pith. machine review for the scientific record. sign in

arxiv: 2605.14018 · v1 · submitted 2026-05-13 · 🌌 astro-ph.SR · astro-ph.GA

Recognition: no theorem link

Spectral Disentangling Reveals Deep CNO-cycle Exposure in ET Cru

Authors on Pith no claims yet

Pith reviewed 2026-05-15 02:37 UTC · model grok-4.3

classification 🌌 astro-ph.SR astro-ph.GA
keywords ET CruAlgol binaryspectral disentanglingCNO cyclestellar abundancesmass transferbinary evolutionmassive stars
0
0 comments X

The pith

Spectral disentangling in ET Cru isolates extreme carbon depletion and nitrogen enrichment in the secondary star, showing deep CNO-cycle exposure in the donor.

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

The analysis applies spectral disentangling to high-resolution spectra of the semi-detached binary ET Cru to separate the contributions of both components. This yields precise masses of 13.41 and 6.00 solar masses, radii to better than one percent, and surface abundances for nine elements. The secondary shows carbon depletion and nitrogen enrichment that greatly exceed levels in classical Algol systems, directly indicating that mass transfer has exposed layers processed by the CNO cycle. The primary appears as a rejuvenated gainer that has accreted fresh material. These measurements position ET Cru as a benchmark for testing how advanced binary interactions alter the chemical profiles and evolutionary paths of massive stars.

Core claim

Spectral disentangling of ET Cru produces independent spectra that give component masses of 13.41 solar masses and 6.00 solar masses to 1.3 percent precision, radii of 5.58 and 5.68 solar radii to 0.5 percent, and surface abundances showing the secondary's severe carbon depletion together with nitrogen enrichment far beyond values in classical Algol systems. This establishes direct spectroscopic evidence of deep CNO-cycle exposure in the donor and identifies the primary as a rejuvenated accretor, confirming ET Cru as a chemically and dynamically precise illustration of late-stage massive binary evolution.

What carries the argument

Spectral disentangling applied to composite spectra to isolate uncontaminated component spectra and derive individual effective temperatures and abundances for nine elements.

If this is right

  • ET Cru supplies a benchmark system with precisely known masses, radii, and abundances for modeling advanced mass transfer in massive binaries.
  • The primary star is confirmed as a rejuvenated gainer that accreted processed material from the donor.
  • Multi-wavelength spectral energy distribution modeling gives a distance of approximately 2.5 kpc that conflicts with the Gaia DR3 parallax.
  • The results illustrate how deep stripping in Algol-type systems exposes CNO-processed layers in the donor.

Where Pith is reading between the lines

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

  • Comparable disentangling studies of other semi-detached massive binaries could map a range of CNO exposure depths linked to mass-transfer duration and efficiency.
  • The reported Gaia parallax mismatch may reflect broader systematic uncertainties in astrometric distances for luminous interacting binaries.
  • Stellar evolution codes for massive stars should test whether deeper interior mixing during mass transfer reproduces the observed abundance extremes in donors.

Load-bearing premise

Spectral disentangling produces clean, uncontaminated spectra for each star without residuals or line-blending effects that would bias the derived chemical abundances.

What would settle it

Independent high-resolution spectroscopy of the secondary obtained during primary eclipse or analyzed with alternative disentangling codes that returns carbon and nitrogen abundances matching the reported extreme depletion and enrichment levels.

Figures

Figures reproduced from arXiv: 2605.14018 by Christian Nitschelm, Ferhat G\"uney, G\"okhan Y\"ucel, Timur \c{S}ahin, Volkan Bak{\i}\c{s}.

Figure 1
Figure 1. Figure 1: Field images of ET Cru from short to long wavelengths: DSS2 Blue (optical), TESS (red-optical), and 2MASS (near-infrared). This sequence highlights the appearance of the system across different wavelength regimes. The dimension of images is 3.85 × 3.85 arcmin2 . although nearby stars are present within the TESS aper￾ture, the times of minima can be determined with high precision, allowing the derivation of… view at source ↗
Figure 2
Figure 2. Figure 2: Linear and quadratic fits to the O − C residuals. The far left point belongs to ASAS, while the rest of the data is from the TESS Sectors. Sector mean values are shown with a red circle. The positive quadratic term suggests a possible long￾term increase in the orbital period of the system. Using the quadratic coefficient, the period change rate was derived as P˙ = (3.2 ± 2.1) × 10−10 day day−1 , or equival… view at source ↗
Figure 3
Figure 3. Figure 3: Observed RVs and photometric light curves of ET Cru, together with the best-fitting models and correspond￾ing residuals. The blue and red filled circles indicate the RV measurements of the primary and secondary components, respectively. In the LC panel, green dots show the ASAS photometric data, and the black curve represents the best-fit￾ting LC solution. configuration, which provides the best representat… view at source ↗
Figure 4
Figure 4. Figure 4: Observations and best fitting LC and spectroscopic orbital models for Gaia LCs and FEROS RV data, respectively. tude variations between different sectors and exposure times, affecting both maxima and eclipse depths. While variations at maxima may be attributed to physical ef￾fects such as stellar activity, the changes in eclipse depths are not expected to depend on sector or cadence, and instead point to t… view at source ↗
Figure 5
Figure 5. Figure 5: The corner plot of the posteriors for the fundamental parameters of the components of ET Cru from Gaia G LC. To determine the parameter space for global χ 2 mini￾mization, we used the three hydrogen Balmer lines (Hβ, Hγ, and Hδ) and Helium lines (see F. G¨uney et al. 2026) present in 4000 - 5056 ˚A spectral range of the FEROS spectrum. These were fitted against an exten￾sive library of pre-computed synthet… view at source ↗
Figure 6
Figure 6. Figure 6: Mesh plots of the binary system ET Cru at orbital phases 0.75 (left), 0.85 (middle), and 0.95 (right), generated with PHOEBE v2.4. The colour scale represents the local effective temperature across each stellar surface, while the mesh structure traces the distorted Roche-lobe-filling components. The sequence illustrates the changing aspect of the system as it approaches secondary eclipse (phase 0.75) and m… view at source ↗
Figure 7
Figure 7. Figure 7: The observed composite spectrum, ϕ = 0.819, of the semi-detached binary ET Cru (black) and its decomposition into the individual contributions of the primary (blue) and secondary (red) components in the 4000–5000 ˚A region. This disentangling, essential for isolating the spectral features of each star, provided the foundation for the subsequent determination of orbital dynamics, atmospheric parameters, and… view at source ↗
Figure 8
Figure 8. Figure 8: Determination of the microturbulent velocity (ξ) for the primary (left panel) and secondary (right panel) components of the binary system ET Cru. The standard deviation (σ) of derived abundances from a set of selected O ii lines is plotted against ξ. The adopted value for ξ (indicated by the vertical and horizontal lines) corresponds to the point of minimum σ for each component. range of trial ξ values. Th… view at source ↗
Figure 9
Figure 9. Figure 9: Comparison of photospheric elemental abundances (log ε(X)) for the primary (gainer) and secondary (donor) components of the Algol-type binary system ET Cru. The plot shows the spectroscopically derived abundances of He, C, N, O, Mg, Al, Si, S, and Fe in both stars. Error bars represent 1σ uncertainties [PITH_FULL_IMAGE:figures/full_fig_p010_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Selected line profile fits for the ET Cru primary component from FEROS spectra. Observed spectra are shown as black dots, with the best-fit synthetic spectra overlaid in red. The dashed horizontal line indicates the continuum level. The derived logarithmic abundance (logϵ) for each species is indicated in the corresponding panel [PITH_FULL_IMAGE:figures/full_fig_p010_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Same as [PITH_FULL_IMAGE:figures/full_fig_p011_11.png] view at source ↗
Figure 12
Figure 12. Figure 12: SED of ET Cru constructed from multi-wavelength photometric data. Black circles represent the observed fluxes, and red crosses indicate data points excluded by the 3σ clipping procedure. The solid red curve shows the total reddened model SED, while the dashed green curve corresponds to the intrinsic (unreddened) SED. The dashed blue and orange curves illustrate the individual flux contributions of the pri… view at source ↗
read the original abstract

Binary stars undergoing mass transfer provide unique laboratories for testing stellar evolution. Here, we present a comprehensive photometric and spectroscopic analysis of the semi-detached system ET Cru. Using spectral disentangling, we independently determined the effective temperatures and chemical abundances of both components with high precision, including nine elements (eleven species). We find masses of $13.41\,M_\odot$ and $6.00\,M_\odot$ for the primary and secondary, respectively, with uncertainties of only $\sim$1.3%. The radii are $5.58\,R_\odot$ and $5.68\,R_\odot$, measured to within 0.4% and 0.5%. Surface gravities are constrained to better than 1%, while effective temperatures are determined to within 3-5%. The secondary exhibits extreme chemical anomalies, with severe carbon depletion and nitrogen enrichment far exceeding those reported in classical Algol systems. Multi-wavelength spectral energy distribution modelling yields a distance of $\sim$2.5 kpc, inconsistent with the $Gaia$ DR3 parallax, suggesting systematic astrometric uncertainties in the parallax distance. Together, these results establish ET Cru as a benchmark Algol-type binary, revealing direct spectroscopic evidence of deep CNO-cycle exposure in the donor and confirming the primary star as a rejuvenated gainer. ET Cru thus provides a chemically and dynamically illustrative case for understanding advanced binary interactions and the late evolutionary stages of massive-star evolution.

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 a photometric and spectroscopic study of the semi-detached Algol binary ET Cru. Through spectral disentangling, it derives high-precision masses (13.41 and 6.00 M⊙ with ~1.3% uncertainty), radii (5.58 and 5.68 R⊙ with 0.4-0.5% uncertainty), surface gravities to better than 1%, and effective temperatures to 3-5%. Abundances for nine elements (eleven species) are reported, with the secondary showing severe carbon depletion and nitrogen enrichment far exceeding classical Algols. SED modeling yields a distance of ~2.5 kpc, inconsistent with Gaia DR3 parallax. The authors position ET Cru as a benchmark system providing direct evidence of deep CNO-cycle exposure in the donor and rejuvenation of the gainer.

Significance. If the disentangling and abundance results hold, this would provide valuable direct spectroscopic confirmation of CNO-processed material in the envelope of a massive binary donor, offering a rare test case for mass-transfer and mixing models in interacting systems. The claimed precisions on dynamical parameters could make ET Cru a reference object for calibrating binary evolution tracks, while the Gaia discrepancy highlights potential astrometric issues in close binaries.

major comments (3)
  1. [Spectral Disentangling and Abundance Analysis] The central claim of extreme C depletion and N enrichment in the secondary (far beyond classical Algols) rests on the fidelity of spectral disentangling. No residuals, cross-contamination tests, or line-blending assessments for key C/N features are referenced, leaving open the possibility that systematics inflate the reported anomalies.
  2. [Uncertainties and Error Budget] Masses, radii, gravities, and temperatures are quoted with very small uncertainties (~1.3%, 0.4-0.5%, <1%, 3-5%), but the abstract provides no error budget, covariance analysis, or validation of disentangling residuals. This undermines assessment of whether the central abundance claims are robust against unquantified systematics.
  3. [Distance and Gaia Comparison] The SED distance of ~2.5 kpc is stated to be inconsistent with Gaia DR3 parallax, implying systematic astrometric uncertainties, but no specific parallax value, uncertainty, or discussion of causes (e.g., orbital motion) is given, weakening the interpretation.
minor comments (2)
  1. [Abstract] Clarify the distinction between 'nine elements (eleven species)' by specifying the ionization states included in the abundance analysis.
  2. [Notation and Presentation] Adopt consistent abundance notation (e.g., [X/H] or log ε(X)) and define it explicitly on first use.

Simulated Author's Rebuttal

3 responses · 0 unresolved

We thank the referee for the detailed and constructive review of our manuscript on ET Cru. We address each major comment below and have revised the paper accordingly to improve clarity and robustness.

read point-by-point responses
  1. Referee: [Spectral Disentangling and Abundance Analysis] The central claim of extreme C depletion and N enrichment in the secondary (far beyond classical Algols) rests on the fidelity of spectral disentangling. No residuals, cross-contamination tests, or line-blending assessments for key C/N features are referenced, leaving open the possibility that systematics inflate the reported anomalies.

    Authors: We agree that explicit validation strengthens the abundance results. The manuscript already shows the disentangled spectra overlaid on the observations, but we will add a dedicated figure with residuals for the key C and N lines, plus cross-contamination tests via synthetic spectrum injection and line-blending assessments. These additions will confirm that the reported CNO anomalies are not inflated by systematics. revision: yes

  2. Referee: [Uncertainties and Error Budget] Masses, radii, gravities, and temperatures are quoted with very small uncertainties (~1.3%, 0.4-0.5%, <1%, 3-5%), but the abstract provides no error budget, covariance analysis, or validation of disentangling residuals. This undermines assessment of whether the central abundance claims are robust against unquantified systematics.

    Authors: The quoted uncertainties derive from the joint photometric-spectroscopic covariance matrix and the disentangling solution. We acknowledge the abstract omits an explicit error budget. In revision we will add a concise error-budget statement to the abstract and expand the methods section with covariance details plus residual validation to demonstrate robustness against systematics. revision: yes

  3. Referee: [Distance and Gaia Comparison] The SED distance of ~2.5 kpc is stated to be inconsistent with Gaia DR3 parallax, implying systematic astrometric uncertainties, but no specific parallax value, uncertainty, or discussion of causes (e.g., orbital motion) is given, weakening the interpretation.

    Authors: We agree that the specific Gaia DR3 parallax value, uncertainty, and possible causes should be stated explicitly. We will insert the exact Gaia DR3 parallax and its uncertainty, together with a short discussion of how orbital motion in close binaries can bias astrometric solutions, thereby supporting the interpretation of the distance discrepancy. revision: yes

Circularity Check

0 steps flagged

No significant circularity in derivation chain

full rationale

The paper reports direct measurements of masses, radii, temperatures, and abundances for ET Cru via standard photometric light-curve fitting, radial-velocity orbits, and spectral disentangling applied to observed spectra. The chemical anomalies (C depletion, N enrichment) are obtained by fitting model atmospheres to the disentangled component spectra; these steps do not reduce by construction to previously fitted parameters or to a self-citation chain. No equations or claims in the abstract or described workflow equate a derived quantity to its own input via redefinition, renaming, or ansatz smuggling. The analysis is therefore self-contained against external benchmarks and receives the default non-circularity finding.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The central claim rests on the validity of spectral disentangling applied to this system and standard assumptions about binary orbital geometry and stellar atmospheres; no new entities are postulated.

axioms (1)
  • domain assumption The binary is semi-detached with the secondary filling its Roche lobe
    Stated in the abstract as the system classification used to interpret the mass transfer.

pith-pipeline@v0.9.0 · 5595 in / 1152 out tokens · 28704 ms · 2026-05-15T02:37:24.826739+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

74 extracted references · 74 canonical work pages · 6 internal anchors

  1. [1]

    1991, A&A Rv, 3, 91, doi: 10.1007/BF00873538

    Andersen, J. 1991, A&A Rv, 3, 91, doi: 10.1007/BF00873538

  2. [2]

    2024, A&A, 691, A361, doi: 10.1051/0004-6361/202451878

    Aschenbrenner, P., & Przybilla, N. 2024, A&A, 691, A361, doi: 10.1051/0004-6361/202451878

  3. [3]

    1999, XSPEC: An X-ray spectral fitting package,, Astrophysics Source Code Library, record ascl:9910.005 http://ascl.net/9910.005 Astropy Collaboration, Robitaille, T

    Asplund, M., Grevesse, N., Sauval, A. J., & Scott, P. 2009, Annual review of astronomy and astrophysics, 47, 481 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Price-Whelan, A. M., Sip˝ ocz, B. M., et al. 2018, AJ, 156, 123, doi: 10.3847/1538-3881/aabc4f Astrop...

  4. [4]

    H., & Mihalas, D

    Auer, L. H., & Mihalas, D. 1973, Astrophysical Journal Supplement, vol. 25, p. 433 (1973), 25, 433

  5. [5]

    Bailer-Jones, C. A. L., Rybizki, J., Fouesneau, M., Mantelet, G., & Andrae, R. 2018, AJ, 156, 58, doi: 10.3847/1538-3881/aacb21 Bakı¸ s, H., Hilal Yıldız,¨O., Bakı¸ s, V., & Y¨ ucel, G. 2025, PASA, 42, e114, doi: 10.1017/pasa.2025.10057 Bakı¸ s, V., & Eker, Z. 2022, AcA, 72, 195, doi: 10.32023/0001-5237/72.3.4 Bakıs,, H., Bakıs,, V., Eker, Z., & Demircan,...

  6. [6]

    1974, Journal of Quantitative Spectroscopy and Radiative Transfer, 14, 1025

    Barnard, A., Cooper, J., & Smith, E. 1974, Journal of Quantitative Spectroscopy and Radiative Transfer, 14, 1025

  7. [7]

    2019, MNRAS, 486, 2075, doi: 10.1093/mnras/stz549

    Blanco-Cuaresma, S. 2019, MNRAS, 486, 2075, doi: 10.1093/mnras/stz549

  8. [8]

    2014, A&A, 569, A111, doi: 10.1051/0004-6361/201423945

    Blanco-Cuaresma, S., Soubiran, C., Heiter, U., & Jofr´ e, P. 2014, A&A, 569, A111, doi: 10.1051/0004-6361/201423945

  9. [9]

    Castelli, F., & Kurucz, R. L. 2003, in IAU Symposium, Vol. 210, Modelling of Stellar Atmospheres, ed. N. Piskunov, W. W. Weiss, & D. F. Gray, A20, doi: 10.48550/arXiv.astro-ph/0405087

  10. [10]

    E., Kochoska, A., Hey, D., et al

    Conroy, K. E., Kochoska, A., Hey, D., et al. 2020, ApJS, 250, 34, doi: 10.3847/1538-4365/abb4e2

  11. [11]

    Crawford, J. A. 1955, ApJ, 121, 71, doi: 10.1086/145965

  12. [12]

    1989, A&A, 214, 168

    Cugier, H. 1989, A&A, 214, 168

  13. [13]

    1988, A&A, 202, 101 Dervi¸ soˇ glu, A., Pavlovski, K., Lehmann, H., Southworth, J., & Bewsher, D

    Cugier, H., & Hardorp, J. 1988, A&A, 202, 101 Dervi¸ soˇ glu, A., Pavlovski, K., Lehmann, H., Southworth, J., & Bewsher, D. 2018, MNRAS, 481, 5660, doi: 10.1093/mnras/sty2684

  14. [14]

    1984, Journal of Quantitative Spectroscopy and Radiative Transfer, 31, 301

    Dimitrijevic, M., & Sahal-Br´ echot, S. 1984, Journal of Quantitative Spectroscopy and Radiative Transfer, 31, 301

  15. [15]

    2023, MNRAS, 523, 2440, doi: 10.1093/mnras/stad1563

    Eker, Z., & Bakı¸ s, V. 2023, MNRAS, 523, 2440, doi: 10.1093/mnras/stad1563

  16. [16]

    2025, Physics and Astronomy Reports, 3, 43, doi: 10.26650/PAR.2025.00005

    Eker, Z., & Bakı¸ s, V. 2025, Physics and Astronomy Reports, 3, 43, doi: 10.26650/PAR.2025.00005

  17. [17]

    2024, Physics and Astronomy Reports, 2, 41, doi: 10.26650/PAR.2024.00001

    Eker, Z., Soydugan, F., & Bilir, S. 2024, Physics and Astronomy Reports, 2, 41, doi: 10.26650/PAR.2024.00001

  18. [18]
  19. [19]

    2015, AJ, 149, 131, doi: 10.1088/0004-6256/149/4/131

    Eker, Z., Soydugan, F., Soydugan, E., et al. 2015, AJ, 149, 131, doi: 10.1088/0004-6256/149/4/131

  20. [20]

    2018, MNRAS, 479, 5491, doi: 10.1093/mnras/sty1834

    Eker, Z., Bakı¸ s, V., Bilir, S., et al. 2018, MNRAS, 479, 5491, doi: 10.1093/mnras/sty1834

  21. [21]

    2020, MNRAS, 496, 3887, doi: 10.1093/mnras/staa1659

    Eker, Z., Soydugan, F., Bilir, S., et al. 2020, MNRAS, 496, 3887, doi: 10.1093/mnras/staa1659

  22. [22]

    J., Stanway, E

    Eldridge, J. J., Stanway, E. R., Xiao, L., et al. 2017, PASA, 34, e058, doi: 10.1017/pasa.2017.51

  23. [23]

    2016, The Journal of Open Source Software, 1, 24, doi: 10.21105/joss.00024

    Foreman-Mackey, D. 2016, The Journal of Open Source Software, 1, 24, doi: 10.21105/joss.00024

  24. [24]

    and Lang, Dustin and Goodman, Jonathan , title =

    Foreman-Mackey, D., Hogg, D. W., Lang, D., & Goodman, J. 2013, PASP, 125, 306, doi: 10.1086/670067

  25. [25]

    2012, Ap&SS, 341, 405, doi: 10.1007/s10509-012-1125-3 Gaia Collaboration, Vallenari, A., Brown, A

    Gafeira, R., Patacas, C., & Fernandes, J. 2012, Ap&SS, 341, 405, doi: 10.1007/s10509-012-1125-3 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al. 2023, A&A, 674, A1, doi: 10.1051/0004-6361/202243940 G¨ uney, F., S ¸ahin, T., & Dervi¸ so˘ glu, A. 2026, Physica Scripta, 101, 045004, doi: 10.1088/1402-4896/ae364e

  26. [26]

    1995, A&AS, 114, 393

    Hadrava, P. 1995, A&AS, 114, 393

  27. [27]

    R., Millman, K

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

  28. [28]

    2000, A&A, 358, 553

    Hensberge, H., Pavlovski, K., & Verschueren, W. 2000, A&A, 358, 553

  29. [29]

    Hilditch, R. W. 2001, An Introduction to Close Binary Stars (Cambridge University Press) Høg, E., Fabricius, C., Makarov, V. V., et al. 2000, A&A, 355, L27

  30. [30]

    E., Pablo, H., et al

    Horvat, M., Conroy, K. E., Pablo, H., et al. 2018, ApJS, 237, 26, doi: 10.3847/1538-4365/aacd0f

  31. [31]

    Houk, N., & Cowley, A. P. 1975, University of Michigan Catalogue of two-dimensional spectral types for the HD stars. Volume I. Declinations -90 to -53 ƒ0. (University of Michigan)

  32. [32]

    X., Vanderburg, A., P´ al, A., et al

    Huang, C. X., Vanderburg, A., P´ al, A., et al. 2020a, Research Notes of the American Astronomical Society, 4, 204, doi: 10.3847/2515-5172/abca2e

  33. [33]

    X., Vanderburg, A., P´ al, A., et al

    Huang, C. X., Vanderburg, A., P´ al, A., et al. 2020b, Research Notes of the American Astronomical Society, 4, 206, doi: 10.3847/2515-5172/abca2d

  34. [34]

    2020, TESS Lightcurves From The MIT Quick-Look Pipeline (”QLP”), STScI/MAST, doi: https://dx.doi.org/10.17909/t9-r086-e880 21

    Huang, Chelsea X. 2020, TESS Lightcurves From The MIT Quick-Look Pipeline (”QLP”), STScI/MAST, doi: https://dx.doi.org/10.17909/t9-r086-e880 21

  35. [35]

    1994, Astronomy and Astrophysics (ISSN 0004-6361), vol

    Hubeny, I., Hummer, D., & Lanz, T. 1994, Astronomy and Astrophysics (ISSN 0004-6361), vol. 282, no. 1, p. 151-167, 282, 151

  36. [36]

    1995, ApJ, 439, 875, doi: 10.1086/175226

    Hubeny, I., & Lanz, T. 1995, ApJ, 439, 875, doi: 10.1086/175226

  37. [37]

    A brief introductory guide to TLUSTY and SYNSPEC

    Hubeny, I., & Lanz, T. 2017, arXiv e-prints, arXiv:1706.01859, doi: 10.48550/arXiv.1706.01859

  38. [38]

    Hunter, J. D. 2007, Computing in Science and Engineering, 9, 90, doi: 10.1109/MCSE.2007.55 Ibanoˇ glu, C., Dervi¸ soˇ glu, A.,´Cakırlı, ¨O., Sipahi, E., & Y¨ uce, K. 2012, MNRAS, 419, 1472, doi: 10.1111/j.1365-2966.2011.19812.x

  39. [39]

    W., Tkachenko, A., Johnston, C., et al

    IJspeert, L. W., Tkachenko, A., Johnston, C., et al. 2021, A&A, 652, A120, doi: 10.1051/0004-6361/202141489

  40. [40]

    2001, in

    Ilijic, S., Hensberge, H., & Pavlovski, K. 2001, in

  41. [41]

    L., & Morgan, W

    Johnson, H. L., & Morgan, W. W. 1953, ApJ, 117, 313, doi: 10.1086/145697

  42. [42]

    E., Horvat, M., et al

    Jones, D., Conroy, K. E., Horvat, M., et al. 2020, ApJS, 247, 63, doi: 10.3847/1538-4365/ab7927

  43. [43]

    1999, The Messenger, 95, 8

    Kaufer, A., Stahl, O., Tubbesing, S., et al. 1999, The Messenger, 95, 8

  44. [44]

    2014, MNRAS, 444, 3118, doi: 10.1093/mnras/stu1652

    Kolbas, V., Dervi¸ so˘ glu, A., Pavlovski, K., & Southworth, J. 2014, MNRAS, 444, 3118, doi: 10.1093/mnras/stu1652

  45. [45]

    2015, MNRAS, 451, 4150, doi: 10.1093/mnras/stv1261

    Kolbas, V., Pavlovski, K., Southworth, J., et al. 2015, MNRAS, 451, 4150, doi: 10.1093/mnras/stv1261

  46. [46]

    2024, MNRAS, 535, 2651, doi: 10.1093/mnras/stae2494

    Kovalev, M., Li, Z., Xiong, J., et al. 2024, MNRAS, 535, 2651, doi: 10.1093/mnras/stae2494

  47. [47]

    2022, Research Notes of the American Astronomical Society, 6, 236, doi: 10.3847/2515-5172/aca158

    Kunimoto, M., Tey, E., Fong, W., et al. 2022, Research Notes of the American Astronomical Society, 6, 236, doi: 10.3847/2515-5172/aca158

  48. [48]

    2021, Research Notes of the American Astronomical Society, 5, 234, doi: 10.3847/2515-5172/ac2ef0

    Kunimoto, M., Huang, C., Tey, E., et al. 2021, Research Notes of the American Astronomical Society, 5, 234, doi: 10.3847/2515-5172/ac2ef0

  49. [49]

    2007, The Astrophysical Journal Supplement Series, 169, 83 Lightkurve Collaboration, Cardoso, J

    Lanz, T., & Hubeny, I. 2007, The Astrophysical Journal Supplement Series, 169, 83 Lightkurve Collaboration, Cardoso, J. V. d. M., Hedges, C., et al. 2018, Lightkurve: Kepler and TESS time series analysis in Python,, Astrophysics Source Code Library http://ascl.net/1812.013

  50. [50]

    Malkov, O. Y. 2003, A&A, 402, 1055, doi: 10.1051/0004-6361:20030313

  51. [51]

    Malkov, O. Y. 2007, MNRAS, 382, 1073, doi: 10.1111/j.1365-2966.2007.12086.x

  52. [52]

    Malkov, O. Y. 2020, MNRAS, 491, 5489, doi: 10.1093/mnras/stz3363

  53. [53]

    2012, Astronomy & Astrophysics, 539, A143

    Nieva, M.-F., & Przybilla, N. 2012, Astronomy & Astrophysics, 539, A143

  54. [54]

    A., & Claus, F

    Otero, S. A., & Claus, F. 2004, Information Bulletin on Variable Stars, 5495, 1

  55. [55]

    1983, Monthly Notices of the Royal Astronomical Society, 203, 1063

    Parthasarathy, M., Lambert, D., & Tomkin, J. 1983, Monthly Notices of the Royal Astronomical Society, 203, 1063

  56. [56]

    L., & Tomkin, J

    Parthasarathy, M., Lambert, D. L., & Tomkin, J. 1983, MNRAS, 203, 1063, doi: 10.1093/mnras/203.4.1063

  57. [57]

    2005, A&A, 439, 309, doi: 10.1051/0004-6361:20052804

    Pavlovski, K., & Hensberge, H. 2005, A&A, 439, 309, doi: 10.1051/0004-6361:20052804

  58. [58]

    2023, A&A, 671, A139, doi: 10.1051/0004-6361/202244980

    Pavlovski, K., Southworth, J., Tkachenko, A., Van Reeth, T., & Tamajo, E. 2023, A&A, 671, A139, doi: 10.1051/0004-6361/202244980

  59. [59]

    The All Sky Automated Survey

    Pojmanski, G. 1997, AcA, 47, 467, doi: 10.48550/arXiv.astro-ph/9712146 Prˇ sa, A., Conroy, K. E., Horvat, M., et al. 2016, ApJS, 227, 29, doi: 10.3847/1538-4365/227/2/29

  60. [60]

    B., & Twigg, L

    Rafert, J. B., & Twigg, L. W. 1980, MNRAS, 193, 79, doi: 10.1093/mnras/193.1.79

  61. [61]

    R., Winn, J

    Ricker, G. R., Winn, J. N., Vanderspek, R., et al. 2015, Journal of Astronomical Telescopes, Instruments, and Systems, 1, 014003, doi: 10.1117/1.JATIS.1.1.014003 S ¸ahin, T., & Dervi¸ so˘ glu, A. 2019, Astronomy Letters, 45, 528

  62. [62]

    2021, A&A Rv, 29, 4, doi: 10.1007/s00159-021-00132-9

    Serenelli, A., Weiss, A., Aerts, C., et al. 2021, A&A Rv, 29, 4, doi: 10.1007/s00159-021-00132-9

  63. [63]

    Shamey, L. J. 1969, Ph. D. Thesis

  64. [64]

    P., & Sturm, E

    Simon, K. P., & Sturm, E. 1994, A&A, 281, 286

  65. [65]

    2025, A&A, 698, A48, doi: 10.1051/0004-6361/202452341

    Skarka, M., Lipt´ ak, J., Niemczura, E., et al. 2025, A&A, 698, A48, doi: 10.1051/0004-6361/202452341

  66. [66]

    2021, Universe, 7, 369, doi: 10.3390/universe7100369

    Southworth, J. 2021, Universe, 7, 369, doi: 10.3390/universe7100369

  67. [67]

    1965, Information Bulletin on Variable Stars, 115, 1

    Strohmeier, W., Knigge, R., & Ott, H. 1965, Information Bulletin on Variable Stars, 115, 1

  68. [68]

    2008, A&A, 483, 263, doi: 10.1051/0004-6361:20079305

    Tomasella, L., Munari, U., Cassisi, S., et al. 2008, A&A, 483, 263, doi: 10.1051/0004-6361:20079305

  69. [69]

    L., & Lemke, M

    Tomkin, J., Lambert, D. L., & Lemke, M. 1993, Monthly Notices of the Royal Astronomical Society, 265, 581, doi: 10.1093/mnras/265.3.581

  70. [70]

    2010, A&A Rv, 18, 67, doi: 10.1007/s00159-009-0025-1

    Torres, G., Andersen, J., & Gim´ enez, A. 2010, A&A Rv, 18, 67, doi: 10.1007/s00159-009-0025-1

  71. [71]

    M., Navarro, S

    Tovmassian, H. M., Navarro, S. G., & Cardona, O. 1996, AJ, 111, 306, doi: 10.1086/117782

  72. [72]

    1973, Astrophysical Journal Supplement, vol

    Vidal, C., Cooper, J., & Smith, E. 1973, Astrophysical Journal Supplement, vol. 25, p. 37 (1973), 25, 37

  73. [73]

    E., et al

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

  74. [74]

    1996, Astronomy and Astrophysics, v

    Vrancken, M., Butler, K., & Becker, S. 1996, Astronomy and Astrophysics, v. 311, p. 661-668, 311, 661 Y¨ ucel, G., Alan, N., Banks, T., et al. 2026a, ApJ, 997, 8, doi: 10.3847/1538-4357/ae2a25 22 Y¨ ucel, G., & Bakı¸ s, V. 2022, MNRAS, 516, 2486, doi: 10.1093/mnras/stac2293 Y¨ ucel, G., Bakı¸ s, V., Canbay, R., et al. 2025, AJ, 169, 71, doi: 10.3847/1538-...