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arxiv: 2606.11293 · v1 · pith:BFGW5AYVnew · submitted 2026-06-09 · 🌌 astro-ph.SR

A systematic survey for hypervelocity runaways from thermonuclear supernovae

Pith reviewed 2026-06-27 11:29 UTC · model grok-4.3

classification 🌌 astro-ph.SR
keywords hypervelocity starsD6 starsthermonuclear supernovaewhite dwarf binariesrunaway starsGaia surveySN Ia progenitors
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The pith

A systematic Gaia survey of hypervelocity stars finds intermediate-heating models best match the observed D6 population and imply low birth rates.

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

The paper conducts a magnitude-limited search for hypervelocity runaways from thermonuclear supernovae using Gaia tangential velocities and blue colors, then classifies every candidate with spectroscopy or archival data. Ten objects are identified as D6 stars whose properties span a wide range of temperatures and ages. Forward-modeling the survey under different post-explosion heating prescriptions shows that pure shock-heating tracks are too faint and brief while fully reheated tracks are too bright and long-lived. Only models with intermediate heating reproduce the magnitude, distance, and kinematic-age distributions of the detected stars. The matching models require D6 birth rates of only a few percent of the Galactic SN Ia rate.

Core claim

No single D6 evolutionary model reproduces the observed diversity; shock-heating-only models underpredict the sample while fully reheated models overpredict it, but intermediate-heating models that occur in some violent-merger and partial-disruption simulations match the magnitude, distance, and kinematic-age distributions. The inferred D6 birth rate under these best-matching models is only a few percent of the Galactic SN Ia rate, suggesting that most type Ia events arise from white-dwarf binaries in which both components explode.

What carries the argument

Forward-modeling that couples proposed D6 evolutionary tracks (shock heating only, full reheating, intermediate cases) to a Galactic density-velocity model and the survey's explicit selection function.

If this is right

  • Shock-heating-only models are too faint and short-lived to account for most of the observed D6 stars.
  • Fully reheated models are too luminous and long-lived to match the sample.
  • Intermediate-heating models reproduce the magnitude, distance, and kinematic-age distributions.
  • The D6 birth rate required by the best-matching models is only a few percent of the Galactic SN Ia rate.

Where Pith is reading between the lines

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

  • The low inferred rate would require that the majority of SN Ia events leave no surviving companion.
  • The observed temperature spread among D6 stars suggests that real events sample a range of remnant masses and heating efficiencies.
  • Larger spectroscopic surveys could test whether the velocity and spatial distributions continue to favor the intermediate-heating channel.

Load-bearing premise

The adopted D6 evolutionary models correctly predict the post-explosion thermal evolution, cooling tracks, and detectable lifetimes of the runaways.

What would settle it

A measured D6 birth rate substantially higher than a few percent of the SN Ia rate, or the discovery of a large additional population whose luminosities and ages match only the shock-only or fully-reheated tracks.

Figures

Figures reproduced from arXiv: 2606.11293 by Aakash Bhat, Antonio C. Rodriguez, Boris T. G\"ansicke, Hila Glanz, Ilaria Caiazzo, Jan van Roestel, Jay Strader, Jiwon Jesse Han, Kareem El-Badry, Ken J. Shen, Klaus Werner, Laura Chomiuk, Lisa Blomberg, Mark A. Hollands, Natsuko Yamaguchi, Pranav Nagarajan, Tin Long Sunny Wong, Vedant Chandra, Zachary P. Vanderbosch.

Figure 1
Figure 1. Figure 1: — Basic properties of the 92 candidates returned by our Gaia search. Gray points show false positives, while colored points show different classes of spectroscopically confirmed runaways: hot D6 stars (cyan), cool D6 stars (red), and LP 40-365 stars (green). Panels show sky positions, the Gaia color–apparent magnitude diagram, radial velocity as a function of the 1σ tangential-velocity lower limit v⊥,lower… view at source ↗
Figure 2
Figure 2. Figure 2: — Comparison of the X-shooter spectra of J1251-5059, a new D6 star discovered by our search (black) and D6-1, a brighter and nearer source discovered by Shen et al. (2018b). The spectrum of D6-1 is multiplied by 0.1 so that the flux scales of the two sources are consistent. Overall, the two stars have extremely similar spectra after this rescaling, indicating that they have similar temperatures and surface… view at source ↗
Figure 3
Figure 3. Figure 3: — GMOS spectrum and RV constraints for J0812-5943, a new hot D6 star discovered by our search. Left: coadded, normalized GMOS spectrum (black) compared to a normalized Kurucz model with Teff = 49,000 K, log g = 7.40, and a C/O-dominated composition (red). Right: χ 2 − χ 2 min as a function of radial velocity. Gray curves show the individual exposures, while the black curve shows their sum. The best-fit rad… view at source ↗
Figure 4
Figure 4. Figure 4: — Normalized spectrum of J1949+0745 compared to a He-dominated NLTE atmosphere model calculated with TMAP. The model has Teff = 65,000 K, log g = 8.5, and abundances He = 0.58, C = 0.25, and O = 0.17 (mass fractions). It reproduces most of the strongest lines, supporting classification of J1949+0745 as a hot D6 star, but the model does not fully match all features in the spectrum. In particular, the C IV l… view at source ↗
Figure 5
Figure 5. Figure 5: — Summary of the known population of hypervelocity WDs and related objects. In each panel, we show suspected hot and cool D6 stars in cyan and red, LP 40-365 stars in green, and the runaway sdB US 708 in magenta. The three new discoveries presented in this work are shown with a black outline. Top left: color-magnitude diagram, with the Gaia 100 pc sample shown for context. Top right: HR diagram. Bottom lef… view at source ↗
Figure 6
Figure 6. Figure 6: — Comparison of observed D6 stars recovered by our search (red and cyan) with simulated populations (black) for shocked-donor models from Wong & Bildsten (2025). Each column shows a different model, labeled by the mass of the runaway star. In this and the following population-comparison figures, the simulated points show a random subset of 10 detectable sources after scaling the model birth rate to produce… view at source ↗
Figure 7
Figure 7. Figure 7: — Same as [PITH_FULL_IMAGE:figures/full_fig_p017_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: — Same as [PITH_FULL_IMAGE:figures/full_fig_p018_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: — Same as [PITH_FULL_IMAGE:figures/full_fig_p019_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: — Same as [PITH_FULL_IMAGE:figures/full_fig_p020_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: — Comparison of the observed and underlying D6 star population. Gray points show all simulated runaways launched in the last 10 Myr under the Glanz et al. (2025) evolutionary model, while red points show the subset detectable to our search. The panels show sky position, apparent magnitude as a function of distance and observed color, and height above the Galactic plane as a function of midplane-crossing t… view at source ↗
read the original abstract

The explosion of a white dwarf (WD) in a close binary can launch a surviving runaway star at velocities of $\gtrsim 1000\, \rm km\,s^{-1}$. Such runaways provide a direct probe of thermonuclear supernovae (SNe) in double-degenerate binaries. Several candidate runaways are known, but their evolutionary states and the demographics of the broader population are uncertain. To enable robust population inference, we carry out a systematic survey for hypervelocity runaways with a simple selection function, selecting candidates based on large Gaia-inferred tangential velocities and blue colors. We classify 100% of the resulting 92 candidates using a combination of spectroscopic follow-up and archival data. The search yields ten suspected D$^6$ stars and three LP 40-365 stars. Three D$^6$ stars are new discoveries, including two hot ($T_{\rm eff} > 50,000$ K) objects and one cool ($T_{\rm eff}\approx 7,000$ K) object. We forward-model our survey under several proposed D$^6$ star evolutionary models, coupling each to a Galactic model and the survey selection function. No single model reproduces the observed diversity of D$^6$ stars, which likely reflects a range of remnant masses, ages, and heating mechanisms. Models in which runaway companions are heated by SN shocks alone are too faint and short-lived to explain most of the observed sample, while fully reheated models are too luminous and long-lived. Models with intermediate heating, as occurs in some simulations of violent mergers and partially disrupted remnants, best match the observed magnitude, distance, and kinematic-age distributions. The inferred D$^6$ star birth rate is model dependent, but the models that best match the observed population require rates of only a few percent of the Galactic SN Ia rate, perhaps implying that most SNe Ia result from WD binaries in which both components explode.

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 conducts a systematic Gaia-based survey for hypervelocity runaway stars from thermonuclear supernovae using a simple selection on large tangential velocities and blue colors. It classifies all 92 candidates via spectroscopy and archival data, identifying 10 suspected D6 stars (including three new) and three LP 40-365 stars. Forward modeling of the survey under different D6 evolutionary models (shock heating only, full reheating, intermediate) coupled to a Galactic model and selection function shows that intermediate-heating models best match the observed magnitude, distance, and kinematic-age distributions, while implying a D6 birth rate of only a few percent of the Galactic SN Ia rate.

Significance. If the forward-modeling results hold, the work supplies direct demographic constraints on the double-degenerate SN Ia channel by showing that surviving runaways are rare, consistent with most events involving both white dwarfs exploding. The complete classification of a well-defined sample and the identification of new hot and cool D6 candidates strengthen the observational foundation for testing evolutionary scenarios.

major comments (2)
  1. [forward-modeling analysis] The forward-modeling comparison (detailed after the candidate classification) assumes that the adopted D6 cooling tracks and heating prescriptions for the three model families correctly predict luminosities, effective temperatures, and lifetimes as functions of remnant mass and age. No independent validation of the intermediate-heating case against detailed stellar-evolution calculations is described, yet this family is identified as best-matching; any systematic offset in cooling timescales would alter both the model preference and the inferred birth-rate ratio.
  2. [results and discussion of birth rates] The birth-rate inference that best-matching models require rates of only a few percent of the SN Ia rate is presented as model-dependent, but the text does not quantify the sensitivity of the predicted detectable counts to the specific choices of Galactic density/velocity distributions or the exact form of the survey selection function; these enter the comparison directly and could shift the rate ratio if biased.
minor comments (2)
  1. [abstract] The abstract states that 'no single model reproduces the observed diversity' but does not list the specific goodness-of-fit metric or number of free parameters used to rank the three heating families.
  2. [candidate table] Table or figure presenting the 10 D6 candidates should include the adopted kinematic ages and distances for direct comparison to the model predictions.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their thorough review and constructive comments. We address each major comment below.

read point-by-point responses
  1. Referee: [forward-modeling analysis] The forward-modeling comparison (detailed after the candidate classification) assumes that the adopted D6 cooling tracks and heating prescriptions for the three model families correctly predict luminosities, effective temperatures, and lifetimes as functions of remnant mass and age. No independent validation of the intermediate-heating case against detailed stellar-evolution calculations is described, yet this family is identified as best-matching; any systematic offset in cooling timescales would alter both the model preference and the inferred birth-rate ratio.

    Authors: The three model families are taken directly from published hydrodynamical simulations and stellar-evolution calculations in the literature; our analysis compares the observed sample against these existing prescriptions rather than deriving new tracks. We agree that the lack of an independent validation of the intermediate-heating case within this work is a limitation, and any systematic offset in cooling timescales would affect both the model ranking and the birth-rate ratio. We will revise the discussion to explicitly note this reliance on literature models and to discuss how plausible offsets in cooling timescales could alter the conclusions. revision: partial

  2. Referee: [results and discussion of birth rates] The birth-rate inference that best-matching models require rates of only a few percent of the SN Ia rate is presented as model-dependent, but the text does not quantify the sensitivity of the predicted detectable counts to the specific choices of Galactic density/velocity distributions or the exact form of the survey selection function; these enter the comparison directly and could shift the rate ratio if biased.

    Authors: The Galactic model and selection function are fully specified in the methods section using standard parameters from the literature. While the manuscript states that the birth-rate result is model-dependent, we have not performed a quantitative sensitivity study varying the Galactic density/velocity distributions or the precise selection cuts. We will add a short discussion (or appendix) that explores the effect of reasonable variations in these inputs on the predicted detectable counts, thereby quantifying the robustness of the inferred rate ratio. revision: yes

Circularity Check

0 steps flagged

No circularity: observational survey and external model comparison are independent

full rationale

The paper conducts a Gaia-based candidate selection and spectroscopic classification that is independent of the D6 evolutionary models. It then forward-models the survey using several proposed external models (shock-heating only, full reheating, intermediate) coupled to a Galactic density/velocity model and selection function. Model preference is determined by match to observed magnitude, distance, and kinematic-age distributions; the birth rate is scaled to match counts but remains explicitly model-dependent without reducing to a tautology or self-fit by the paper's equations. No self-definitional, fitted-input-called-prediction, or load-bearing self-citation steps are present. The derivation chain is self-contained against external benchmarks.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claim rests on standard assumptions about white-dwarf binary evolution and Galactic structure plus the specific D6 heating prescriptions; the main adjustable element is the level of post-explosion reheating.

free parameters (1)
  • reheating efficiency
    The amount of energy deposited into the companion by the supernova is varied across models to match observed luminosities and lifetimes.
axioms (1)
  • domain assumption The selected high-velocity blue stars are genuine thermonuclear-supernova runaways whose properties are governed by the tested evolutionary models.
    Invoked when interpreting the 13 candidates as D6 or LP 40-365 stars and when comparing their distribution to the forward models.

pith-pipeline@v0.9.1-grok · 5979 in / 1528 out tokens · 26523 ms · 2026-06-27T11:29:46.457759+00:00 · methodology

discussion (0)

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Reference graph

Works this paper leans on

107 extracted references · 3 linked inside Pith

  1. [1]

    B., White C

    Bauer E. B., White C. J., Bildsten L., 2019, @doi [ ] 10.3847/1538-4357/ab4ea4 , https://ui.adsabs.harvard.edu/abs/2019ApJ...887...68B 887, 68

  2. [2]

    B., Chandra V., Shen K

    Bauer E. B., Chandra V., Shen K. J., Hermes J. J., 2021, @doi [ ] 10.3847/2041-8213/ac432d , https://ui.adsabs.harvard.edu/abs/2021ApJ...923L..34B 923, L34

  3. [3]

    B \'e dard A., Bergeron P., Brassard P., 2022, @doi [ ] 10.3847/1538-4357/ac609d , https://ui.adsabs.harvard.edu/abs/2022ApJ...930....8B 930, 8

  4. [4]

    Belokurov V., et al., 2020, @doi [ ] 10.1093/mnras/staa1522 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.496.1922B 496, 1922

  5. [5]

    B., Pakmor R., Shen K

    Bhat A., Bauer E. B., Pakmor R., Shen K. J., Caiazzo I., Rajamuthukumar A. S., El-Badry K., Kerzendorf W. E., 2025, @doi [ ] 10.1051/0004-6361/202451371 , https://ui.adsabs.harvard.edu/abs/2025A&A...693A.114B 693, A114

  6. [6]

    J., 2026a, @doi [arXiv e-prints] 10.48550/arXiv.2602.23900 , https://ui.adsabs.harvard.edu/abs/2026arXiv260223900B p

    Bhat A., Hollands M., Dorsch M., Geier S., Heber U., Koester D., Pakmor R., Shen K. J., 2026a, @doi [arXiv e-prints] 10.48550/arXiv.2602.23900 , https://ui.adsabs.harvard.edu/abs/2026arXiv260223900B p. arXiv:2602.23900

  7. [7]

    J., Bauer E

    Bhat A., Pakmor R., Shen K. J., Bauer E. B., Rajamuthukumar A. S., 2026b, @doi [ ] 10.1051/0004-6361/202557683 , https://ui.adsabs.harvard.edu/abs/2026A&A...706A.375B 706, A375

  8. [8]

    Blaauw A., 1961, , https://ui.adsabs.harvard.edu/abs/1961BAN....15..265B 15, 265

  9. [9]

    Bland-Hawthorn J., Gerhard O., 2016, @doi [ ] 10.1146/annurev-astro-081915-023441 , https://ui.adsabs.harvard.edu/abs/2016ARA&A..54..529B 54, 529

  10. [10]

    C., M \'e sz \'a ros S., Fleming S

    Bohlin R. C., M \'e sz \'a ros S., Fleming S. W., Gordon K. D., Koekemoer A. M., Kov \'a cs J., 2017, @doi [ ] 10.3847/1538-3881/aa6ba9 , https://ui.adsabs.harvard.edu/abs/2017AJ....153..234B 153, 234

  11. [11]

    J., Townsley D

    Boos S. J., Townsley D. M., Shen K. J., 2024, @doi [ ] 10.3847/1538-4357/ad5da2 , https://ui.adsabs.harvard.edu/abs/2024ApJ...972..200B 972, 200

  12. [12]

    Bovy J., 2015, @doi [ ] 10.1088/0067-0049/216/2/29 , https://ui.adsabs.harvard.edu/abs/2015ApJS..216...29B 216, 29

  13. [13]

    Braudo J., Soker N., 2024, @doi [The Open Journal of Astrophysics] 10.21105/astro.2310.16554 , https://ui.adsabs.harvard.edu/abs/2024OJAp....7E...7B 7, 7

  14. [14]

    R., 2015, @doi [ ] 10.1146/annurev-astro-082214-122230 , https://ui.adsabs.harvard.edu/abs/2015ARA&A..53...15B 53, 15

    Brown W. R., 2015, @doi [ ] 10.1146/annurev-astro-082214-122230 , https://ui.adsabs.harvard.edu/abs/2015ARA&A..53...15B 53, 15

  15. [15]

    R., Beers T

    Brown W. R., Beers T. C., Wilhelm R., Allende Prieto C., Geller M. J., Kenyon S. J., Kurtz M. J., 2008, @doi [ ] 10.1088/0004-6256/135/2/564 , https://ui.adsabs.harvard.edu/abs/2008AJ....135..564B 135, 564

  16. [16]

    R., Anderson J., Gnedin O

    Brown W. R., Anderson J., Gnedin O. Y., Bond H. E., Geller M. J., Kenyon S. J., 2015, @doi [ ] 10.1088/0004-637X/804/1/49 , https://ui.adsabs.harvard.edu/abs/2015ApJ...804...49B 804, 49

  17. [17]

    A., Clayton G

    Cardelli J. A., Clayton G. C., Mathis J. S., 1989, @doi [ ] 10.1086/167900 , https://ui.adsabs.harvard.edu/abs/1989ApJ...345..245C 345, 245

  18. [18]

    Chandra V., et al., 2022, @doi [ ] 10.1093/mnras/stac883 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.512.6122C 512, 6122

  19. [19]

    C., Crain J

    Clemens J. C., Crain J. A., Anderson R., 2004, in Moorwood A. F. M., Iye M., eds, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 5492, Ground-based Instrumentation for Astronomy. pp 331--340, @doi 10.1117/12.550069

  20. [20]

    Cui X.-Q., et al., 2012, @doi [Research in Astronomy and Astrophysics] 10.1088/1674-4527/12/9/003 , https://ui.adsabs.harvard.edu/abs/2012RAA....12.1197C 12, 1197

  21. [21]

    Cukanovaite E., Tremblay P.-E., Bergeron P., Freytag B., Ludwig H.-G., Steffen M., 2021, @doi [ ] 10.1093/mnras/staa3684 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.501.5274C 501, 5274

  22. [22]

    De Angeli F., et al., 2023, @doi [ ] 10.1051/0004-6361/202243680 , https://ui.adsabs.harvard.edu/abs/2023A&A...674A...2D 674, A2

  23. [23]

    El-Badry K., 2025, @doi [The Open Journal of Astrophysics] 10.33232/001c.138448 , https://ui.adsabs.harvard.edu/abs/2025OJAp....8E..62E 8, 62

  24. [24]

    M., 2021, @doi [ ] 10.1093/mnras/stab323 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.506.2269E 506, 2269

    El-Badry K., Rix H.-W., Heintz T. M., 2021, @doi [ ] 10.1093/mnras/stab323 , https://ui.adsabs.harvard.edu/abs/2021MNRAS.506.2269E 506, 2269

  25. [25]

    El-Badry K., et al., 2023, @doi [The Open Journal of Astrophysics] 10.21105/astro.2306.03914 , https://ui.adsabs.harvard.edu/abs/2023OJAp....6E..28E 6, 28

  26. [26]

    Eyer L., et al., 2023, @doi [ ] 10.1051/0004-6361/202244242 , https://ui.adsabs.harvard.edu/abs/2023A&A...674A..13E 674, A13

  27. [27]

    J., et al., 2013, @doi [ ] 10.1088/0004-637X/767/1/57 , https://ui.adsabs.harvard.edu/abs/2013ApJ...767...57F 767, 57

    Foley R. J., et al., 2013, @doi [ ] 10.1088/0004-637X/767/1/57 , https://ui.adsabs.harvard.edu/abs/2013ApJ...767...57F 767, 57

  28. [28]

    M., Ballester P., Forchi V., Garc \' a-Dabl \'o C

    Freudling W., Romaniello M., Bramich D. M., Ballester P., Forchi V., Garc \' a-Dabl \'o C. E., Moehler S., Neeser M. J., 2013, @doi [ ] 10.1051/0004-6361/201322494 , https://ui.adsabs.harvard.edu/abs/2013A&A...559A..96F 559, A96

  29. [29]

    T., Koester D., Raddi R., Toloza O., Kepler S

    G \"a nsicke B. T., Koester D., Raddi R., Toloza O., Kepler S. O., 2020, @doi [ ] 10.1093/mnras/staa1761 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.496.4079G 496, 4079

  30. [30]

    Geier S., et al., 2015, @doi [Science] 10.1126/science.1259063 , https://ui.adsabs.harvard.edu/abs/2015Sci...347.1126G 347, 1126

  31. [31]

    Geier S., et al., 2024, @doi [ ] 10.1051/0004-6361/202450778 , https://ui.adsabs.harvard.edu/abs/2024A&A...690A.368G 690, A368

  32. [32]

    B., Bhat A., Pakmor R., 2025, @doi [Nature Astronomy] 10.1038/s41550-025-02633-4 , https://ui.adsabs.harvard.edu/abs/2025NatAs...9.1523G 9, 1523

    Glanz H., Perets H. B., Bhat A., Pakmor R., 2025, @doi [Nature Astronomy] 10.1038/s41550-025-02633-4 , https://ui.adsabs.harvard.edu/abs/2025NatAs...9.1523G 9, 1523

  33. [33]

    Griffin R., 1973, @doi [ ] 10.1093/mnras/162.3.243 , https://ui.adsabs.harvard.edu/abs/1973MNRAS.162..243G 162, 243

  34. [34]

    Hayashi C., 1961, @doi [ ] 10.1093/pasj/13.4.450 , https://ui.adsabs.harvard.edu/abs/1961PASJ...13..450H 13, 450

  35. [35]

    G., 1988, @doi [ ] 10.1038/331687a0 , https://ui.adsabs.harvard.edu/abs/1988Natur.331..687H 331, 687

    Hills J. G., 1988, @doi [ ] 10.1038/331687a0 , https://ui.adsabs.harvard.edu/abs/1988Natur.331..687H 331, 687

  36. [36]

    A., Heber U., O'Toole S

    Hirsch H. A., Heber U., O'Toole S. J., Bresolin F., 2005, @doi [ ] 10.1051/0004-6361:200500212 , https://ui.adsabs.harvard.edu/abs/2005A&A...444L..61H 444, L61

  37. [37]

    A., Shen K

    Hollands M. A., Shen K. J., Raddi R., G \"a nsicke B. T., Bauer E. B., Rebassa-Mansergas A., 2025, @doi [ ] 10.1093/mnras/staf950 , https://ui.adsabs.harvard.edu/abs/2025MNRAS.541.2231H 541, 2231

  38. [38]

    M., J rgensen I., Allington-Smith J

    Hook I. M., J rgensen I., Allington-Smith J. R., Davies R. L., Metcalfe N., Murowinski R. G., Crampton D., 2004, @doi [ ] 10.1086/383624 , https://ui.adsabs.harvard.edu/abs/2004PASP..116..425H 116, 425

  39. [39]

    I., Tutukov A

    Iben Jr. I., Tutukov A. V., 1984, @doi [ ] 10.1086/190932 , https://ui.adsabs.harvard.edu/abs/1984ApJS...54..335I 54, 335

  40. [40]

    S., et al., 2023, @doi [ ] 10.3847/1538-4365/acae8d , https://ui.adsabs.harvard.edu/abs/2023ApJS..265...15J 265, 15

    Jermyn A. S., et al., 2023, @doi [ ] 10.3847/1538-4365/acae8d , https://ui.adsabs.harvard.edu/abs/2023ApJS..265...15J 265, 15

  41. [41]

    Justham S., Wolf C., Podsiadlowski P., Han Z., 2009, @doi [ ] 10.1051/0004-6361:200810106 , https://ui.adsabs.harvard.edu/abs/2009A&A...493.1081J 493, 1081

  42. [42]

    O., et al., 2016, @doi [Science] 10.1126/science.aad6705 , 352, 67

    Kepler S. O., et al., 2016, @doi [Science] 10.1126/science.aad6705 , 352, 67

  43. [43]

    E., Schmidt B

    Kerzendorf W. E., Schmidt B. P., Laird J. B., Podsiadlowski P., Bessell M. S., 2012, @doi [ ] 10.1088/0004-637X/759/1/7 , https://ui.adsabs.harvard.edu/abs/2012ApJ...759....7K 759, 7

  44. [44]

    E., et al., 2013, @doi [ ] 10.1088/0004-637X/774/2/99 , https://ui.adsabs.harvard.edu/abs/2013ApJ...774...99K 774, 99

    Kerzendorf W. E., et al., 2013, @doi [ ] 10.1088/0004-637X/774/2/99 , https://ui.adsabs.harvard.edu/abs/2013ApJ...774...99K 774, 99

  45. [45]

    E., Childress M., Scharw \"a chter J., Do T., Schmidt B

    Kerzendorf W. E., Childress M., Scharw \"a chter J., Do T., Schmidt B. P., 2014, @doi [ ] 10.1088/0004-637X/782/1/27 , https://ui.adsabs.harvard.edu/abs/2014ApJ...782...27K 782, 27

  46. [46]

    E., Strampelli G., Shen K

    Kerzendorf W. E., Strampelli G., Shen K. J., Schwab J., Pakmor R., Do T., Buchner J., Rest A., 2018, @doi [ ] 10.1093/mnras/sty1357 , https://ui.adsabs.harvard.edu/abs/2018MNRAS.479..192K 479, 192

  47. [47]

    J., et al., 2013, @doi [ ] 10.1088/0067-0049/204/1/5 , https://ui.adsabs.harvard.edu/abs/2013ApJS..204....5K 204, 5

    Kleinman S. J., et al., 2013, @doi [ ] 10.1088/0067-0049/204/1/5 , https://ui.adsabs.harvard.edu/abs/2013ApJS..204....5K 204, 5

  48. [48]

    Koester D., 2010, Memorie della Societa Astronomica Italiana, https://ui.adsabs.harvard.edu/abs/2010MmSAI..81..921K 81, 921

  49. [49]

    E., et al., 2020, @doi [ ] 10.1093/mnras/stz3081 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491.2465K 491, 2465

    Koposov S. E., et al., 2020, @doi [ ] 10.1093/mnras/stz3081 , https://ui.adsabs.harvard.edu/abs/2020MNRAS.491.2465K 491, 2465

  50. [50]

    L., 1993, ATLAS9 Stellar Atmosphere Programs and 2 km/s grid , Kurucz CD-ROM No

    Kurucz R. L., 1993, ATLAS9 Stellar Atmosphere Programs and 2 km/s grid , Kurucz CD-ROM No. 13

  51. [51]

    Leonard P. J. T., 1991, @doi [ ] 10.1086/115704 , https://ui.adsabs.harvard.edu/abs/1991AJ....101..562L 101, 562

  52. [52]

    V., Poznanski D., Wang X., Ganeshalingam M., Mannucci F., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18162.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.412.1473L 412, 1473

    Li W., Chornock R., Leaman J., Filippenko A. V., Poznanski D., Wang X., Ganeshalingam M., Mannucci F., 2011, @doi [ ] 10.1111/j.1365-2966.2011.18162.x , https://ui.adsabs.harvard.edu/abs/2011MNRAS.412.1473L 412, 1473

  53. [53]

    Lindegren L., 2018, R e-normalising the astrometric chi-square in G aia D R 2, GAIA-C3-TN-LU-LL-124, https://dms.cosmos.esa.int/COSMOS/doc_fetch.php?id=3757412

  54. [54]

    Lindegren L., et al., 2021, @doi [ ] 10.1051/0004-6361/202039709 , https://ui.adsabs.harvard.edu/abs/2021A&A...649A...2L 649, A2

  55. [55]

    Mackensen N., Reindl N., Werner K., Dorsch M., Tan S., 2025, @doi [ ] 10.1051/0004-6361/202554639 , https://ui.adsabs.harvard.edu/abs/2025A&A...700A..24M 700, A24

  56. [56]

    S., Fremling C., Kasliwal M

    Mandigo-Stoba M. S., Fremling C., Kasliwal M. M., 2022, @doi [Journal of Open Source Software] 10.21105/joss.03612 , 7, 3612

  57. [57]

    D., 2012, @doi [ ] 10.1111/j.1365-2966.2012.21871.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.426.3282M 426, 3282

    Maoz D., Mannucci F., Brandt T. D., 2012, @doi [ ] 10.1111/j.1365-2966.2012.21871.x , https://ui.adsabs.harvard.edu/abs/2012MNRAS.426.3282M 426, 3282

  58. [58]

    Maoz D., Mannucci F., Nelemans G., 2014, @doi [ ] 10.1146/annurev-astro-082812-141031 , https://ui.adsabs.harvard.edu/abs/2014ARA&A..52..107M 52, 107

  59. [59]

    Marietta E., Burrows A., Fryxell B., 2000, @doi [ ] 10.1086/313392 , https://ui.adsabs.harvard.edu/abs/2000ApJS..128..615M 128, 615

  60. [60]

    L., et al., 2008, in McLean I

    Marshall J. L., et al., 2008, in McLean I. S., Casali M. M., eds, Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series Vol. 7014, Ground-based and Airborne Instrumentation for Astronomy II. p. 701454 ( @eprint arXiv 0807.3774 ), @doi 10.1117/12.789972

  61. [61]

    arXiv:2602.23414

    Mehta V., Tiwari V., Pakmor R., Singh D., Fisher R., 2026, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2026arXiv260223414M p. arXiv:2602.23414

  62. [62]

    C., van Roestel J., Roulston B., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2304.07324 , https://ui.adsabs.harvard.edu/abs/2023arXiv230407324N p

    Nagarajan P., El-Badry K., Rodriguez A. C., van Roestel J., Roulston B., 2023, @doi [arXiv e-prints] 10.48550/arXiv.2304.07324 , https://ui.adsabs.harvard.edu/abs/2023arXiv230407324N p. arXiv:2304.07324

  63. [63]

    Neunteufel P., 2020, @doi [ ] 10.1051/0004-6361/202037792 , https://ui.adsabs.harvard.edu/abs/2020A&A...641A..52N 641, A52

  64. [64]

    S., Justham S., Podsiadlowski P., 2022, @doi [ ] 10.1051/0004-6361/202142864 , https://ui.adsabs.harvard.edu/abs/2022A&A...663A..91N 663, A91

    Neunteufel P., Preece H., Kruckow M., Geier S., Hamers A. S., Justham S., Podsiadlowski P., 2022, @doi [ ] 10.1051/0004-6361/202142864 , https://ui.adsabs.harvard.edu/abs/2022A&A...663A..91N 663, A91

  65. [65]

    B., Gunn J

    Oke J. B., Gunn J. E., 1982, @doi [ ] 10.1086/131027 , https://ui.adsabs.harvard.edu/abs/1982PASP...94..586O 94, 586

  66. [66]

    B., et al., 1995, @doi [ ] 10.1086/133562 , https://ui.adsabs.harvard.edu/abs/1995PASP..107..375O 107, 375

    Oke J. B., et al., 1995, @doi [ ] 10.1086/133562 , https://ui.adsabs.harvard.edu/abs/1995PASP..107..375O 107, 375

  67. [67]

    Pakmor R., et al., 2022, @doi [ ] 10.1093/mnras/stac3107 , https://ui.adsabs.harvard.edu/abs/2022MNRAS.517.5260P 517, 5260

  68. [68]

    arXiv:2510.11781

    Pakmor R., et al., 2025, @doi [arXiv e-prints] 10.48550/arXiv.2510.11781 , https://ui.adsabs.harvard.edu/abs/2025arXiv251011781P p. arXiv:2510.11781

  69. [69]

    M., Taam R

    Pan K.-C., Ricker P. M., Taam R. E., 2012, @doi [ ] 10.1088/0004-637X/760/1/21 , https://ui.adsabs.harvard.edu/abs/2012ApJ...760...21P 760, 21

  70. [70]

    Paxton B., Bildsten L., Dotter A., Herwig F., Lesaffre P., Timmes F., 2011, @doi [ ] 10.1088/0067-0049/192/1/3 , https://ui.adsabs.harvard.edu/abs/2011ApJS..192....3P 192, 3

  71. [71]

    Paxton B., et al., 2013, @doi [ ] 10.1088/0067-0049/208/1/4 , https://ui.adsabs.harvard.edu/abs/2013ApJS..208....4P 208, 4

  72. [72]

    Paxton B., et al., 2015, @doi [ ] 10.1088/0067-0049/220/1/15 , https://ui.adsabs.harvard.edu/abs/2015ApJS..220...15P 220, 15

  73. [73]

    Paxton B., et al., 2018, @doi [ ] 10.3847/1538-4365/aaa5a8 , https://ui.adsabs.harvard.edu/abs/2018ApJS..234...34P 234, 34

  74. [74]

    Paxton B., et al., 2019, @doi [ ] 10.3847/1538-4365/ab2241 , https://ui.adsabs.harvard.edu/abs/2019ApJS..243...10P 243, 10

  75. [75]

    A., 2019, @doi [ ] 10.1088/1538-3873/ab215d , https://ui.adsabs.harvard.edu/abs/2019PASP..131h4503P 131, 084503

    Perley D. A., 2019, @doi [ ] 10.1088/1538-3873/ab215d , https://ui.adsabs.harvard.edu/abs/2019PASP..131h4503P 131, 084503

  76. [76]

    M., Sim S

    Pollin J. M., Sim S. A., Pakmor R., Callan F. P., Collins C. E., Shingles L. J., R \"o pke F. K., Srivastav S., 2024, @doi [ ] 10.1093/mnras/stae1909 , https://ui.adsabs.harvard.edu/abs/2024MNRAS.533.3036P 533, 3036

  77. [77]

    X., Hennawi J

    Prochaska J. X., Hennawi J. F., Westfall K. B., Cooke R. J., Wang F., Hsyu T., Davies F. B., Farina E. P., 2020, arXiv e-prints, https://ui.adsabs.harvard.edu/abs/2020arXiv200506505P p. arXiv:2005.06505

  78. [78]

    J., Bildsten L., Boos S

    Prust L. J., Bildsten L., Boos S. J., 2026, @doi [ ] 10.3847/1538-4357/ae22db , https://ui.adsabs.harvard.edu/abs/2026ApJ...997...17P 997, 17

  79. [79]

    Raddi R., et al., 2019, @doi [ ] 10.1093/mnras/stz1618 , https://ui.adsabs.harvard.edu/abs/2019MNRAS.489.1489R 489, 1489

  80. [80]

    S., Bauer E

    Rajamuthukumar A. S., Bauer E. B., Justham S., Pakmor R., de Mink S. E., Neunteufel P., 2025, @doi [ ] 10.1051/0004-6361/202554452 , https://ui.adsabs.harvard.edu/abs/2025A&A...704A..82R 704, A82

Showing first 80 references.