH_FULL_IMAGE:figures/full_fig_p023_12.png] view at source ↗
Figure 13
Figure 13. Figure 13: The rotation-effective temperature distri [PITH_FULL_IMAGE:figures/full_fig_p024_13.png] view at source ↗
Figure 14
Figure 14. Figure 14: Extra validation plots for our systematics classifier. Top left: Confusion matrix for our negative (systematic) and positive (rotation signal) classes. Top right: ROC curve for this classifier showing the effectiveness of the classifier at distinguishing systematics from probable rotation signals. Bottom left: Histogram showing the probability distribution of each class. The bimodal distribution with a wi… view at source ↗
Figure 15
Figure 15. Figure 15: Extra validation plots for our harmonic classifier. Top left: Confusion matrix for our negative (harmonic) and positive (true rotation signal) classes. Top right: ROC curve for this classifier showing the effectiveness of the classifier at distinguishing harmonics from non-harmonic rotation signals. Bottom left: Histogram showing the probability distribution of each class. Compared to the systematics clas… view at source ↗
read the original abstract

Stellar rotation is a fundamental tracer of stellar magnetic evolution, age, and activity, with broad implications for Galactic archaeology and exoplanet characterization. The Transiting Exoplanet Survey Satellite (TESS) provides high-precision time-series photometry across the sky, enabling rotation measurements for an unprecedented number of stars. We present the TESS All-Sky Rotation Survey (TARS), an all-sky catalog of stellar variability periods for 1,046,317 stars with T < 16 and distances within 500 pc. We estimate that 93% of these periods are rotation periods. This catalog increases the number of rotation period measurements for stars with T < 16 within 100 pc by a factor of 2.3 and within 500 pc by 4.0. We also present a method to correct half-period aliases in TESS data and show that it reliably recovers periods as long as 25 days from a single TESS sector. TARS represents the largest homogeneous catalog of stellar rotation periods to date, providing a foundation for studies of stellar ages, young associations, and Galactic structure. We make the light curves used in our analysis available as a HLSP through MAST. Beyond the default TARS catalog, we provide code that allows users to generate rotation period catalogs with adjustable completeness and reliability thresholds. This code and all rotation period measurements are available through Zenodo.

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

2 major / 3 minor

Summary. The paper presents the TESS All-Sky Rotation Survey (TARS), a catalog containing stellar variability periods for 1,046,317 stars with T < 16 and distances < 500 pc. It claims that 93% of these periods are genuine stellar rotation periods, introduces a half-period alias correction method that recovers periods up to 25 days from a single TESS sector, and reports that the catalog increases the number of rotation measurements by factors of 2.3 (within 100 pc) and 4.0 (within 500 pc) relative to prior work. The light curves, code for adjustable thresholds, and period measurements are made publicly available.

Significance. If the 93% purity and alias-recovery claims are substantiated, TARS would constitute the largest homogeneous stellar rotation catalog to date, directly enabling improved constraints on stellar ages, magnetic evolution, young moving groups, and Galactic structure. The public release of the underlying light curves as an HLSP and the adjustable-threshold code are clear strengths that support reproducibility and community use.

major comments (2)
  1. [§4] §4 (Alias-correction method): the statement that the method 'reliably recovers periods as long as 25 days from a single TESS sector' is not accompanied by any injection-recovery statistics, success fractions, or false-alias rates on simulated light curves with known input periods; without these metrics the 93% purity claim cannot be evaluated.
  2. [§5] §5 / Table 2 (Catalog validation): the 93% purity estimate is presented without quantitative cross-checks against independent rotation catalogs (e.g., Kepler or ground-based surveys) for the overlapping stars, nor any reported false-positive rate from the downstream filtering steps; this is load-bearing for the central catalog claim.
minor comments (3)
  1. [Figure 3] Figure 3: axis labels and color scale for the period distribution are too small to read in print; consider enlarging or splitting into two panels.
  2. [§2.1] §2.1: the distance cut at 500 pc is stated but the corresponding parallax uncertainty threshold or quality cuts on Gaia data are not explicitly listed; add a short table of selection criteria.
  3. [Abstract] The abstract claims a factor-of-4 increase within 500 pc, but no explicit comparison table to the prior largest catalog is provided; a one-row summary table would clarify the gain.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed review of our manuscript. Their comments highlight important areas where additional quantitative validation will strengthen the presentation of the TARS catalog. We address each major comment below and commit to revisions that directly respond to the concerns raised.

read point-by-point responses

  1. Referee: [§4] §4 (Alias-correction method): the statement that the method 'reliably recovers periods as long as 25 days from a single TESS sector' is not accompanied by any injection-recovery statistics, success fractions, or false-alias rates on simulated light curves with known input periods; without these metrics the 93% purity claim cannot be evaluated.

    Authors: We agree that the current manuscript lacks the quantitative injection-recovery statistics needed to fully substantiate the alias-correction performance. In the revised version we will add a dedicated subsection (or expanded §4) presenting results from simulated light curves with injected periods ranging from 1 to 30 days. These tests will report recovery success fractions, false-alias rates, and dependence on signal-to-noise and sector length, directly supporting the claim that periods up to 25 days can be recovered from a single sector and allowing readers to evaluate the 93% purity estimate. revision: yes

  2. Referee: [§5] §5 / Table 2 (Catalog validation): the 93% purity estimate is presented without quantitative cross-checks against independent rotation catalogs (e.g., Kepler or ground-based surveys) for the overlapping stars, nor any reported false-positive rate from the downstream filtering steps; this is load-bearing for the central catalog claim.

    Authors: We acknowledge that the 93% purity figure requires stronger empirical grounding through external validation. In the revised manuscript we will expand §5 to include a quantitative cross-match analysis with the Kepler rotation catalog and selected ground-based surveys for stars in common. We will report agreement fractions, period-difference distributions, and an estimated false-positive rate derived from the filtering pipeline steps. These additions will provide the independent checks requested and allow a more rigorous assessment of catalog reliability. revision: yes

Circularity Check

0 steps flagged

No significant circularity in TARS catalog derivation

full rationale

The paper constructs its catalog by direct processing of TESS light curves to extract periods, with the 93% rotation-period purity estimate presented as the outcome of alias-correction and validation steps applied to the data. No equations, fitted parameters, or claims reduce the reported periods or purity fraction to quantities defined from the output itself or from self-citations that bear the central load. The work remains self-contained against external observational benchmarks and does not invoke uniqueness theorems or ansatzes that collapse back to the present inputs.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on standard assumptions about the origin of photometric variability and the effectiveness of period-finding algorithms; no free parameters or new entities are explicitly introduced in the abstract.

axioms (1)
  • domain assumption Photometric variability in TESS light curves is dominated by rotational modulation from starspots for the majority of stars in the sample.
    This is invoked implicitly when interpreting detected periods as rotation periods and when estimating the 93% purity fraction.

pith-pipeline@v0.9.0 · 5569 in / 1285 out tokens · 79584 ms · 2026-05-15T14:57:29.489553+00:00 · methodology

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Forward citations

Cited by 3 Pith papers

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

  1. NASA's Pandora SmallSat Mission: Simulating the Impact of Stellar Photospheric Heterogeneity and Its Correction

    astro-ph.EP 2026-03 conditional novelty 5.0

    Pandora simulations recover stellar photospheric temperatures to ~30 K with no bias and reduce simple spot contamination from 100-1000 ppm to under 10 ppm, but complex spot geometries leave ~1000 ppm residuals.

  2. A useful representation of TESS light curves

    astro-ph.IM 2026-05 unverdicted novelty 4.0

    A quantile-graph PCA SOM embedding creates a map of 1.5 million TESS light curves where proximity reflects similarity in variability amplitude, timescale, SNR, and shape, with stable positions for repeat observations.

  3. The HAges Catalog: Stellar Ages for High Priority HWO Target Stars

    astro-ph.SR 2026-05 unverdicted novelty 2.0

    The HAges catalog compiles published asteroseismic and gyrochronological ages for 659 HWO target stars, finding that only ~5% have asteroseismic ages and ~20% have gyrochronal ages.

Reference graph

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