Calibration of binary population synthesis models using white dwarf binaries from APOGEE, GALEX, and Gaia Article Swipe
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· 2025
· Open Access
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· DOI: https://doi.org/10.1051/0004-6361/202555600
The effectiveness and stability of mass transfer in a binary system are crucial for determining the final product of its evolution. Rapid binary population synthesis codes simplify the complex physics of mass transfer and common-envelope evolution by adopting parameterized prescriptions for the stability of mass transfer, accretion efficiency in stable mass transfer, and the efficiency of common-envelope ejection. Our goal is to calibrate these uncertain parameters by comparing binary population synthesis models with observational data. Binary systems composed of a white dwarf and main-sequence star are ideal for studying the effects of binary interaction, as they can be formed through stable or unstable mass transfer, or without any interaction. These different evolutionary paths affect the orbital period and masses of the present-day population. The APOGEE-GALEX-Gaia catalog (AGGC) provides a homogeneous sample of over 500 systems with well-measured radial velocities that can be used as a comparison baseline for population synthesis simulations of white dwarf–main-sequence binaries. We compare the distribution of the observed maximum radial velocity variation (Δ RV max ) in the AGGC to binary population models simulated with COSMIC, a publicly developed binary population synthesis code. Within these synthetic populations, we vary the mass transfer and common-envelope ejection efficiency, and the criteria for mass transfer stability at the first ascent, asymptotic, and thermally pulsing giant branch phases. We also compare our models to systems with orbital solutions and estimated stellar masses. The Δ RV max comparison shows clear preference for models with a higher fraction of stars undergoing stable mass transfer during the first ascent giant branch phase, and for highly effective envelope ejection during common-envelope phases. For the few systems with estimated WD masses, a comparison to models shows a slight preference for nonconservative stable mass transfer. In COSMIC and similar codes, the envelope ejection efficiency and the envelope binding energy are degenerate parameters. Therefore, our result of a high ejection efficiency may indicate either that additional sources of energy (such as recombination energy from the expansion of the envelope) are required to eject the envelope, or that its binding energy is lower than traditionally assumed. Future comparisons to population synthesis simulations of WD binaries can be drawn for other datasets as they become available, such as upcoming Gaia data releases and the future LISA mission, and for binary systems in other evolutionary stages.
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- https://doi.org/10.1051/0004-6361/202555600
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- 46
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https://openalex.org/W4415353136Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1051/0004-6361/202555600Digital Object Identifier
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Calibration of binary population synthesis models using white dwarf binaries from APOGEE, GALEX, and GaiaWork title
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articleOpenAlex work type
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2025Year of publication
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2025-10-20Full publication date if available
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A. C. Rubio, K. Breivik, Carles Badenes, K. El-Badry, Borja Anguiano, Ethan Linck, Steven R. Majewski, Keivan G. StassunList of authors in order
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https://doi.org/10.1051/0004-6361/202555600Publisher landing page
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hybridOpen access status per OpenAlex
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| abstract_inverted_index.stability | 3, 42, 206 |
| abstract_inverted_index.synthesis | 24, 70, 149, 185, 352 |
| abstract_inverted_index.synthetic | 189 |
| abstract_inverted_index.thermally | 213 |
| abstract_inverted_index.transfer, | 45, 51, 104 |
| abstract_inverted_index.transfer. | 288 |
| abstract_inverted_index.uncertain | 64 |
| abstract_inverted_index.variation | 165 |
| abstract_inverted_index.Therefore, | 306 |
| abstract_inverted_index.additional | 318 |
| abstract_inverted_index.available, | 366 |
| abstract_inverted_index.comparison | 145, 236, 277 |
| abstract_inverted_index.degenerate | 304 |
| abstract_inverted_index.efficiency | 47, 54, 297, 313 |
| abstract_inverted_index.evolution. | 20 |
| abstract_inverted_index.parameters | 65 |
| abstract_inverted_index.population | 23, 69, 148, 175, 184, 351 |
| abstract_inverted_index.preference | 239, 283 |
| abstract_inverted_index.undergoing | 248 |
| abstract_inverted_index.velocities | 138 |
| abstract_inverted_index.asymptotic, | 211 |
| abstract_inverted_index.comparisons | 349 |
| abstract_inverted_index.determining | 14 |
| abstract_inverted_index.efficiency, | 199 |
| abstract_inverted_index.homogeneous | 129 |
| abstract_inverted_index.parameters. | 305 |
| abstract_inverted_index.population. | 122 |
| abstract_inverted_index.present-day | 121 |
| abstract_inverted_index.simulations | 150, 353 |
| abstract_inverted_index.distribution | 158 |
| abstract_inverted_index.evolutionary | 111, 384 |
| abstract_inverted_index.interaction, | 93 |
| abstract_inverted_index.interaction. | 108 |
| abstract_inverted_index.populations, | 190 |
| abstract_inverted_index.effectiveness | 1 |
| abstract_inverted_index.main-sequence | 83 |
| abstract_inverted_index.observational | 73 |
| abstract_inverted_index.parameterized | 38 |
| abstract_inverted_index.prescriptions | 39 |
| abstract_inverted_index.recombination | 324 |
| abstract_inverted_index.traditionally | 346 |
| abstract_inverted_index.well-measured | 136 |
| abstract_inverted_index.common-envelope | 34, 56, 197, 266 |
| abstract_inverted_index.nonconservative | 285 |
| abstract_inverted_index.APOGEE-GALEX-Gaia | 124 |
| abstract_inverted_index.dwarf–main-sequence | 153 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.35254398 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |