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A Framework for Linking Pre- and Post-Common Envelope Binary Properties with Star Clusters: The First Demonstration with a Massive White Dwarf+M Dwarf Binary in Alessi 12

T0 review · 3 major / 5 minor · reviewed 2026-08-01 · deepseek-v4-flash

Pith's one-line read The first star-cluster post-common-envelope binary with fully constrained pre- and post-envelope states, Alessi12-PCE, pins common-envelope efficiency to either ≈0.99 (mid-AGB) or ≈0.05 (late-AGB).

desk verdict A genuinely new cluster-anchored post-CE benchmark with careful observations; the alpha_CE inference is real but degenerate, and the single-star assumption has a slightly self-referential flavor. read the letter →

arxiv 2607.20611 v1 pith:XYORRS5B submitted 2026-07-22 astro-ph.SR astro-ph.HE

classification astro-ph.SRastro-ph.HE
keywords binarystarscommonenvelopeevolutionwhitedwarfsMdwarfopenstarclustersstellarorbitalperiodradialvelocity
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

This paper establishes that Alessi12-PCE is the first white dwarf + M dwarf binary in a star cluster for which both the pre-common-envelope and post-common-envelope properties are precisely measured. Combining the cluster age with the white dwarf cooling age, the authors reconstruct a 5.4±0.1 solar-mass progenitor that engulfed its M dwarf companion during the asymptotic giant branch phase, leaving a 6.99-hour orbit with a final separation of 2.07 solar radii. They show that convection-based common envelope models reproduce this exact final separation in only two scenarios: a mid-AGB interaction with efficiency α_CE≈0.99, or a late-AGB interaction with α_CE≈0.05. The framework matters because cluster membership supplies an independent stellar age, allowing the timing of the envelope ejection to be anchored — something field binaries cannot provide — and enabling empirical tests of common-envelope physics.

What carries the argument

The load-bearing machinery is an age-anchored reconstruction chain: cluster membership fixes the system's age; the white dwarf's atmosphere models give its mass and cooling age; subtracting the cooling age from the cluster age yields the progenitor's main-sequence-plus-giant lifetime, which stellar evolution tracks convert into a 5.4±0.1 solar-mass initial mass. With that mass and the observed final separation, the common-envelope efficiency α_CE — the fraction of released orbital energy that unbinds the envelope — is computed from the energy budget. The paper then applies a convection-based model in which, at each inspiral step, the local efficiency is zero when convection can carry the rel

What would settle it

If refined cluster-age measurements place Alessi 12 outside roughly 85–185 Myr, the 5.4±0.1 solar-mass progenitor inference fails; or if a full double-lined orbit yields an M dwarf mass outside 0.37±0.058 solar masses, the final separation and the two α_CE solutions (0.99 and 0.05) are ruled out.

Watch

Extended reading notes

Core claim

The paper's central claim is that Alessi12-PCE, a 6.99-hour detached binary in the open cluster Alessi 12 composed of a 1.06±0.02 solar-mass white dwarf and a 0.37±0.058 solar-mass M4 dwarf, is the first such system in a cluster whose entire evolutionary history can be reconstructed without invoking a merger. The cluster age (135±50 Myr) minus the white dwarf cooling age (22±5 Myr) gives the lifetime of the WD progenitor; stellar evolution models then require an initial mass of 5.4±0.1 solar masses, with the common envelope beginning on the asymptotic giant branch. Energy-budget arguments yield a broad range α_CE≈0.03–1.55 depending on exactly when along the AGB the interaction begins, and c

Load-bearing premise

The entire reconstruction assumes the white dwarf formed by single-star evolution, so its formation time equals the cluster age minus the cooling age and its helium core grows on the AGB at the single-star rate; if the WD is instead a merger product, the inferred 5.4 solar-mass progenitor and all derived α_CE values collapse.

Editorial extensions

If this is right

  • Either a mid-AGB common envelope with near-unity efficiency or a late-AGB event with efficiency near 0.05 is required to explain the observed 6.99-hour orbit; both match the same measured post-CE parameters.
  • The inferred α_CE varies from about 0.03 to 1.55 depending on when along the AGB the envelope ejection begins, so CE timing is degenerate with efficiency in this single system.
  • The white dwarf's consistency with the initial-final mass relation, plus the negligible dynamical encounter rate, makes Alessi12-PCE a clean benchmark that rules out merger and dynamical formation channels.
  • The same cluster-based framework can be applied to other WD+MS binaries in open clusters to place empirical constraints on common-envelope physics without relying on field-star age assumptions.
  • If a similar common-envelope event is caught by time-domain surveys, the predicted light-curve rise timescale could distinguish the mid-AGB high-efficiency scenario from the late-AGB low-efficiency scenario.

Reading between the lines

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

  • Editorial inference: A refined age for Alessi 12 — for example from higher-precision photometry or asteroseismology — could break the AGB-timing degeneracy and single out one of the two α_CE solutions, making the system a stronger test of convection-regulated CE models.
  • Editorial inference: The existence of two widely different efficiencies for the same binary suggests α_CE is unlikely to be a single universal constant; population synthesis codes that adopt a universal value may need to account for CE onset timing as a key variable.
  • Editorial inference: Applied to an ensemble of cluster WD+MS binaries spanning different WD masses, this framework could map how α_CE and CE outcomes depend on the donor's evolutionary phase, offering a direct observational proxy for envelope structure at CE onset.
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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 manuscript presents a framework for reconstructing the pre- and post-common-envelope properties of WD+MS binaries in star clusters and applies it to Alessi12-PCE, a WD+M dwarf binary in the open cluster Alessi 12. Using Keck/LRIS, Gemini/GMOS, and Shane/Kast spectroscopy, Swift/UVOT photometry, and ZTF light curves, the authors measure a DA WD with M_WD = 1.06 ± 0.02 M_sun, T_eff = 39,100 ± 300 K, log g = 8.69 ± 0.04, an M4V companion with M = 0.37 ± 0.058 M_sun, and an orbital period of 6.99 hr, implying a_f = 2.07 ± 0.02 R_sun. Combining the WD cooling age with the Alessi 12 cluster age and MESA single-star models yields a progenitor mass M_i = 5.4 ± 0.1 M_sun and initial separations a_i ≈ 1200–3400 R_sun. Model-agnostic α_CE values range from about 0.03 to 1.55 depending on the assumed AGB onset time; the Wilson & Nordhaus convective-CE framework reproduces the observed a_f at a mid-AGB solution with α_CE ≈ 0.99 and a late-AGB solution with α_CE ≈ 0.05. The authors argue against a merger and a dynamical origin and propose the approach as a general method for cluster post-CE binaries.

Significance. If the reconstruction is correct, Alessi12-PCE is a rare and valuable anchor: it is the first cluster post-CE binary with a massive WD for which both pre- and post-CE parameters are claimed to be precisely determined, and the comparison with convective-CE models is a forward prediction rather than a fit to the final period. The observational characterization is careful: Monte Carlo uncertainties are propagated for the WD parameters, the orbital period is confirmed by anti-correlated RVs, and alternative formation channels are explicitly considered. However, two load-bearing issues currently prevent acceptance of the central α_CE and pre-CE claims: the exclusion of a merger origin is circular, and the initial-separation calculation appears to use the wrong mass ratio in the Roche-lobe formula. These issues are fixable within the scope of a revision, but they must be addressed before the central results can be regarded as established.

major comments (3)
  1. [§6.2, §7.2, §9.1] The exclusion of a merger origin is circular and load-bearing. Section 6.2 adopts thick-hydrogen WD atmosphere models because “the WD properties and age of Alessi 12 rule out a merger scenario (see Section 9.1)”, but Section 9.1 infers M_i = 5.4 M_sun from MESA single-star models and then demonstrates consistency with the Miller et al. (2026) IFMR using that same M_i. Since the MESA grid is stated in §7.2 to be calibrated to the Cummings et al. (2018) IFMR, the comparison in Figure 10 is not independent. Section 9.2 computes only single-single encounter rates and does not address the primordial triple/merger channel invoked for V471 Tau. If the WD is a merger product, t_form = t_cluster − t_cool and the AGB core-growth reconstruction in §7.2 no longer apply, and the derived M_i, a_i, and α_CE values lose their foundation. Please supply an independent merger diagnostic or explicitly refra
  2. [§7.3, Eq. (1), §8.1] Equation (1) appears to use the wrong mass ratio for the donor’s Roche lobe. The text defines q ≡ M*/M_i and then applies the Eggleton approximation; with that definition the formula returns the Roche-lobe radius of the M-dwarf companion, not of the giant donor. To compute the initial separation at RLOF for the donor one needs q = M_i/M_* (or the appropriate reciprocal form). Since a_i is used to compute E_orb,i in §8.1 and therefore α_CE, the numerical values in Table 2 and Figure 9 may be systematically affected. Please verify the definition used in the code, correct the formula if needed, and recompute the quoted ranges.
  3. [§7.2, Table 2] The quoted progenitor mass M_i = 5.4 ± 0.1 M_sun does not include the adopted cluster-age uncertainty. The authors adopt log t_cluster = 0.20, giving t_cluster = 134.89 ± 49.78 Myr and t_form = 113.04 ± 50.02 Myr, yet no propagation of this large uncertainty into M_i or α_CE is shown. The allowed mass range appears to come only from the M_WD and RGB-radius conditions. Please state explicitly whether the age uncertainty affects the allowed M_i range and include it in the α_CE uncertainty budget, or explain why it is irrelevant.
minor comments (5)
  1. [§5.2.2] The WD RV description refers to Hβ/Hγ in one sentence and Hβ/Hδ elsewhere. Please check which lines were actually used and make the text consistent.
  2. [Figure 9] The labels “Early-AGB / Mid-AGB / Late-AGB” each show min = 0.034, max = 1.55, which appears to be a typo; the text in §8.1 gives different ranges for different AGB stages. Please correct the figure labels to match the stated values.
  3. [§4.2 vs §9.2] The adopted reddening is A_V = 0.10 from Cantat-Gaudin et al. (2020) in §4.2 but 0.08 in the dynamical-rate calculation of §9.2. Please reconcile or explain the difference.
  4. [Abstract, §8.2.2] The phrase “exactly two scenarios” is stronger than the analysis supports: the companion mass has a range (0.326–0.414 M_sun) and the 5.3 and 5.5 M_sun models are said to behave similarly. The two crossings are better described as two families of solutions or two AGB epochs, each with an associated α_CE range.
  5. [Throughout] Minor typos include “a the physically-motivated” in §8.2 and “Aless12-PCE” in the Figure 8 caption. These do not affect the science.

Circularity Check

1 steps flagged · score 6.0 of 10

The merger-exclusion test is circular: M_i = 5.4 is computed from the single-star assumption and then used to validate that same assumption.

  1. self definitional [§7.2 (with §6.2 and §9.1)]
    "Despite the relatively large uncertainty in the Alessi 12 cluster age, the inferred formation times are inconsistent with a merger scenario (see Section 9.1 for details), so the WD evolution can be modeled as a single star up until the CE event."

    The 'inferred formation times' are obtained in §7.2 from t_form = t_cluster − t_cool using single-star MESA models; this identity presupposes the WD formed by single-star evolution rather than a merger. §7.2 then refers to §9.1 to conclude that a merger is excluded. In §9.1, the same single-star-derived M_i = 5.4±0.1 is plotted against the single-star IFMR, and the agreement is used to conclude that 'the mass (and temperature) of the WD in Alessi12-PCE is consistent with single-star evolutionary models.' That consistency is a restatement of the input assumption, not an independent test: if the WD were a merger product, t_form would not equal t_cluster − t_cool, so the derived M_i would not be a physical initial mass. §6.2's adoption of a thick hydrogen atmosphere is likewise justified by r

full rationale

The observed post-CE quantities (P_orb, M_WD, M_*, a_f) are independent measurements from spectroscopy, photometry, and Kepler's law, and the MESA-based computation of M_i is not fitted to the binary's final separation. The Wilson & Nordhaus convective-CE framework is applied without tuning its free parameters to Alessi12-PCE and is anchored to external binary populations, so the heavy self-citation by itself is not the circular step. The genuine circularity is the merger exclusion: §7.2 computes M_i = 5.4±0.1 under the single-star assumption (t_form = t_cluster − t_cool), §9.1 uses that model-dependent M_i to claim consistency with the single-star IFMR, and §6.2/§7.2 then use that claim to justify the single-star modeling. The thin/thick atmosphere difference is small, so the load-bearing use of §9.1 is the authorization of single-star evolution, and that authorization is circular. Because the derived pre-CE mass and all α_CE values collapse if the WD is a merger product, the circularity affects the central pre-CE reconstruction, although the rest of the analysis retains independent content; hence a score of 6 rather than higher.

Assumptions & free parameters 3 free parameters · 6 assumptions · 0 invented entities

The central claim rests on standard astrophysical models (MESA, WD cooling tracks, IFMR) plus a coauthor-developed CE framework. The main ad hoc choices are the AGB-stage fractions, the adopted cluster-age uncertainty, and the M-dwarf systematic. No new physics entities are introduced.

free parameters (3)
  • AGB onset stage fractions = 33%, 66%, 99% of maximum AGB radius
    Chosen by hand to represent early/mid/late AGB interactions; directly sets the range of initial separations a_i ≈ 1200–3400 R_sun and all derived α_CE values (Sections 7.3, 8.1).
  • Adopted cluster age uncertainty = log t_cluster = 0.20 (σ ≈ 50 Myr)
    No individual uncertainty is provided in Cantat-Gaudin et al. (2020); the authors adopt the catalog's typical value and propagate it into t_form and M_i. This choice influences which MESA models are allowed (Section 7.2).
  • M dwarf mass systematic uncertainty = 10%
    Included to account for known systematic underpredictions of the Mann et al. (2019) M_Ks relation in tight binaries; directly affects the companion mass grid used in CE modeling (Section 6.1).
assumptions (6)
  • domain assumption The Hα emission line originates predominately from the irradiated surface of the M dwarf and traces its center of light, not its center of mass; therefore the measured semi-amplitude underestimates the true value.
    Section 5.3: used to interpret the RV curve and to argue q < 0.5 is consistent with the photometric mass measurements. If the emission originated from the WD or from starspots, the RV-derived upper limit would be invalid, though the anti-correlated motion and period remain secure.
  • domain assumption The WD's pre-CE evolution was single-star evolution up to the CE, and the CE onset time is t_cluster - t_cool, with the helium core mass at onset approximately equal to the final WD mass.
    Section 7.2: This is the central premise of the IFMR-style reconstruction. It requires cluster membership and a non-merger origin; the authors test merger (Section 9.1) and dynamical (Section 9.2) alternatives.
  • domain assumption The M dwarf's mass is unchanged by the CE because its thermal timescale (10^8–10^9 yr) vastly exceeds the CE duration (~hundreds of days).
    Section 7.1: assumed based on Hjellming & Taam (1991) and Nordhaus & Spiegel (2013); if significant accretion occurred, the pre-CE mass and separation estimates would shift.
  • domain assumption For M_i > 5.3 M_sun the CE occurs on the AGB rather than the RGB, because the AGB radius exceeds the maximum RGB radius at the relevant core mass.
    Section 7.2: used to restrict the progenitor mass to 5.3–5.5 M_sun and to map the helium-core growth to the AGB phase.
  • domain assumption The Wilson & Nordhaus (2019) convective CE framework—where the local CE efficiency is 0 or 1 depending on convective transport timescales—is a valid physical description of CE energy deposition.
    Section 8.2: The central conclusion that convective CE models reproduce the observed separation depends entirely on this theoretical model, which was developed by coauthor Nordhaus and collaborators and is not independently machine-checked.
  • domain assumption The MESA models with solar metallicity and mass-loss prescriptions (Reimers η=0.7, Bloecker η=0.15) produce WDs consistent with the empirical IFMR (Cummings et al. 2018).
    Section 7.2: used to infer M_i from the post-CE WD mass and to compute envelope binding energies; if the mass-loss prescription is wrong, both M_i and E_bind shift.

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Cite this review

Pith. "Pith review of A Framework for Linking Pre- and Post-Common Envelope Binary Properties with Star Clusters: The First Demonstration with a Massive White Dwarf+M Dwarf Binary in Alessi 12." pith.science (2026). https://pith.science/paper/XYORRS5B

@misc{pith2026260720611,
  author       = {Pith},
  title        = {Pith review of: A Framework for Linking Pre- and Post-Common Envelope Binary Properties with Star Clusters: The First Demonstration with a Massive White Dwarf+M Dwarf Binary in Alessi 12},
  year         = {2026},
  howpublished = {\url{https://pith.science/paper/XYORRS5B}},
  note         = {Machine review of arXiv:2607.20611}
}
abstract

Common envelope (CE) evolution is a critical phase in the lives of binary stars, producing close binaries that are progenitors of type Ia supernovae and gravitational wave sources. Despite its importance, CE evolution remains poorly understood, largely due to the scarcity of systems with constrained pre- and post-CE properties. Here, we present a star cluster-based framework for reconstructing the evolutionary histories of white dwarf+main-sequence (WD+MS) post-CE binaries, where cluster membership can provide an independent age constraint and/or rule out a merger origin for the WD. We demonstrate this method with Alessi12-PCE, the first such binary in an open cluster with precisely determined pre- and post-CE properties. We classify the companion as an M4V and measure a WD mass of $1.06 \pm 0.02 M_{\odot}$, making it the most massive WD+MS binary associated with a cluster. A 6.99-hour periodicity detected in a light curve is confirmed as the binary orbital period via radial velocity monitoring. Combined with the WD mass, WD cooling age, and Alessi 12 cluster age, stellar evolution models imply a $5.40 \pm 0.10 M_{\odot}$ WD progenitor that entered a CE on the asymptotic giant branch (AGB). CE evolution models where convection is the dominant physical mechanism that sets $\alpha_{\text{CE}}$ reproduce the observed orbital separation in exactly two scenarios: either a mid-AGB interaction with $\alpha_{\text{CE}}\approx0.99$, or a late-AGB interaction with $\alpha_{\text{CE}}\approx0.05$. Applicable to other post-CE binaries in star clusters, our new framework enables empirical constraints on CE physics inaccessible from field binaries alone.

Figures

Figures reproduced from arXiv: 2607.20611 by the authors.

Figure 1
Figure 1. A χ 2 cluster membership analysis for Alessi12-PCE. Left: A 3D spatial analysis of Alessi12-PCE (star) relative to the probable cluster members (P > 0.5) of Alessi 12 from T. Cantat-Gaudin et al. (2020) (circles, colored by their χ 2 value), with the cluster center marked by a white cross. Each source is colored by its spatial χ 2 value (color bar), computed from a combination of right ascension (α), declination (δ)… view at source ↗
Figure 2
Figure 2. Multi-wavelength spectral energy distribution of Alessi12-PCE, combining ultraviolet photometry from Swift UVOT (U, B, UVW1, UVM2, UVW2), optical photometry from Pan-STARRS1 (g, r, i, z, y), and near-infrared photometry from 2MASS (J, H, Ks). Each photometric band is indicated accordingly. The SED reveals the composite nature of the system: a hot WD dominates the ultraviolet and blue optical flux, while an M dwarf c… view at source ↗
Figure 3
Figure 3. Summary of fitting properties to determine the M dwarf spectral type and WD atmospheric parameters (Teff and log g). Left: Flux-space spectral fitting of Alessi12-PCE. Although a broad range of WD atmospheric models provide acceptable fits to the observed continuum (gray), only models containing an M4V companion are consistent within 1σ, demonstrating that the companion’s spectral type is robustly constrained. The b… view at source ↗
Figures from the paper (7 more)
Figure 4
Figure 4. Figure 4: The orbital variability of Alessi12-PCE. Left panel: A schematic illustrating variability due to a reflection/irradiation effect. Here, the WD irradiates one hemisphere of the tidally locked M dwarf, so the same face always points towards the WD throughout the binary’s…
Figure 5
Figure 5. Figure 5: A Monte Carlo analysis to determine the cooling age (tcool; left plot) and mass (MWD; right plot) of the WD in Alessi12-PCE, using the A. B´edard et al. (2020) “thick” DA WD atmosphere models (colored grid). All Monte Carlo results are plotted as small circles and our …
Figure 6
Figure 6. Figure 6: Location of Alessi12-PCE (pink star) in the Porb–MWD plane, compared with the currently known population of detached WD+MS post-CE binaries. With MWD = 1.06 ± 0.02 M⊙, Alessi12-PCE is the most massive such system associated with an open star cluster. Comparison systems…
Figure 7
Figure 7. Figure 7: The pre-CE WD progenitor core mass (solid lines) and radius (dashed lines) evolution of 5.2 − 5.6M⊙ MESA models from E. C. Wilson & J. Nordhaus (2020). Only models that (i) reach a WD mass of MWD = 1.06 ± 0.02M⊙ (black line) in the time span of tform = tcluster − tcool…
Figure 8
Figure 8. Figure 8: Left panels: The CE ejection efficiency αCE (top) and the final orbital separation (bottom) as a function of age along the AGB for a 5.4M⊙ progenitor. The mid-AGB (green) and late-AGB (blue) MESA profiles from E. C. Wilson & J. Nordhaus (2019) that reproduce the observ…
Figure 9
Figure 9. Figure 9: Comparison of CE efficiency (αCE) estimates for WD post-CE binaries from this work and the literature, color-coded by binary type (WD+MS, WD+WD, WD+brown dwarf). The top panel shows literature which present individual system estimates for αCE. This includes our model a…
Figure 10
Figure 10. Figure 10: Alessi12-PCE (pink) is shown relative to the initial–final mass relation (IFMR) for single white dwarfs in open clusters from D. R. Miller et al. (2026) (blue). Empir￾ical IFMR constraints from D. R. Miller et al. (2026) (blue line), along with relations based on PARS…

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Works this paper leans on

162 extracted references · 22 canonical work pages

  1. [1]

    J., Bavera, S

    Andrews, J. J., Bavera, S. S., Briel, M., et al. 2025, ApJS, 281, 3, doi: 10.3847/1538-4365/adfb78 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013a, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collaboration, Robitaille, T. P., Tollerud, E. J., et al. 2013b, A&A, 558, A33, doi: 10.1051/0004-6361/201322068 Astropy Collabor...

  2. [2]

    2021, AJ, 161, 147, doi: 10.3847/1538-3881/abd806

    Demleitner, M., & Andrae, R. 2021, AJ, 161, 147, doi: 10.3847/1538-3881/abd806

  3. [3]

    2021, lightkurve/lightkurve: Lightkurve v2.0.9, v2.0.9 Zenodo, doi: 10.5281/zenodo.4654522 B´ edard, A., Bergeron, P., Brassard, P., & Fontaine, G

    Barentsen, G., Hedges, C., Vin ´ ıcius, Z., et al. 2021, lightkurve/lightkurve: Lightkurve v2.0.9, v2.0.9 Zenodo, doi: 10.5281/zenodo.4654522 B´ edard, A., Bergeron, P., Brassard, P., & Fontaine, G. 2020, ApJ, 901, 93, doi: 10.3847/1538-4357/abafbe

  4. [4]

    2017, MNRAS, 471, 4702, doi: 10.1093/mnras/stx1759

    Belczynski, K., Ryu, T., Perna, R., et al. 2017, MNRAS, 471, 4702, doi: 10.1093/mnras/stx1759

  5. [5]

    Bessell, M. S. 1999, PASP, 111, 1426, doi: 10.1086/316454

  6. [6]

    1995, A&A, 297, 727

    Bloecker, T. 1995, A&A, 297, 727

  7. [7]

    2019, A&A, 623, A108, doi: 10.1051/0004-6361/201834693

    Bossini, D., Vallenari, A., Bragaglia, A., et al. 2019, A&A, 623, A108, doi: 10.1051/0004-6361/201834693

  8. [8]

    G., Curtis, J

    Bouma, L. G., Curtis, J. L., Hartman, J. D., Winn, J. N., & Bakos, G. ´A. 2021, AJ, 162, 197, doi: 10.3847/1538-3881/ac18cd

Show all 162 references
  1. [9]

    2020, ApJ, 898, 71, doi: 10.3847/1538-4357/ab9d85

    Breivik, K., Coughlin, S., Zevin, M., et al. 2020, ApJ, 898, 71, doi: 10.3847/1538-4357/ab9d85

  2. [11]

    S., Lam, A., Levina, S., et al

    Broekgaarden, F. S., Lam, A., Levina, S., et al. 2026, arXiv e-prints, arXiv:2606.05322, doi: 10.48550/arXiv.2606.05322 26Grondin et al

  3. [12]

    J., Parsons, S

    Brown, A. J., Parsons, S. G., van Roestel, J., et al. 2023, MNRAS, 521, 1880, doi: 10.1093/mnras/stad612

  4. [13]

    2014, A&A, 566, A86, doi: 10.1051/0004-6361/201323052

    Camacho, J., Torres, S., Garc ´ ıa-Berro, E., et al. 2014, A&A, 566, A86, doi: 10.1051/0004-6361/201323052

  5. [14]

    2020, A&A, 640, A1, doi: 10.1051/0004-6361/202038192

    Cantat-Gaudin, T., Anders, F., Castro-Ginard, A., et al. 2020, A&A, 640, A1, doi: 10.1051/0004-6361/202038192

  6. [15]

    A., Clayton, G

    Cardelli, J. A., Clayton, G. C., & Mathis, J. S. 1989, ApJ, 345, 245, doi: 10.1086/167900

  7. [16]

    2020, MNRAS, 495, 4028, doi: 10.1093/mnras/staa1273

    Carroll-Nellenback, J., & Tu, Y. 2020, MNRAS, 495, 4028, doi: 10.1093/mnras/staa1273

  8. [17]

    G., Nordhaus, J., & Wilson, E

    Chamandy, L., Blackman, E. G., Nordhaus, J., & Wilson, E. 2021, MNRAS, 502, L110, doi: 10.1093/mnrasl/slab017

  9. [18]

    G., et al

    Chamandy, L., Carroll-Nellenback, J., Blackman, E. G., et al. 2024, MNRAS, 528, 234, doi: 10.1093/mnras/stae036

  10. [19]

    G., & Wilson, E

    Chamandy, L., Nordhaus, J., Blackman, E. G., & Wilson, E. 2025, PASA, 42, e027, doi: 10.1017/pasa.2025.4

  11. [20]

    G., et al

    Chamandy, L., Frank, A., Blackman, E. G., et al. 2018, MNRAS, 480, 1898, doi: 10.1093/mnras/sty1950

  12. [21]

    C., Magnier, E

    Chambers, K. C., Magnier, E. A., Metcalfe, N., et al. 2016, arXiv e-prints, arXiv:1612.05560, doi: 10.48550/arXiv.1612.05560

  13. [22]

    2015, MNRAS, 452, 1068, doi: 10.1093/mnras/stv1281

    Chen, Y., Bressan, A., Girardi, L., et al. 2015, MNRAS, 452, 1068, doi: 10.1093/mnras/stv1281

  14. [23]

    2014, MNRAS, 444, 2525, doi: 10.1093/mnras/stu1605

    Chen, Y., Girardi, L., Bressan, A., et al. 2014, MNRAS, 444, 2525, doi: 10.1093/mnras/stu1605

  15. [24]

    2017, MNRAS, 470, 1442, doi: 10.1093/mnras/stx1326

    Cojocaru, R., Rebassa-Mansergas, A., Torres, S., & Garc ´ ıa-Berro, E. 2017, MNRAS, 470, 1442, doi: 10.1093/mnras/stx1326

  16. [25]

    2025, Astropy, v7.2.0 Zenodo, doi: 10.5281/zenodo.17756022

    Collaboration, A. 2025, Astropy, v7.2.0 Zenodo, doi: 10.5281/zenodo.17756022

  17. [26]

    1995, Machine Learning, 20, 273, doi: 10.1007/BF00994018

    Cortes, C., & Vapnik, V. 1995, Machine Learning, 20, 273, doi: 10.1007/BF00994018

  18. [27]

    2018, ApJ, 866, 21, doi: 10.3847/1538-4357/aadfd6

    Ramirez-Ruiz, E., & Choi, J. 2018, ApJ, 866, 21, doi: 10.3847/1538-4357/aadfd6

  19. [28]

    J., Kolb, U., & Knigge, C

    Davis, P. J., Kolb, U., & Knigge, C. 2012, MNRAS, 419, 287, doi: 10.1111/j.1365-2966.2011.19690.x De Marco, O. 2009, PASP, 121, 316, doi: 10.1086/597765 De Marco, O., Passy, J.-C., Moe, M., et al. 2011, MNRAS, 411, 2277, doi: 10.1111/j.1365-2966.2010.17891.x Di Stefano, R., Kr...

  20. [29]

    Lau, H. H. B. 2015, MNRAS, 446, 2599, doi: 10.1093/mnras/stu2180

  21. [30]

    2023, A&A, 675, A89, doi: 10.1051/0004-6361/202245219

    Donada, J., Anders, F., Jordi, C., et al. 2023, A&A, 675, A89, doi: 10.1051/0004-6361/202245219

  22. [31]

    Eggleton, P. P. 1983, ApJ, 268, 368, doi: 10.1086/160960

  23. [32]

    J., Stanway, E

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

  24. [33]

    K., Tremblay, P.-E., G¨ ansicke, B

    Elms, A. K., Tremblay, P.-E., G¨ ansicke, B. T., et al. 2023, MNRAS, 524, 4996, doi: 10.1093/mnras/stad2171

  25. [34]

    1987, in IAU Colloq

    Fontaine, G., & Wesemael, F. 1987, in IAU Colloq. 95: Second Conference on Faint Blue Stars, ed. A. G. D

  26. [35]

    J., Bavera, S

    Fragos, T., Andrews, J. J., Bavera, S. S., et al. 2023, ApJS, 264, 45, doi: 10.3847/1538-4365/ac90c1

  27. [36]

    J., Barnes, S

    Fritzewski, D. J., Barnes, S. A., Weingrill, J., et al. 2023, A&A, 674, A152, doi: 10.1051/0004-6361/202346083

  28. [37]

    L., Woosley, S

    Fryer, C. L., Woosley, S. E., & Hartmann, D. H. 1999, ApJ, 526, 152, doi: 10.1086/307992 Gaia Collaboration, Brown, A. G. A., Vallenari, A., et al. 2016, A&A, 595, A2, doi: 10.1051/0004-6361/201629512 Gaia Collaboration, Vallenari, A., Brown, A. G. A., et al. 2023, A&A, 674, A...

  29. [38]

    2004, ApJ, 611, 1005, doi: 10.1086/422091

    Gehrels, N., Chincarini, G., Giommi, P., et al. 2004, ApJ, 611, 1005, doi: 10.1086/422091

  30. [39]

    2015, MNRAS, 454, 576, doi: 10.1093/mnras/stv1848

    Gieles, M., & Zocchi, A. 2015, MNRAS, 454, 576, doi: 10.1093/mnras/stv1848

  31. [40]

    H., & Rebull, L

    Godoy-Rivera, D., Pinsonneault, M. H., & Rebull, L. M. 2021, ApJS, 257, 46, doi: 10.3847/1538-4365/ac2058

  32. [41]

    2026, scipy/scipy: SciPy 1.18.0, v1.18.0 Zenodo, doi: 10.5281/zenodo.20764140

    Gommers, R., Virtanen, P., Haberland, M., et al. 2026, scipy/scipy: SciPy 1.18.0, v1.18.0 Zenodo, doi: 10.5281/zenodo.20764140

  33. [42]

    M., Drout, M

    Grondin, S. M., Drout, M. R., Nordhaus, J., et al. 2024, ApJ, 976, 102, doi: 10.3847/1538-4357/ad7500

  34. [43]

    2022, MNRAS, 511, 5994, doi: 10.1093/mnras/stac463

    Guidarelli, G., Nordhaus, J., Carroll-Nellenback, J., et al. 2022, MNRAS, 511, 5994, doi: 10.1093/mnras/stac463

  35. [44]

    2019, MNRAS, 490, 1179, doi: 10.1093/mnras/stz2641

    Guidarelli, G., Nordhaus, J., Chamandy, L., et al. 2019, MNRAS, 490, 1179, doi: 10.1093/mnras/stz2641

  36. [45]

    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

  37. [46]

    J., & Jao, W.-C

    Henry, T. J., & Jao, W.-C. 2024, ARA&A, 62, 593, doi: 10.1146/annurev-astro-052722-102740

  38. [47]

    S., Schreiber, M

    Hernandez, M. S., Schreiber, M. R., Parsons, S. G., et al. 2021, MNRAS, 501, 1677, doi: 10.1093/mnras/staa3815

  39. [48]

    S., Schreiber, M

    Hernandez, M. S., Schreiber, M. R., Parsons, S. G., et al. 2022a, MNRAS, 517, 2867, doi: 10.1093/mnras/stac2837

  40. [49]

    S., Schreiber, M

    Hernandez, M. S., Schreiber, M. R., Parsons, S. G., et al. 2022b, MNRAS, 512, 1843, doi: 10.1093/mnras/stac604

  41. [50]

    S., & Taam, R

    Hjellming, M. S., & Taam, R. E. 1991, ApJ, 370, 709, doi: 10.1086/169854

  42. [51]

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

    Hook, I. M., Jørgensen, I., Allington-Smith, J. R., et al. 2004, PASP, 116, 425, doi: 10.1086/383624 Linking Pre/Post-CE Binary Properties with Star Clusters27

  43. [52]

    Hunter, J. D. 2007, Computing in Science & Engineering, 9, 90, doi: 10.1109/MCSE.2007.55

  44. [53]

    R., Tout, C

    Hurley, J. R., Tout, C. A., & Pols, O. R. 2002, MNRAS, 329, 897, doi: 10.1046/j.1365-8711.2002.05038.x

  45. [54]

    Iben, Jr., I., & Tutukov, A. V. 1984, ApJ, 282, 615, doi: 10.1086/162241 IRSA. 2022, Zwicky Transient Facility Image Service, IPAC, doi: 10.26131/IRSA539

  46. [55]

    Fregeau, J. M. 2008, MNRAS, 386, 553, doi: 10.1111/j.1365-2966.2008.13064.x

  47. [57]

    2015, MNRAS, 447, 2181, doi: 10.1093/mnras/stu2582

    Ivanova, N., Justham, S., & Podsiadlowski, P. 2015, MNRAS, 447, 2181, doi: 10.1093/mnras/stu2582

  48. [58]

    2020, Common Envelope Evolution, 2514-3433 (IOP), doi: 10.1088/2514-3433/abb6f0

    Ivanova, N., Justham, S., & Ricker, P. 2020, Common Envelope Evolution, 2514-3433 (IOP), doi: 10.1088/2514-3433/abb6f0

  49. [59]

    2013, A&A Rv, 21, 59, doi: 10.1007/s00159-013-0059-2

    Ivanova, N., Justham, S., Chen, X., et al. 2013, A&A Rv, 21, 59, doi: 10.1007/s00159-013-0059-2

  50. [60]

    2024, arXiv e-prints, arXiv:2404.07388, doi: 10.48550/arXiv.2404.07388

    Jackim, R., Heyl, J., & Richer, H. 2024, arXiv e-prints, arXiv:2404.07388, doi: 10.48550/arXiv.2404.07388

  51. [61]

    S., Bauer, E

    Jermyn, A. S., Bauer, E. B., Schwab, J., et al. 2023, ApJS, 265, 15, doi: 10.3847/1538-4365/acae8d

  52. [62]

    V., Piskunov, A

    Kharchenko, N. V., Piskunov, A. E., R¨ oser, S., Schilbach, E., & Scholz, R. D. 2005, A&A, 438, 1163, doi: 10.1051/0004-6361:20042523

  53. [63]

    G., Kosakowski, A., et al

    Kilic, M., Moss, A. G., Kosakowski, A., et al. 2023, MNRAS, 518, 2341, doi: 10.1093/mnras/stac3182

  54. [64]

    2016, in Positioning and Power in Academic Publishing: Players, Agents and Agendas, ed

    Kluyver, T., Ragan-Kelley, B., P´ erez, F., et al. 2016, in Positioning and Power in Academic Publishing: Players, Agents and Agendas, ed. F. Loizides & B. Schmidt, IOS Press, 87 – 90

  55. [65]

    Z., Weatherford, N

    Kremer, K., Rui, N. Z., Weatherford, N. C., et al. 2021, ApJ, 917, 28, doi: 10.3847/1538-4357/ac06d4

  56. [66]

    2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x

    Kroupa, P. 2001, MNRAS, 322, 231, doi: 10.1046/j.1365-8711.2001.04022.x

  57. [67]

    Lau, M. Y. M., Hirai, R., Price, D. J., & Mandel, I. 2022, MNRAS, 516, 4669, doi: 10.1093/mnras/stac2490

  58. [68]

    Law-Smith, J. A. P., Everson, R. W., Ramirez-Ruiz, E., et al. 2020, arXiv e-prints, arXiv:2011.06630, doi: 10.48550/arXiv.2011.06630

  59. [69]

    2011, MNRAS, 410, 2370, doi: 10.1111/j.1365-2966.2010.17609.x

    Leigh, N., & Sills, A. 2011, MNRAS, 410, 2370, doi: 10.1111/j.1365-2966.2010.17609.x

  60. [70]

    2025, arXiv e-prints, arXiv:2501.14494, doi: 10.48550/arXiv.2501.14494 Lightkurve Collaboration, Cardoso, J

    Li, J., Ting, Y.-S., Rix, H.-W., et al. 2025, arXiv e-prints, arXiv:2501.14494, doi: 10.48550/arXiv.2501.14494 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...

  61. [71]

    K., & Han, Z

    Liu, Z.-W., R¨ opke, F. K., & Han, Z. 2023, Research in Astronomy and Astrophysics, 23, 082001, doi: 10.1088/1674-4527/acd89e

  62. [72]

    Lomb, N. R. 1976, Ap&SS, 39, 447, doi: 10.1007/BF00648343

  63. [73]

    W., Dupuy, T., Kraus, A

    Mann, A. W., Dupuy, T., Kraus, A. L., et al. 2019, ApJ, 871, 63, doi: 10.3847/1538-4357/aaf3bc

  64. [74]

    2022, Universe, 8, 243, doi: 10.3390/universe8040243

    Marigo, P. 2022, Universe, 8, 243, doi: 10.3390/universe8040243

  65. [75]

    2017, ApJ, 835, 77, doi: 10.3847/1538-4357/835/1/77

    Marigo, P., Girardi, L., Bressan, A., et al. 2017, ApJ, 835, 77, doi: 10.3847/1538-4357/835/1/77

  66. [76]

    D., Curtis, J

    Marigo, P., Cummings, J. D., Curtis, J. L., et al. 2020, Nature Astronomy, 4, 1102, doi: 10.1038/s41550-020-1132-1

  67. [77]

    J., Laher, R

    Masci, F. J., Laher, R. R., Rusholme, B., et al. 2019, PASP, 131, 018003, doi: 10.1088/1538-3873/aae8ac

  68. [78]

    2020, ApJ, 905, 107, doi: 10.3847/1538-4357/abc686

    Charbonneau, D. 2020, ApJ, 905, 107, doi: 10.3847/1538-4357/abc686

  69. [79]

    E., et al

    Melis, C., Klein, B., Doyle, A. E., et al. 2020, ApJ, 905, 56, doi: 10.3847/1538-4357/abbdfa

  70. [80]

    2022, ApJL, 926, L24, doi: 10.3847/2041-8213/ac50a5

    Tremblay, P.-E. 2022, ApJL, 926, L24, doi: 10.3847/2041-8213/ac50a5

  71. [81]

    R., Caiazzo, I., Heyl, J., et al

    Miller, D. R., Caiazzo, I., Heyl, J., et al. 2026, ApJ, 996, 69, doi: 10.3847/1538-4357/ae18c8

  72. [82]

    S., & Stone, R

    Miller, J. S., & Stone, R. P. S. 1993, Lick Observatory Techical Reports, 66

  73. [83]

    P., West, A

    Morgan, D. P., West, A. A., Garc´ es, A., et al. 2012, AJ, 144, 93, doi: 10.1088/0004-6256/144/4/93

  74. [84]

    D., et al

    Motherway, E., Linck, E., Mathieu, R. D., et al. 2026, AJ, 171, 159, doi: 10.3847/1538-3881/ae3b42

  75. [85]

    S., Nordhaus, J., & Drout, M

    Muirhead, P. S., Nordhaus, J., & Drout, M. R. 2022, AJ, 163, 34, doi: 10.3847/1538-3881/ac390f

  76. [86]

    K., Ganguly, A., & Chatterjee, S

    Nayak, P. K., Ganguly, A., & Chatterjee, S. 2024, MNRAS, 527, 6100, doi: 10.1093/mnras/stad3580 Nebot G´ omez-Mor´ an, A., G¨ ansicke, B. T., Schreiber, M. R., et al. 2011, A&A, 536, A43, doi: 10.1051/0004-6361/201117514

  77. [87]

    Zwart, S. F. 2000, A&A, 360, 1011, doi: 10.48550/arXiv.astro-ph/0006216 28Grondin et al

  78. [88]

    2001, A&A, 365, 491, doi: 10.1051/0004-6361:20000147

    Verbunt, F. 2001, A&A, 365, 491, doi: 10.1051/0004-6361:20000147

  79. [89]

    R., Irwin, J., Charbonneau, D., et al

    Newton, E. R., Irwin, J., Charbonneau, D., et al. 2017, ApJ, 834, 85, doi: 10.3847/1538-4357/834/1/85

  80. [90]

    Nordhaus, J., & Blackman, E. G. 2006, MNRAS, 370, 2004, doi: 10.1111/j.1365-2966.2006.10625.x

  81. [92]

    Nordhaus, J., & Spiegel, D. S. 2013, MNRAS, 432, 500, doi: 10.1093/mnras/stt569

  82. [93]

    Blackman, E. G. 2011, Proceedings of the National Academy of Science, 108, 3135, doi: 10.1073/pnas.1015005108

  83. [94]

    Noughani, N., Nordhaus, J., Richmond, M., & Wilson, E. C. 2024, arXiv e-prints, arXiv:2406.04118, doi: 10.48550/arXiv.2406.04118 O’Brien, M. S., Bond, H. E., & Sion, E. M. 2001, ApJ, 563, 971, doi: 10.1086/324040

  84. [95]

    T., R¨ opke, F

    Ohlmann, S. T., R¨ opke, F. K., Pakmor, R., & Springel, V. 2016, ApJL, 816, L9, doi: 10.3847/2041-8205/816/1/L9

  85. [96]

    B., Cohen, J

    Oke, J. B., Cohen, J. G., Carr, M., et al. 1995, PASP, 107, 375, doi: 10.1086/133562

  86. [97]

    1976, in IAU Symposium, Vol

    Paczynski, B. 1976, in IAU Symposium, Vol. 73, Structure and Evolution of Close Binary Systems, ed. P. Eggleton, S. Mitton, & J. Whelan, 75 pandas development team, T. 2026, pandas-dev/pandas: Pandas, v3.0.2 Zenodo, doi: 10.5281/zenodo.19340003

  87. [99]

    G., Rebassa-Mansergas, A., Schreiber, M

    Parsons, S. G., Rebassa-Mansergas, A., Schreiber, M. R., et al. 2016, MNRAS, 463, 2125, doi: 10.1093/mnras/stw2143

  88. [100]

    G., G¨ ansicke, B

    Parsons, S. G., G¨ ansicke, B. T., Marsh, T. R., et al. 2018, MNRAS, 481, 1083, doi: 10.1093/mnras/sty2345

  89. [101]

    L., et al

    Passy, J.-C., De Marco, O., Fryer, C. L., et al. 2012, ApJ, 744, 52, doi: 10.1088/0004-637X/744/1/52

  90. [102]

    2019, MNRAS, 485, 5666, doi: 10.1093/mnras/stz725

    Pastorelli, G., Marigo, P., Girardi, L., et al. 2019, MNRAS, 485, 5666, doi: 10.1093/mnras/stz725

  91. [103]

    2020, MNRAS, 498, 3283, doi: 10.1093/mnras/staa2565

    Pastorelli, G., Marigo, P., Girardi, L., et al. 2020, MNRAS, 498, 3283, doi: 10.1093/mnras/staa2565

  92. [105]

    2011b, ApJS, 192, 3, doi: 10.1088/0067-0049/192/1/3

    Paxton, B., Bildsten, L., Dotter, A., et al. 2011b, ApJS, 192, 3, doi: 10.1088/0067-0049/192/1/3

  93. [106]

    2013, ApJS, 208, 4, doi: 10.1088/0067-0049/208/1/4

    Paxton, B., Cantiello, M., Arras, P., et al. 2013, ApJS, 208, 4, doi: 10.1088/0067-0049/208/1/4

  94. [107]

    2015, ApJS, 220, 15, doi: 10.1088/0067-0049/220/1/15

    Paxton, B., Marchant, P., Schwab, J., et al. 2015, ApJS, 220, 15, doi: 10.1088/0067-0049/220/1/15

  95. [108]

    B., et al

    Paxton, B., Schwab, J., Bauer, E. B., et al. 2018, ApJS, 234, 34, doi: 10.3847/1538-4365/aaa5a8

  96. [109]

    2019, ApJS, 243, 10, doi: 10.3847/1538-4365/ab2241

    Paxton, B., Smolec, R., Schwab, J., et al. 2019, ApJS, 243, 10, doi: 10.3847/1538-4365/ab2241

  97. [110]

    2025, arXiv e-prints, arXiv:2502.19496, doi: 10.48550/arXiv.2502.19496

    Pelisoli, I., & Williams, J. 2025, arXiv e-prints, arXiv:2502.19496, doi: 10.48550/arXiv.2502.19496

  98. [111]

    Perez, F., & Granger, B. E. 2007, Computing in Science and Engineering, 9, 21, doi: 10.1109/MCSE.2007.53

  99. [112]

    Pickles, A. J. 1998, PASP, 110, 863, doi: 10.1086/316197

  100. [113]

    C., Di Stefano, R., & Han, Z

    Rappaport, S., Podsiadlowski, P., Joss, P. C., Di Stefano, R., & Han, Z. 1995, MNRAS, 273, 731, doi: 10.1093/mnras/273.3.731

  101. [114]

    A., & Livio, M

    Rasio, F. A., & Livio, M. 1996, ApJ, 471, 366, doi: 10.1086/177975

  102. [115]

    R., & Koester, D

    Schreiber, M. R., & Koester, D. 2007, MNRAS, 382, 1377, doi: 10.1111/j.1365-2966.2007.12288.x

  103. [116]

    2010, MNRAS, 402, 620, doi: 10.1111/j.1365-2966.2009.15915.x

    Koester, D., & Rodr ´ ıguez-Gil, P. 2010, MNRAS, 402, 620, doi: 10.1111/j.1365-2966.2009.15915.x

  104. [117]

    R., & G¨ ansicke, B

    Rebassa-Mansergas, A., Schreiber, M. R., & G¨ ansicke, B. T. 2013, MNRAS, 429, 3570, doi: 10.1093/mnras/sts630

  105. [118]

    M., et al

    Rebassa-Mansergas, A., Solano, E., Jim´ enez-Esteban, F. M., et al. 2021, MNRAS, 506, 5201, doi: 10.1093/mnras/stab2039

  106. [119]

    A., De Marco, O., Iaconi, R., Chamandy, L., & Price, D

    Reichardt, T. A., De Marco, O., Iaconi, R., Chamandy, L., & Price, D. J. 2020, MNRAS, 494, 5333, doi: 10.1093/mnras/staa937

  107. [120]

    1977, A&A, 61, 217

    Reimers, D. 1977, A&A, 61, 217

  108. [121]

    J., Rebassa-Mansergas, A., Luo, A

    Ren, J. J., Rebassa-Mansergas, A., Luo, A. L., et al. 2014, A&A, 570, A107, doi: 10.1051/0004-6361/201423689

  109. [122]

    B., Kerr, R., Heyl, J., et al

    Richer, H. B., Kerr, R., Heyl, J., et al. 2019, ApJ, 880, 75, doi: 10.3847/1538-4357/ab2874

  110. [123]

    B., Caiazzo, I., Du, H., et al

    Richer, H. B., Caiazzo, I., Du, H., et al. 2021, ApJ, 912, 165, doi: 10.3847/1538-4357/abdeb7

  111. [124]

    M., & Taam, R

    Ricker, P. M., & Taam, R. E. 2012, ApJ, 746, 74, doi: 10.1088/0004-637X/746/1/74

  112. [125]

    W., et al

    Riley, J., Agrawal, P., Barrett, J. W., et al. 2022, ApJS, 258, 34, doi: 10.3847/1538-4365/ac416c

  113. [126]

    Roming, P. W. A., Kennedy, T. E., Mason, K. O., et al. 2005, SSRv, 120, 95, doi: 10.1007/s11214-005-5095-4 R¨ opke, F. K., & De Marco, O. 2023, LRCA, 9, 2, doi: 10.1007/s41115-023-00017-x

  114. [127]

    T., et al

    Sahu, S., B´ edard, A., G¨ ansicke, B. T., et al. 2025, Nature Astronomy, 9, 1347, doi: 10.1038/s41550-025-02590-y Santos-Garc ´ ıa, A., Torres, S., Rebassa-Mansergas, A., &

  115. [128]

    Brown, A. J. 2025, A&A, 695, A161, doi: 10.1051/0004-6361/202452989 Linking Pre/Post-CE Binary Properties with Star Clusters29

  116. [129]

    Scargle, J. D. 1982, ApJ, 263, 835, doi: 10.1086/160554

  117. [130]

    2023, MNRAS, 518, 3966, doi: 10.1093/mnras/stac3313

    Scherbak, P., & Fuller, J. 2023, MNRAS, 518, 3966, doi: 10.1093/mnras/stac3313

  118. [131]

    Schneider, F. R. N., Lau, M. Y. M., & Roepke, F. K. 2025, arXiv e-prints, arXiv:2502.00111, doi: 10.48550/arXiv.2502.00111

  119. [132]

    R., & G¨ ansicke, B

    Schreiber, M. R., & G¨ ansicke, B. T. 2003, A&A, 406, 305, doi: 10.1051/0004-6361:20030801 Science Software Branch at STScI. 2012, PyRAF: Python alternative for IRAF,, Astrophysics Source Code Library, record ascl:1207.011

  120. [133]

    2024, MNRAS, 529, 3729, doi: 10.1093/mnras/stae773

    Shahaf, S., Hallakoun, N., Mazeh, T., et al. 2024, MNRAS, 529, 3729, doi: 10.1093/mnras/stae773

  121. [134]

    2026, PASP, 138, 034202, doi: 10.1088/1538-3873/ae453b

    Shariat, C., & El-Badry, K. 2026, PASP, 138, 034202, doi: 10.1088/1538-3873/ae453b

  122. [135]

    M., Foley, R

    Silverman, J. M., Foley, R. J., Filippenko, A. V., et al. 2012, MNRAS, 425, 1789, doi: 10.1111/j.1365-2966.2012.21270.x

  123. [136]

    M., Hawley, S

    Silvestri, N. M., Hawley, S. L., West, A. A., et al. 2006, AJ, 131, 1674, doi: 10.1086/499494

  124. [137]

    F., Cutri, R

    Skrutskie, M. F., Cutri, R. M., Stiening, R., et al. 2006, AJ, 131, 1163, doi: 10.1086/498708

  125. [138]

    Stauffer, J. R. 1987, AJ, 94, 996, doi: 10.1086/114533

  126. [139]

    2014, MNRAS, 445, 4287, doi: 10.1093/mnras/stu2029

    Tang, J., Bressan, A., Rosenfield, P., et al. 2014, MNRAS, 445, 4287, doi: 10.1093/mnras/stu2029

  127. [140]

    M., & van den Heuvel, E

    Tauris, T. M., & van den Heuvel, E. P. J. 2006, in Cambridge Astrophysics Series, Vol. 39, Compact Stellar X-ray Sources, ed. W. Lewin & M. van der Klis (Cambridge: Cambridge University Press), 623–665, doi: 10.1017/CBO9780511536281.015

  128. [141]

    M., & van den Heuvel, E

    Tauris, T. M., & van den Heuvel, E. P. J. 2023, Physics of Binary Star Evolution: From Stars to X-ray Binaries and Gravitational Wave Sources (Princeton: Princeton University Press)

  129. [142]

    D., Toonen, S., Zapartas, E., Justham, S., & G¨ ansicke, B

    Temmink, K. D., Toonen, S., Zapartas, E., Justham, S., & G¨ ansicke, B. T. 2020, A&A, 636, A31, doi: 10.1051/0004-6361/201936889

  130. [143]

    1986, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol

    Tody, D. 1986, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 627, Instrumentation in astronomy VI, ed. D. L. Crawford, 733, doi: 10.1117/12.968154

  131. [144]

    1993, in Astronomical Society of the Pacific Conference Series, Vol

    Tody, D. 1993, in Astronomical Society of the Pacific Conference Series, Vol. 52, Astronomical Data Analysis Software and Systems II, ed. R. J. Hanisch, R. J. V. Brissenden, & J. Barnes, 173

  132. [145]

    L., Stubbs, C

    Tonry, J. L., Stubbs, C. W., Lykke, K. R., et al. 2012, ApJ, 750, 99, doi: 10.1088/0004-637X/750/2/99

  133. [146]

    T., & T., B

    Toonen, S., Hollands, M., G¨ ansicke, B. T., & T., B. 2017, A&A, 602, A16, doi: 10.1051/0004-6361/201629978

  134. [147]

    2013, A&A, 557, A87, doi: 10.1051/0004-6361/201321753

    Toonen, S., & Nelemans, G. 2013, A&A, 557, A87, doi: 10.1051/0004-6361/201321753

  135. [148]

    2025, A&A, 698, A173, doi: 10.1051/0004-6361/202554039

    Torres, S., Gili, M., Rebassa-Mansergas, A., et al. 2025, A&A, 698, A173, doi: 10.1051/0004-6361/202554039

  136. [149]

    E., Bergeron, P., & Gianninas, A

    Tremblay, P. E., Bergeron, P., & Gianninas, A. 2011, ApJ, 730, 128, doi: 10.1088/0004-637X/730/2/128

  137. [150]

    R., Speagle, J

    Van-Lane, P. R., Speagle, J. S., Eadie, G. M., et al. 2025, ApJ, 986, 59, doi: 10.3847/1538-4357/adcd73 Van Rossum, G., & Drake, F. L. 2009, Python 3 Reference Manual (Scotts Valley, CA: CreateSpace)

  138. [151]

    A., & Horne, K

    Wade, R. A., & Horne, K. 1988, ApJ, 324, 411, doi: 10.1086/165905

  139. [152]

    Wagg, T., & Broekgaarden, F. S. 2024, arXiv e-prints, arXiv:2406.04405. https://arxiv.org/abs/2406.04405

  140. [153]

    1995, Cambridge Astrophysics Series, Vol

    Warner, B. 1995, Cambridge Astrophysics Series, Vol. 28, Cataclysmic Variable Stars (Cambridge: Cambridge University Press)

  141. [154]

    Webbink, R. F. 1984, ApJ, 277, 355, doi: 10.1086/161701

  142. [155]

    Y., Speagle, J

    Wen, R. Y., Speagle, J. S., Webb, J. J., & Eadie, G. M. 2024, MNRAS, 527, 4193, doi: 10.1093/mnras/stad3536

  143. [156]

    2000, A&AS, 143, 9, doi: 10.1051/aas:2000332 Wes McKinney

    Wenger, M., Ochsenbein, F., Egret, D., et al. 2000, A&AS, 143, 9, doi: 10.1051/aas:2000332 Wes McKinney. 2010, in Proceedings of the 9th Python in Science Conference, ed. St´ efan van der Walt & Jarrod Millman, 56 – 61, doi: 10.25080/Majora-92bf1922-00a

  144. [157]

    C., & Nordhaus, J

    Wilson, E. C., & Nordhaus, J. 2019, MNRAS, 485, 4492, doi: 10.1093/mnras/stz601

  145. [158]

    C., & Nordhaus, J

    Wilson, E. C., & Nordhaus, J. 2020, MNRAS, 497, 1895, doi: 10.1093/mnras/staa2088

  146. [159]

    C., & Nordhaus, J

    Wilson, E. C., & Nordhaus, J. 2022, MNRAS, 516, 2189, doi: 10.1093/mnras/stac2300

  147. [160]

    R., et al

    Yamaguchi, N., El-Badry, K., Rees, N. R., et al. 2024a, PASP, 136, 084202, doi: 10.1088/1538-3873/ad6809

  148. [161]

    2025, arXiv e-prints, arXiv:2505.14786, doi: 10.48550/arXiv.2505.14786

    Yamaguchi, N., El-Badry, K., & Shahaf, S. 2025, arXiv e-prints, arXiv:2505.14786, doi: 10.48550/arXiv.2505.14786

  149. [162]

    2024b, MNRAS, 527, 11719, doi: 10.1093/mnras/stad4005

    Yamaguchi, N., El-Badry, K., Fuller, J., et al. 2024b, MNRAS, 527, 11719, doi: 10.1093/mnras/stad4005

  150. [163]

    2026, ApJS, 284, 38, doi: 10.3847/1538-4365/ae5bc2

    Yang, M., Yuan, H., Yang, X., et al. 2026, ApJS, 284, 38, doi: 10.3847/1538-4365/ae5bc2

  151. [164]

    Young, A., & Capps, R. W. 1971, ApJL, 166, L81, doi: 10.1086/180744

  152. [165]

    B., Liu, X

    Yuan, H. B., Liu, X. W., & Xiang, M. S. 2013, MNRAS, 430, 2188, doi: 10.1093/mnras/stt039

  153. [166]

    2022, MNRAS, 513, 3587, doi: 10.1093/mnras/stac1137

    Zorotovic, M., & Schreiber, M. 2022, MNRAS, 513, 3587, doi: 10.1093/mnras/stac1137

  154. [167]

    R., G¨ ansicke, B

    Zorotovic, M., Schreiber, M. R., G¨ ansicke, B. T., & Nebot G´ omez-Mor´ an, A. 2010, A&A, 520, A86, doi: 10.1051/0004-6361/200913658 30Grondin et al. APPENDIX A.SUMMARY OF OBSER V ATIONS Here, we summarize the spectroscopic and photometric observations of Alessi12-PCE. Table ...

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