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arxiv: 2605.15757 · v1 · pith:6O3AGWCZnew · submitted 2026-05-15 · 🌌 astro-ph.SR

Binarity at LOw Metallicity (BLOeM): massive star variability revealed using a novel software tool for point-spread function fitting of TESS images

Pith reviewed 2026-05-19 19:37 UTC · model grok-4.3

classification 🌌 astro-ph.SR
keywords massive starsTESS photometrystochastic low-frequency variabilitySmall Magellanic CloudbinarityasteroseismologyPSF fittinglight curve extraction
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The pith

A PSF-fitting method extracts clean TESS light curves for 91 massive stars in the SMC, showing their stochastic low-frequency variability follows patterns similar to those in the Milky Way.

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

The paper presents a new point-spread function fitting tool called Lemons to extract light curves from TESS images of faint, crowded massive stars in the Small Magellanic Cloud. This overcomes limitations of simple aperture photometry that often includes contamination from nearby stars. With accurate light curves for 91 stars, the authors identify variability from binarity, pulsations, and stochastic low-frequency signals. The morphology of the stochastic variability appears to indicate a star's position in the Hertzsprung-Russell diagram in the same way it does for higher-metallicity Galactic stars. This suggests the physical mechanism behind the variability could be largely independent of a star's metal content.

Core claim

Using the Lemons PSF-based extraction on TESS data, light curves of SMC massive stars reveal stochastic low-frequency variability whose morphology probes the star's location in the Hertzsprung-Russell diagram similarly to Galactic massive stars, indicating that the underlying physical mechanism could be insensitive to metallicity.

What carries the argument

The Lemons point-spread function fitting procedure, which models the PSF to extract uncontaminated light curves from crowded TESS images of faint stars.

If this is right

  • The extracted light curves show indications of binarity including eclipses and ellipsoidal modulation.
  • Stellar pulsations appear in the low-metallicity SMC massive stars.
  • SLF variability morphology can locate stars within the Hertzsprung-Russell diagram.
  • The close match to Galactic stars implies the driving mechanism does not strongly depend on metallicity.

Where Pith is reading between the lines

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

  • The Lemons technique could be applied to TESS observations of massive stars in other crowded or distant fields.
  • If the mechanism proves metallicity-insensitive, evolution models for massive stars may require fewer environment-specific adjustments.
  • Targeted follow-up photometry could test whether specific SLF features correlate with parameters beyond HR-diagram position.

Load-bearing premise

The Lemons PSF-fitting procedure removes crowding contamination without introducing systematic artifacts that could mimic or distort the reported SLF variability patterns.

What would settle it

Re-extraction of the same TESS data with an independent method or ground-based observations that yield substantially different SLF morphology for the same stars would undermine the claimed similarity to Galactic patterns.

Figures

Figures reproduced from arXiv: 2605.15757 by Ankur Kalita, Daniel Pauli, Dominic M. Bowman, Jan Henneco, Julia Bodensteiner, Laurent Mahy, Lee Patrick, Maude Gull, Micha{\l} Pawlak, Norbert Langer, Paul A. Crowther, Pieterjan J. Van Daele, Roey Ovadia, Tomer Shenar, Zehava Katabi.

Figure 1
Figure 1. Figure 1: The locations in the HR diagram of all BLOeM targets (Shenar et al. 2024) are shown in grey using parameters from Bestenlehner et al. (2025) and Shenar et al. (2024). The targets with successfully extracted PSF TESS light curves are overplotted as blue diamonds and are delimited by the TESS brightness limit of about 𝐺 < 15 mag, which is indicated by the red-dashed line. Note that PSF sub-sample is biased t… view at source ↗
Figure 2
Figure 2. Figure 2: Spatial location of the BLOeM targets for which a successful PSF light curve have been extracted. Figure adapted from Shenar et al. (2024). in an image is extracted as the weighted sum over the pixel flux value, where different weights are assigned to each pixel according to the Gaussian PSF shape integrated over the pixel’s area. In our initial testing, we found that differences in the optical path for [… view at source ↗
Figure 4
Figure 4. Figure 4: The relative path of the centroid for sector 68 of selected SMC massive stars, each labelled with their BLOeM identifier and colour-coded with the stars TESS magnitude. The 1𝜎 errors on these centroid positions are typically 0.05 ∼ 0.1 in terms of the pixel size. by Han & Brandt (2023). However, the tests performed by Van Daele (2023) illustrated that the assumption of circularly symmetric PSFs are suffici… view at source ↗
Figure 5
Figure 5. Figure 5: shows the light curve of BLOeM 4-058 (Sk 80; GAIA DR3 4690516677131714432), which is a ∼ 60 M⊙ O7Iaf+ supergiant 4 https://github.com/pieterjanv314/Lemons/tree/main/ tutorial 5 www.zenodo.org/TBD [PITH_FULL_IMAGE:figures/full_fig_p006_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Demonstration of similar noise properties (i.e. jitter) between the 3 × 3 SAP light curve and the PSF light curve in TESS sector 68 for BLOeM 2-065 (AzV 121; GAIA DR3 4688967568356557440). 2.4.2 BLOeM 2-065: PSF light curve of an isolated constant star The jitter in addition to the systematic movement of the PSF centroids of all BLOeM stars (cf [PITH_FULL_IMAGE:figures/full_fig_p007_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Comparison of TESS PSF and OGLE 𝐼-band light curves for two known binaries. The OGLE data is taken from Glowacki et al. (2025). The top and bottom panels show the phase folded OGLE (black, with offset) and PSF TESS (blue) light curves for BLOeM 1- 011 (GAIA DR3 4690506712804881792) and BLOeM 5-050 (GAIA DR3 4687501953697501568), respectively. The orbital period, indicated above each plot, extracted from TE… view at source ↗
Figure 8
Figure 8. Figure 8: PSF light curve and Lomb-Scargle periodogram of BLOeM 1-040 (GAIA DR3 4690525438865707904), which has gravity-mode pulsations typical of an Oe/Be star. Bowman et al. (2024) found little difference in the morphologies of SLF variability across Galactic, LMC and SMC massive stars. Their sample spanned a range of masses and ages, and specifically included stars both inside and outside of the transparency wind… view at source ↗
Figure 9
Figure 9. Figure 9: PSF light curve and Lomb-Scargle periodogram of BLOeM 1- 009 (GAIA DR3 4690520387983090432), which is a typical example of a massive star with SLF variability. sector 28 are shown in [PITH_FULL_IMAGE:figures/full_fig_p009_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Phase folded light curves of targets with spectroscopically con￾firmed binary periods which agree with our PSF TESS light curves. The BLOeM identifier and binary period, 𝑃, are mentioned in each subplot’s title. The vertical axis has the same scale for all plots for comparison reasons. and 8-097. Therefore, in this work we provide photometric periods to assist in solving these candidate binary systems in … view at source ↗
Figure 11
Figure 11. Figure 11: Phase folded light curves of targets with photometric indications of binarity or rotation, but without spectroscopic confirmation. The BLOeM identifier and best-fitting photometric period, 𝑃, are mentioned in each sub￾plot’s title. The vertical axis has the same scale as in [PITH_FULL_IMAGE:figures/full_fig_p010_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: Example fitted SLF variability profiles for different stars. Left panel: example of a star that underwent prewhitening, with the original and residual periodograms shown in red and black, respectively. Middle panel: Fitted SLF variability profile that has been excluded form further analysis because 𝜈char < 0.15 d −1 . Right panel: Example of SLF variability with a poorly fitted profile and hence excluded … view at source ↗
Figure 13
Figure 13. Figure 13: Location in the HR diagram of the 51 massive stars with significant SLF variability shown as diamonds, which are colour-coded by the characteristic frequency and amplitude relative to the white noise level of their SLF variability in the left and right panels, respectively. When multiple sectors for a star are available, the values shown correspond to the most recent sector available. The grey dashed line… view at source ↗
Figure 14
Figure 14. Figure 14: Overview of SLF variability parameters as a function of 𝑇eff and luminosity. The different colours indicate the different sectors that have been used to calculate the SLF variability parameters as shown in the legend of the upper left panel. A weighted linear regression combining all sectors is also shown in black, together with a 95% confidence interval. The gradient and 𝑝-value of these regressions are … view at source ↗
Figure 15
Figure 15. Figure 15: Overview of SLF variability parameters for effective temperature 𝑇eff versus luminosity 𝐿, which were done independently for the high-mass main sequence (blue) and lower-mass post-main sequence (green) subgroups, together with a 95% confidence interval for each linear regression. These two subgroups are shown as regions in the HR diagram in [PITH_FULL_IMAGE:figures/full_fig_p015_15.png] view at source ↗
read the original abstract

Massive stars, the progenitors of neutron stars and black holes, play a crucial role in shaping the chemical and radiative properties of entire galaxies through their winds and explosive deaths. Stellar pulsations are a common phenomenon in massive stars and asteroseismology -- the study of such pulsations -- provides crucial constraints on the physics of massive star interiors. The excitation of heat-driven pulsations in massive stars is expected to depend on a star's metallicity, but this remains largely uncalibrated in evolution models due to a lack of a sufficient observations. While TESS has dramatically improved the statistics for Galactic massive stars, obtaining TESS light curves for low-metallicity massive stars beyond the Milky Way is challenging, due to their faintness and heavy crowding. In this paper, we present a novel point-spread function (PSF) based light curve extraction method called {\sc Lemons}, which overcomes these challenges. We also demonstrate the limitations of the often-used simple aperture photometry (SAP) method that can provide heavily contaminated light curves. With this new technique, accurate light curves of 91 SMC massive stars in the BLOeM sample are extracted. They reveal a variety of variability types including indications of binarity (e.g. eclipses and ellipsoidal modulation) and stellar pulsations. They also enable us to investigate stochastic low-frequency (SLF) variability for massive stars in the SMC. Furthermore we demonstrate how the morphology of SLF variability probes a star's location in the Hertzsprung--Russell diagram, which appears similar to Galactic massive stars thus indicating that the underlying physical mechanism could be insensitive to metallicity.

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 / 2 minor

Summary. The paper introduces a novel PSF-fitting tool called Lemons for extracting TESS light curves from crowded, faint fields and applies it to 91 massive stars in the SMC BLOeM sample. It contrasts Lemons results with SAP photometry to show reduced contamination, identifies variability types including binarity and pulsations, and analyzes stochastic low-frequency (SLF) variability, reporting that its morphology correlates with position in the Hertzsprung-Russell diagram similarly to Galactic massive stars and thus suggesting the underlying mechanism is insensitive to metallicity.

Significance. If the central claims hold after validation, the work would be significant for delivering the first substantial sample of space-based light curves of low-metallicity massive stars, enabling new constraints on asteroseismology and pulsation excitation models that currently lack low-Z calibration. The Lemons method itself has potential broader utility for TESS observations of extragalactic targets, and the reported similarity in SLF morphology would provide an important observational anchor for theories of stochastic variability in massive stars.

major comments (2)
  1. [§3] §3 (Lemons PSF-fitting procedure): the manuscript demonstrates cleaner signals relative to SAP but provides no quantitative validation such as injection-recovery tests for SLF signals, assessment of amplitude or frequency bias as a function of local crowding or magnitude, or direct comparison with ground-based photometry. This is load-bearing for the interpretation that the reported SLF patterns and their HRD correlation reflect intrinsic physics rather than extraction systematics.
  2. [§5] §5 (SLF variability analysis and HRD correlation): the claim that SLF morphology probes stellar location in the HR diagram in a manner similar to Galactic stars is presented without statistical quantification of the similarity (e.g., Kolmogorov-Smirnov test on morphological parameters or error bars on the reported trends), weakening the inference that the mechanism is metallicity-insensitive.
minor comments (2)
  1. The acronym BLOeM should be expanded on first use in the main text; similarly, ensure SLF is defined before its extensive use in the results.
  2. Figure captions for the light-curve comparisons and SLF morphology plots would benefit from more detail on the exact sample selection and any applied filters.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed report. We address each major comment below and describe the revisions we will implement to strengthen the manuscript.

read point-by-point responses
  1. Referee: [§3] §3 (Lemons PSF-fitting procedure): the manuscript demonstrates cleaner signals relative to SAP but provides no quantitative validation such as injection-recovery tests for SLF signals, assessment of amplitude or frequency bias as a function of local crowding or magnitude, or direct comparison with ground-based photometry. This is load-bearing for the interpretation that the reported SLF patterns and their HRD correlation reflect intrinsic physics rather than extraction systematics.

    Authors: We agree that quantitative validation would strengthen the claims regarding the intrinsic nature of the extracted signals. The current manuscript relies on direct visual and qualitative comparison with SAP photometry to demonstrate reduced contamination in crowded SMC fields. In the revised manuscript we will add an injection-recovery analysis in which synthetic SLF signals are injected into the TESS images at varying amplitudes, frequencies, crowding levels and magnitudes. Recovery statistics, amplitude and frequency biases will be quantified and discussed, together with any implications for the reported HRD trends. We will also note the absence of contemporaneous ground-based photometry for the specific targets as a limitation. revision: yes

  2. Referee: [§5] §5 (SLF variability analysis and HRD correlation): the claim that SLF morphology probes stellar location in the HR diagram in a manner similar to Galactic stars is presented without statistical quantification of the similarity (e.g., Kolmogorov-Smirnov test on morphological parameters or error bars on the reported trends), weakening the inference that the mechanism is metallicity-insensitive.

    Authors: We acknowledge that the similarity is currently presented through qualitative description of the morphological trends. In the revised manuscript we will add error bars to the reported morphological parameters and perform a quantitative statistical comparison (including a two-sample Kolmogorov-Smirnov test) between the SMC SLF parameter distributions and the corresponding Galactic distributions from the literature. These additions will provide a more rigorous basis for the conclusion that the underlying mechanism appears insensitive to metallicity. revision: yes

Circularity Check

0 steps flagged

No circularity: observational light-curve extraction and empirical SLF morphology comparison are self-contained.

full rationale

The paper introduces the Lemons PSF-fitting algorithm as a new tool, applies it to TESS data for 91 SMC stars, contrasts results with SAP photometry, and reports an empirical similarity in SLF variability morphology to Galactic stars. No derivation chain equates the reported SLF-HRD correlation or metallicity-insensitivity conclusion to an input assumption, fitted parameter, or self-citation by construction. The central claim rests on direct observational classification rather than any self-referential equation or load-bearing prior result that reduces to the present work.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 0 invented entities

The central claims rest on standard assumptions of stellar photometry and TESS data reduction rather than new free parameters or invented entities. No ad-hoc constants are introduced to force the metallicity-insensitivity conclusion.

axioms (2)
  • domain assumption Standard assumptions about the stability and shape of the TESS point-spread function across the observed fields.
    Invoked when claiming that PSF fitting removes crowding contamination more reliably than aperture photometry.
  • domain assumption The morphological classification of SLF variability can be performed consistently across metallicities using the same visual or quantitative criteria.
    Required for the claim that SLF morphology tracks HR-diagram position similarly in SMC and Milky Way samples.

pith-pipeline@v0.9.0 · 5904 in / 1599 out tokens · 34659 ms · 2026-05-19T19:37:49.697644+00:00 · methodology

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