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REVIEW 3 major objections 5 minor 78 references

Modeling the progenitors of low-mass post-accretion binaries

T0 review · 3 major / 5 minor · reviewed 2026-08-07 · deepseek-v4-flash

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Pith's one-line read The paper argues that reproducing strong barium stars' abundances requires each star to accrete more than 0.5 solar masses, and at that limit the standard binary accretion models fail to reproduce their observed mass distribution.

desk verdict Valuable new grid for post-accretion binaries whose headline strong-Ba claim overreaches the computed parameter space. read the letter →

arxiv 2505.22201 v1 pith:4D5P3BIL submitted 2025-05-28 astro-ph.SR

A.J. Dimoff , R.J. Stancliffe , C.J. Hansen , R.M. Seeburger , H. Taylor This is my paper
classification astro-ph.SR
keywords bariumstarsCHCEMP-ss-processnucleosynthesisAGBmasstransferbinaryaccretionstellarevolutionmodelsdilutionfactor
verification ladder T0 review T1 audit T2 compute T3 formal

The pith

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

The reading

The paper tries to pin down the progenitors of barium, CH, and carbon-enhanced metal-poor s-process (CEMP-s) stars, binaries whose surfaces carry heavy elements made by the slow neutron capture process in an evolved AGB companion. Using a new grid of 2,700 accretion models spanning metallicities from [Fe/H] -2.15 to -0.15 and comparing them star-by-star to observed abundances by maximum likelihood, it concludes that AGB donors of about 2-3 solar masses can explain all four populations. The reproduction works well for weak Ba, CH, and CEMP-s stars, but fails for strong Ba stars: matching their high s-process abundances requires each to accrete more than 0.50 solar masses, and in that regime the models cannot reproduce the observed mass distribution of strong Ba stars. If this is right, strong Ba stars are the place to look for missing physics in how polluted binaries accrete.

What carries the argument

The argument is carried by a grid of about 2,700 binary evolution models in which each system is specified by metallicity, AGB donor mass, initial accretor mass, and accreted mass (0.05-0.50 solar masses). Accreted AGB ejecta, taken from published s-process yield tables, are deposited on the surface and tracked with a tracer composition so that the surface abundance at any time is the mass-weighted mix of accreted material and original stellar material. The crucial mixing quantity is the dilution factor $d = M_{\mathrm{acc}}/M_{\mathrm{mix}}$, the ratio of accreted mass to the mass of the convective envelope after the first dredge-up; it controls how much of the observed s-process enhancement survives. Comparing each model at each timestep to observed effective temperature, surface gravity, metallicity, carbon, and heavy-element abundances via a chi-square maximum-likelihood test selects the best-fit progenitor for each star.

What would settle it

Compute the same grid with thermohaline mixing included and check whether the inferred accreted masses for CEMP-s and CH stars drop below about 0.1 solar masses and whether strong Ba stars can be fit with final masses above 2 solar masses. Alternatively, measure C, N, and O on the main sequence or subgiant branch of a sample of CEMP-s stars: if their surface C/N ratio declines before first dredge-up, thermohaline dilution is acting and the no-mixing models are false.

Watch

Extended reading notes

Core claim

The central claim is that the same basic scenario, a 2-3 solar mass AGB donor transferring mass to a lower-mass companion, underlies weak Ba, strong Ba, CH, and CEMP-s stars, but the strength of the required transfer separates them. Weak Ba stars are best fit by moderate accretion (up to 0.5 solar masses) onto a roughly 2.0-2.5 solar mass star; CH and CEMP-s stars by small accretions (about 0.1 solar masses) onto roughly 1.0 solar mass stars; strong Ba stars by large accretions (at least 0.5 solar masses) onto roughly 1.0-2.0 solar mass stars. The paper's key negative result is that strong Ba stars, which require the highest accretion masses, cannot be made consistent with the observed mass distribution: the models push their final masses down near 1 solar mass, about a full solar mass below the peak found in earlier observational studies, because more massive accretors dilute the accreted s-process material more thoroughly. The paper therefore states that in the high-accretion limit it is unable to reproduce the observed mass distribution of strong Ba stars.

Load-bearing premise

The result stands on the assumption that thermohaline mixing is negligible in the accretors, so surface abundances stay unchanged from the end of accretion until first dredge-up; if thermohaline mixing is significant, especially for metal-poor CEMP-s and CH stars, the inferred accreted masses would be systematically wrong.

Editorial extensions

If this is right

  • If the grid is right, AGB donors of 2-3 solar masses are common progenitors of all four classes, which connects their chemical enrichment to the same nucleosynthetic production site.
  • The mass distributions of weak Ba, CH, and CEMP-s stars are reproduced, so current convective-mixing physics appears sufficient for those systems.
  • Strong Ba stars require accretion of at least 0.5 solar masses, and wind mass-transfer models cannot deliver that much material, so their formation likely needs a different mass-transfer channel.
  • The recovered final masses of strong Ba stars sit near 1.0 solar mass, about one solar mass below observational estimates, so either the observed strong Ba sample or the treatment of dilution is incomplete.
  • Strong Ba systems require accretion efficiencies around 25 percent or higher, above the wind-accretion efficiencies predicted by three-dimensional hydrodynamical models.

Reading between the lines

Editorial extensions of the paper, not claims the author makes directly.

  • This reading suggests a testable extension: recomputing the grid with thermohaline mixing switched on for metal-poor accretors would shift the inferred small accreted masses for CEMP-s and CH stars, since the paper itself notes that thermohaline mixing can dilute light elements on the main sequence.
  • I infer that the strong-Ba mass discrepancy could also be read as evidence that the observed strong Ba sample is biased toward low-mass giants, or that a missing mixing process such as rotationally induced mixing changes how much dilution high-mass accretors experience.
  • A full binary population synthesis that feeds these best-fit progenitor parameters into initial binary distributions could predict how many strong versus weak Ba stars should exist, directly testing whether the required high-accretion channel is actually populated.
  • The authors' planned follow-up on long-period systems is a natural place to test whether wind Roche-lobe overflow or circumbinary discs can supply the angular momentum budget needed for large accretions.
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Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, and a circularity audit.

Referee Report

3 major / 5 minor

Summary. The paper presents a grid of about 2700 binary accretion models computed with the STARS code, using FRUITY AGB yields, and compares them via a maximum-likelihood chi-squared analysis to observed Ba, CH, and CEMP-s stars. The authors report consistent AGB donor masses around 2-3 Msun, moderate accreted masses (≤0.5 Msun) for weak Ba stars, large accreted masses (≥0.5 Msun) for strong Ba stars, and low accreted masses (~0.1 Msun) for CH and CEMP-s stars. They also compare derived stellar masses with the observed mass distribution and discuss orbital properties and accretion efficiencies. The central conclusion is that strong Ba stars must accrete more than 0.5 Msun to explain their abundances, and that at this grid boundary the model cannot reproduce the observed mass distribution of strong Ba stars.

Significance. If established, the claim that strong Ba stars require accretion above 0.5 Msun would identify a concrete tension between standard binary mass-transfer models and observations, motivating new modeling efforts and possibly new mass-transfer mechanisms. The paper has notable strengths: a large and reusable model grid, use of independent FRUITY yields, explicit treatment of dilution and first dredge-up, and successful reproduction of the mass and abundance distributions for weak Ba, CH, and CEMP-s stars. The individual fits (e.g., PV UMa, HD 123949, CS 29512-073) are informative. However, the headline conclusion about strong Ba stars rests on an extrapolation beyond the computed grid, since the maximum accreted mass in the grid is 0.5 Msun. The paper also concedes in Section 6 that higher-accretion models may reveal a better scenario, which undercuts the strength of the abstract's claim. The neglect of thermohaline mixing and the acknowledged correlation problem in the chi-squared comparison add further caveats, especially for the metal-poor populations.

major comments (3)
  1. [Section 3, Section 4.1, Fig. 5, Abstract/Conclusions] The central claim that strong Ba stars 'must accrete more than 0.50 Msun' is not established by the presented grid. The accreted mass is capped at 0.50 Msun by construction in Section 3, and the best-fit models piling at this boundary only demonstrate that the grid cannot represent larger values; a maximum-likelihood estimate at a discrete grid edge does not imply the true value lies at or above that edge. Moreover, since final mass is the sum of initial mass plus accreted mass, allowing larger Delta M could move the final masses upward, potentially resolving the reported mismatch with the observed mass distribution of Escorza et al. (2017). The paper's own Section 6 concedes that 'further modeling considering higher accretion masses may reveal a scenario that better describes the final mass distribution of the strong Ba stars,' which is in direct tension with the definitive wording in the abstract. Please either extend the grid to larger accreted masses for at least the strong Ba stars, or reframe the conclusion as a provisional extrapolation rather than a demonstrated failure of the standard scenario.
  2. [Section 3, Section 5.1] The neglect of thermohaline mixing is acknowledged but its impact on the inferred parameters is not quantified. The paper states in Section 5.1 that without thermohaline mixing, surface abundances remain nearly constant until first dredge-up, making differentiation between best-fit models difficult. For the metal-poor CEMP-s and CH stars, thermohaline mixing on the main sequence can significantly dilute light elements (Stancliffe et al. 2007), yet the low accreted masses (~0.05-0.1 Msun) are derived under the assumption of negligible thermohaline mixing. This could systematically bias the inferred accretion masses for these populations. Please provide a quantitative assessment of how the best-fit parameters would change if thermohaline mixing (or a range of mixing efficiencies) were included, or soften the population-level conclusions for CEMP-s and CH stars.
  3. [Section 3.1] The chi-squared comparison assumes that the fitted quantities are uncorrelated, but the paper explicitly notes that the heavy-element abundances are highly correlated with one another and with the surface parameters. This is not a minor caveat: it affects the interpretation of the differences in chi-squared between competing models and could change the ranking of best-fit models, especially when the fits differ only subtly in abundance pattern. Please discuss the likely direction and magnitude of this effect, or implement a covariance-aware likelihood to demonstrate that the main results—particularly the strong-Ba preference for the maximum accreted mass—are robust to the treatment of correlated abundances.
minor comments (5)
  1. [Section 4.1, PV UMa paragraph] The sentence 'The observed temperature The two best fit models...' is incomplete and should be rephrased.
  2. [Section 3, Eq. (1)] The variable 'Xorignial' appears to be a typo for 'Xoriginal'.
  3. [Section 5.1] The sentence beginning 'Stancliffe et al. (2007) found that ther-mohaline mixing is on the main sequence is effective...' contains a grammatical error; the phrase 'is on the main sequence is effective' should be corrected.
  4. [Figure 5] Please add the sample sizes for each population to the caption, since the CH star sample is stated to be small and this affects the interpretation of the histograms.
  5. [Abstract and Section 4.1] The abstract states 'macc≥0.5 Msun' while Section 4.1 reports that 'most fits showing 0.5 Msun'; please ensure consistent phrasing across the paper

Circularity Check

1 steps flagged · score 6.0 of 10

Abundance fitting is independent, but the strong-Ba 'must accrete >0.50 Msun' claim is read off the grid's upper boundary rather than derived from models above it.

  1. fitted input called prediction [Section 3 (Modeling Methods), Section 4.1 (Results), Abstract/Conclusions]
    "For any given final mass, initial masses range from Mf−0.50 M⊙ to Mf−0.05 M⊙, with accretion masses equal to 0.05, 0.10, 0.20, 0.30, 0.40, and 0.50 M⊙. ... The models suggest that for strong Ba stars, large amounts of material have been accreted, with most fits showing 0.50 M⊙. The distribution is strongly peaked at high accretion masses ... We also find that strong Ba stars must accrete more than 0.50 M⊙ to explain their abundance patterns."

    The grid's accretion masses are inputs, capped at 0.50 M⊙. The maximum-likelihood procedure can only select M_acc ≤ 0.50, so 'most fits showing 0.50 M⊙' is a boundary pile-up. The paper then converts this saturated edge bin into the output claim that strong Ba stars 'must accrete more than 0.50 M⊙.' Because no model with M_acc > 0.50 exists in the grid, the inequality is not derived from a computed model; it is the complement of the input range. The paper's own Section 6 concession ('further modeling considering higher accretion masses may reveal a scenario that better describes the final mass distribution of the strong Ba stars') confirms that the conclusion is an extrapolation beyond the fitted grid rather than a model prediction.

full rationale

The central abundance fitting is self-contained: observed surface abundances and parameters are external data, and the s-process ejecta are taken from the independent FRUITY database, so the best-fit AGB masses and dilution physics are not circular. The circularity is limited to the strong-Ba accretion-mass headline: the best fits are at the highest input M_acc, and the paper reports this as a lower-bound prediction without computing models above the boundary. This is a partial circularity/truncation artifact, not a wholesale construction of the result. The thermohaline-mixing omission is a stated physical assumption supported by earlier partly overlapping-author studies; it is a modelling caveat, not a circular step.

Assumptions & free parameters 6 free parameters · 5 assumptions · 0 invented entities

The grid has a small number of physically meaningful free parameters (AGB mass, accreted mass, initial/final mass, metallicity), but the discrete steps and the 0.50 Msun cap on accretion directly shape the inference. Key assumptions (same metallicity, FRUITY yields, no thermohaline mixing, convection-only mixing, q<=1) are stated, but several are known to be approximate for these stars.

free parameters (6)
  • Grid maximum accreted mass = 0.50 Msun
    The largest accretion step in the grid. Strong Ba star best fits stack at this boundary, driving the conclusion that these stars need >0.50 Msun.
  • Best-fit AGB donor mass = 2.5-2.8 Msun (population means)
    Fitted via chi-squared comparison to observed abundances and parameters.
  • Best-fit accreted mass = 0.05-0.50 Msun per star
    Fitted parameter; strong Ba stars hit the 0.50 Msun limit.
  • Best-fit initial/final accretor mass = e.g., 0.45-0.55 Msun initial for strong Ba
    Fitted via matching evolutionary track position and abundances.
  • Mixing length alpha = 2.025
    Adopted from Stancliffe (2021), not fitted here; affects dilution and inferred masses.
  • Convective overshoot delta_ov = 0.15
    Adopted from Stancliffe et al. (2015); affects mixing and thus abundances.
assumptions (5)
  • domain assumption The AGB donor and the companion star have identical metallicity.
    Stated in Section 3; the grid is built on this assumption, which may not hold for all binaries.
  • domain assumption The composition of transferred material is given by FRUITY AGB yields.
    Section 3; the model results inherit any errors in the external yield database.
  • ad hoc to paper Thermohaline mixing is negligible.
    Section 3 says it is not modeled; Section 5.1 admits it can be effective for metal-poor stars, so this is a paper-specific simplification that may bias inferred accretion masses.
  • domain assumption The secondary's surface abundances evolve only via convection and the tracer mixing formula.
    Section 3; ignores rotational mixing, atomic diffusion, and other processes.
  • domain assumption Only systems with initial mass ratio q <= 1.00 are considered.
    Section 3.1; excludes systems where the secondary evolves first.

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Pith. "Pith review of Modeling the progenitors of low-mass post-accretion binaries." pith.science (2026). https://pith.science/paper/4D5P3BIL

@misc{pith2026250522201,
  author       = {Pith},
  title        = {Pith review of: Modeling the progenitors of low-mass post-accretion binaries},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/4D5P3BIL}},
  note         = {Machine review of arXiv:2505.22201}
}
abstract

About half of the mass of all heavy elements with mass number A > 90 is formed through the slow neutron capture process (s-process), occurring in evolved asymptotic giant branch (AGB) stars with masses ~1-6 $\rm{M_{\odot}}$. The s-process can be studied by modeling the accretion of material from AGB stars onto binary barium (Ba), CH, and carbon-enhanced metal-poor (CEMP)-s stars. Comparing observationally derived surface parameters and 1D-LTE abundance patterns of s-process elements to theoretical binary accretion models, we aim to understand the formation of post-accretion systems. We explore the extent of dilution of the accreted material and describe the impact of convective mixing on the observed surface abundances. We compute a new grid of 2700 accretion models for low-mass post-accretion systems. A maximum-likelihood comparison determines the best fit models for observational samples of Ba, CH, and CEMP-s stars. We find consistent AGB donor masses in the mass range of 2-3 $\rm{M_{\odot}}$ across our sample of post-accretion binaries. We find the formation scenario for weak Ba stars is an AGB star transferring a moderate amount of mass ($\leq$0.5 $\rm{M_{\odot}}$) resulting in a ~2.0-2.5 $\rm{M_{\odot}}$ star. The strong Ba stars are best fit with lower final masses ~1.0-2.0 $\rm{M_{\odot}}$, and significant accreted mass ($\geq$0.5 $\rm{M_{\odot}}$). The CH and CEMP-s stars display lower final masses (~1.0 $\rm{M_{\odot}}$) and small amounts of transferred material (~0.1 $\rm{M_{\odot}}$). We find that Ba stars generally accrete more material than CEMP-s and CH stars. We also find that strong Ba stars must accrete more than 0.50 $\rm{M_{\odot}}$ to explain their abundance patterns, and in this limit we are unable to reproduce the observed mass distribution of strong Ba stars. The mass distributions of the weak Ba stars, CEMP-s, and CH stars are well reproduced in our modeling.

Figures

Figures reproduced from arXiv: 2505.22201 by the authors.

Figure 1
Figure 1. Kiel diagram showing surface gravities and effective tempera￾tures for the collected observational sample. Blue data points are strong Ba stars, cyan data points are weak Ba stars, orange data points are CH stars, and red data points are CEMP-s stars. Surface parameters and abundances are collected from Dimoff et al. (2024), de Castro et al. (2016), Roriz et al. (2021b), Goswami et al. (2006), Karinkuzhi & Goswami (… view at source ↗
Figure 2
Figure 2. Left: Evolutionary tracks for a sample of stars with mf inal = 2.50 M⊙ at [Fe/H] = -0.15 with different accretion masses and initial mass ratios, with accretion phases for each model highlighted in blue. Right: Relative surface abundance of the s-process element Ba. The abundance is elevated after the accretion phase, and only after the onset of first dredge-up and mixing is the surface abundance diluted [PITH_FULL… view at source ↗
Figure 3
Figure 3. Example Kippenhahn diagram for a 2.00 M⊙ star accreting 0.50 M⊙ of material from a 2.50 M⊙ AGB star at a metallicity of [Fe/H] = -0.15. Green colors denote convective regions, and purple colors denote radiative regions, determined by the computed difference in the radia￾tive and adiabatic transfer gradients. In the total mass on the y-axis, the accretion phase can be identified by the increase in mass. Note that the… view at source ↗
Figures from the paper (4 more)
Figure 4
Figure 4. Figure 4: Kiel diagrams and abundance fits for the weak Ba star PV UMa, the strong Ba star HD 123949, and the CEMP-s star CS 29512-073, each showing the three best-fitting models and their associated χ 2 values. solar mass. At higher masses, the more massive convective en- velop…
Figure 5
Figure 5. Figure 5: Histograms of model parameters for the different classes of stars in our investigation. Dark blue regions are strong Ba stars, cyan regions are weak Ba stars, red regions are CEMP-s stars, and orange regions are CH stars. lower masses, and to maintain the observed high…
Figure 6
Figure 6. Figure 6: Computed accretion efficiencies for our sample populations. Purple-blue contours are the strong Ba stars, and the green contours are the weak Ba stars. Red-yellow contours are our carbon-enhanced sample, including both CH and CEMP-s stars. 5.3. Possible mass transfer s…
Figure 7
Figure 7. Figure 7: Eccentricity-period diagram for our combined sample of stars. Cyan data points are weak Ba stars, blue data points are strong Ba stars, orange data points are CH stars, and crimson data points are the CEMP￾s stars. Centroids of the populations are marked with X’s of co…

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Works this paper leans on

78 extracted references · 55 canonical work pages

  1. [1]

    R., Izzard, R

    Abate, C., Pols, O. R., Izzard, R. G., Mohamed, S. S., & de Mink, S. E. 2013, A&A, 552, A26

    work page 2013

  2. [2]

    R., & Stancliffe, R

    Abate, C., Pols, O. R., & Stancliffe, R. J. 2018, A&A, 620, A63

    work page 2018

  3. [3]

    Allen, D. M. & Barbuy, B. 2006, A&A, 454, 895

    work page 2006

  4. [4]

    J., & Scott, P

    Asplund, M., Grevesse, N., Sauval, A. J., & Scott, P. 2009, ARA&A, 47, 481

    2009

  5. [5]

    1996, Baltic Astronomy, 5, 217

    Bartkevicius, A. 1996, Baltic Astronomy, 5, 217

    work page 1996

  6. [6]

    Beers, T. C. & Christlieb, N. 2005, ARA&A, 43, 531

    2005

  7. [7]

    2014, ApJ, 787, 10

    Bisterzo, S., Travaglio, C., Gallino, R., Wiescher, M., & Käppeler, F. 2014, ApJ, 787, 10

    2014

  8. [8]

    Boffin, H. M. J. & Jorissen, A. 1988, A&A, 205, 155

    work page 1988

Show all 78 references
  1. [9]

    Bond, H. E. 1974, ApJ, 194, 95

    1974

  2. [10]

    & Hoyle, F

    Bondi, H. & Hoyle, F. 1944, MNRAS, 104, 273

    1944

  3. [11]

    M., Burbidge, G

    Burbidge, E. M., Burbidge, G. R., Fowler, W. A., & Hoyle, F. 1957, Reviews of Modern Physics, 29, 547

    1957

  4. [12]

    Busso, M., Gallino, R., & Wasserburg, G. J. 1999, ARA&A, 37, 239

    1999

  5. [13]

    2016, ApJ, 833, 181

    Cristallo, S., Karinkuzhi, D., Goswami, A., Piersanti, L., & Gobrecht, D. 2016, ApJ, 833, 181

    2016

  6. [14]

    2011, ApJS, 197, 17

    Cristallo, S., Piersanti, L., Straniero, O., et al. 2011, ApJS, 197, 17

    2011

  7. [15]

    2015, ApJS, 219, 40

    Cristallo, S., Straniero, O., Piersanti, L., & Gobrecht, D. 2015, ApJS, 219, 40

    2015

  8. [16]

    2018, A&A, 620, A146

    Cseh, B., Lugaro, M., D’Orazi, V ., et al. 2018, A&A, 620, A146

    2018

  9. [17]

    P., et al

    Cseh, B., Világos, B., Roriz, M. P., et al. 2022, A&A, 660, A128 de Castro, D. B., Pereira, C. B., Roig, F., et al. 2016, MNRAS, 459, 4299 den Hartogh, J. W., Yagüe López, A., Cseh, B., et al. 2023, A&A, 672, A143

    2022

  10. [18]

    J., Hansen, C

    Dimoff, A. J., Hansen, C. J., Stancliffe, R., et al. 2024, A&A, 691, A128 Domínguez, I., Cristallo, S., Straniero, O., et al. 2011, in Astronomical Society of the Pacific Conference Series, V ol. 445, Why Galaxies Care about AGB Stars II: Shining Examples and Common Inhabitant...

    2024

  11. [19]

    2004, New A Rev., 48, 843

    Edgar, R. 2004, New A Rev., 48, 843

    2004

  12. [20]

    1993, A&A, 275, 101

    Edvardsson, B., Andersen, J., Gustafsson, B., et al. 1993, A&A, 275, 101

    1993

  13. [21]

    Eggleton, P. P. 1971, MNRAS, 151, 351

    1971

  14. [22]

    Eggleton, P. P. 1972, MNRAS, 156, 361

    1972

  15. [23]

    Escorza, A., Boffin, H. M. J., Jorissen, A., et al. 2017, A&A, 608, A100

    2017

  16. [24]

    2019, A&A, 626, A128

    Escorza, A., Karinkuzhi, D., Jorissen, A., et al. 2019, A&A, 626, A128

    2019

  17. [25]

    1998, ApJ, 497, 388

    Gallino, R., Arlandini, C., Busso, M., et al. 1998, ApJ, 497, 388

    1998

  18. [26]

    C., et al

    Goswami, A., Aoki, W., Beers, T. C., et al. 2006, MNRAS, 372, 343

    2006

  19. [27]

    2016, MNRAS, 455, 402

    Goswami, A., Aoki, W., & Karinkuzhi, D. 2016, MNRAS, 455, 402

    2016

  20. [28]

    P., Rathour, R

    Goswami, P. P., Rathour, R. S., & Goswami, A. 2021, A&A, 649, A49

    2021

  21. [29]

    P., Podsiadlowski, P., & Tout, C

    Han, Z., Eggleton, P. P., Podsiadlowski, P., & Tout, C. A. 1995, MNRAS, 277, 1443

    1995

  22. [30]

    J., Andersen, A

    Hansen, C. J., Andersen, A. C., & Christlieb, N. 2014, A&A, 568, A47

    2014

  23. [31]

    J., Hansen, T

    Hansen, C. J., Hansen, T. T., Koch, A., et al. 2019, A&A, 623, A128

    2019

  24. [32]

    R., Tout, C

    Hurley, J. R., Tout, C. A., & Pols, O. R. 2002, MNRAS, 329, 897

    2002

  25. [33]

    G., Dermine, T., & Church, R

    Izzard, R. G., Dermine, T., & Church, R. P. 2010, A&A, 523, A10

    2010

  26. [34]

    Jorissen, A., Boffin, H. M. J., Karinkuzhi, D., et al. 2019, A&A, 626, A127

    2019

  27. [35]

    1998, A&A, 332, 877

    Jorissen, A., Van Eck, S., Mayor, M., & Udry, S. 1998, A&A, 332, 877

    1998

  28. [36]

    2016, A&A, 586, A158

    Jorissen, A., Van Eck, S., Van Winckel, H., et al. 2016, A&A, 586, A158

    2016

  29. [37]

    P., Molero, M., Navó, G., et al

    Jost, F. P., Molero, M., Navó, G., et al. 2024, arXiv e-prints, arXiv:2407.14319 Käppeler, F., Gallino, R., Bisterzo, S., & Aoki, W. 2011, Reviews of Modern Physics, 83, 157

    2024 arXiv

  30. [38]

    Karakas, A. I. & Lattanzio, J. C. 2014, PASA, 31, e030

    2014

  31. [39]

    I., Tout, C

    Karakas, A. I., Tout, C. A., & Lattanzio, J. C. 2000, MNRAS, 316, 689

    2000

  32. [40]

    & Goswami, A

    Karinkuzhi, D. & Goswami, A. 2014, MNRAS, 440, 1095

    2014

  33. [41]

    & Goswami, A

    Karinkuzhi, D. & Goswami, A. 2015, MNRAS, 446, 2348

    2015

  34. [42]

    2021, A&A, 654, A140

    Karinkuzhi, D., Van Eck, S., Jorissen, A., et al. 2021, A&A, 654, A140

    2021

  35. [43]

    2018, A&A, 618, A32

    Karinkuzhi, D., Van Eck, S., Jorissen, A., et al. 2018, A&A, 618, A32

    2018

  36. [44]

    Krynski, P., Siess, L., Jorissen, A., & Davis, P. J. 2025, arXiv e-prints, arXiv:2504.10939

    2025 arXiv

  37. [45]

    J., Abate, C., & Matrozis, E

    Liu, Z.-W., Stancliffe, R. J., Abate, C., & Matrozis, E. 2017, ApJ, 846, 117

    2017

  38. [46]

    J., Rizzuti, F., et al

    Lombardo, L., Hansen, C. J., Rizzuti, F., et al. 2025, A&A, 693, A293

    2025

  39. [47]

    K., Dawson, D

    Lu, P. K., Dawson, D. W., Upgren, A. R., & Weis, E. W. 1983, ApJS, 52, 169

    1983

  40. [48]

    C., et al

    Lucatello, S., Tsangarides, S., Beers, T. C., et al. 2005, ApJ, 625, 825

    2005

  41. [49]

    2023, Annual Review of Nuclear and Particle Science, 73, 315

    Lugaro, M., Pignatari, M., Reifarth, R., & Wiescher, M. 2023, Annual Review of Nuclear and Particle Science, 73, 315

    2023

  42. [50]

    A., Plez, B., et al

    Masseron, T., Johnson, J. A., Plez, B., et al. 2010, A&A, 509, A93

    2010

  43. [51]

    Matrozis, E., Abate, C., & Stancliffe, R. J. 2017, A&A, 606, A137

    2017

  44. [52]

    & Stancliffe, R

    Matrozis, E. & Stancliffe, R. J. 2016, A&A, 592, A29

    2016

  45. [53]

    McClure, R. D. 1984, ApJ, 280, L31

    1984

  46. [54]

    D., Fletcher, J

    McClure, R. D., Fletcher, J. M., & Nemec, J. M. 1980, ApJ, 238, L35

    1980

  47. [55]

    McClure, R. D. & Woodsworth, A. W. 1990, ApJ, 352, 709

    1990

  48. [56]

    & Podsiadlowski, P

    Mohamed, S. & Podsiadlowski, P. 2007, in Astronomical Society of the Pacific Conference Series, V ol. 372, 15th European Workshop on White Dwarfs, ed. R. Napiwotzki & M. R. Burleigh, 397

    2007

  49. [57]

    & Podsiadlowski, P

    Mohamed, S. & Podsiadlowski, P. 2012, Baltic Astronomy, 21, 88

    2012

  50. [58]

    E., Ryan, S

    Norris, J. E., Ryan, S. G., & Beers, T. C. 1997, ApJ, 488, 350

    1997

  51. [59]

    B., Sales Silva, J

    Pereira, C. B., Sales Silva, J. V ., Chavero, C., Roig, F., & Jilinski, E. 2011, A&A, 533, A51

    2011

  52. [60]

    R., Tout, C

    Pols, O. R., Tout, C. A., Eggleton, P. P., & Han, Z. 1995, MNRAS, 274, 964

    1995

  53. [61]

    2018, MNRAS, 476, 3432

    Prantzos, N., Abia, C., Limongi, M., Chieffi, A., & Cristallo, S. 2018, MNRAS, 476, 3432

    2018

  54. [62]

    P., Shejeelammal, J., & Masseron, T

    Purandardas, M., Goswami, A., Goswami, P. P., Shejeelammal, J., & Masseron, T. 2019, MNRAS, 486, 3266

    2019

  55. [63]

    I., Tosi, M., & Matteucci, F

    Romano, D., Karakas, A. I., Tosi, M., & Matteucci, F. 2010, A&A, 522, A32

    2010

  56. [64]

    P., Holanda, N., da Conceição, L

    Roriz, M. P., Holanda, N., da Conceição, L. V ., et al. 2024, AJ, 167, 184

    2024

  57. [65]

    P., Lugaro, M., Pereira, C

    Roriz, M. P., Lugaro, M., Pereira, C. B., et al. 2021b, MNRAS, 507, 1956

    1956

  58. [66]

    G., Norris, J

    Ryan, S. G., Norris, J. E., & Beers, T. C. 1996, ApJ, 471, 254

    1996

  59. [67]

    R., & Eggleton, P

    Schroder, K.-P., Pols, O. R., & Eggleton, P. P. 1997, MNRAS, 285, 696

    1997

  60. [68]

    Stancliffe, R. J. 2005, PhD thesis, University of Cambridge, UK

    2005

  61. [69]

    Stancliffe, R. J. 2015, in Astronomical Society of the Pacific Conference Series, V ol. 497, Why Galaxies Care about AGB Stars III: A Closer Look in Space and Time, ed. F. Kerschbaum, R. F. Wing, & J. Hron, 253

    2015

  62. [70]

    Stancliffe, R. J. 2021, MNRAS, 505, 5554

    2021

  63. [71]

    Stancliffe, R. J. & Eldridge, J. J. 2009, MNRAS, 396, 1699

    2009

  64. [72]

    J., Fossati, L., Passy, J

    Stancliffe, R. J., Fossati, L., Passy, J. C., & Schneider, F. R. N. 2015, A&A, 575, A117

    2015

  65. [73]

    Stancliffe, R. J. & Glebbeek, E. 2008, MNRAS, 389, 1828

    2008

  66. [74]

    J., Glebbeek, E., Izzard, R

    Stancliffe, R. J., Glebbeek, E., Izzard, R. G., & Pols, O. R. 2007, A&A, 464, L57

    2007

  67. [75]

    D., McConnachie, A

    Starkenburg, E., Shetrone, M. D., McConnachie, A. W., & Venn, K. A. 2014, MNRAS, 441, 1217

    2014

  68. [76]

    2006, Nucl

    Straniero, O., Gallino, R., & Cristallo, S. 2006, Nucl. Phys. A, 777, 311

    2006

  69. [77]

    1998, A&AS, 131, 25

    Udry, S., Jorissen, A., Mayor, M., & Van Eck, S. 1998, A&AS, 131, 25

    1998

  70. [78]

    1965, MNRAS, 129, 263 Article number, page 11 of 12 A&A proofs:manuscript no

    Warner, B. 1965, MNRAS, 129, 263 Article number, page 11 of 12 A&A proofs:manuscript no. Modeling_the_progenitors_of_low_mass_post_accretion_binaries Appendix A: The Model Grid Fig. A.1.Our computed grid of evolutionary models in the HR diagram, displaying every 5th model in g...

    1965

Pith tools

Reviewed August 7, 2026 · model on record in the stance chip above.