Stellar model calibrations with the Ai Phe binary system

Open questions about the robustness of the fit

¹ Dipartimento di Fisica “Enrico Fermi”, Università di Pisa, Largo Pontecorvo 3, 56127 Pisa, Italy
e-mail: valle@df.unipi.it
² INFN, Sezione di Pisa, Largo Pontecorvo 3, 56127 Pisa, Italy

Received: 23 July 2023
Accepted: 9 September 2023

Abstract

Aims. Relying on recently available and very precise observational data for the Ai Phe binary system, we explore the robustness of the calibration of stellar models achievable with this system.

Methods. We adopt the SCEPtER pipeline with a fitting grid of stellar models computed for different initial chemical compositions and convective core overshooting efficiencies. We investigated the impact of different assumptions about the surface efficiency of microscopic diffusion, whose efficiency is still debated in the mass range of the system. We obtained the fit of this system adopting two alternative scenarios. In the reference scenario, we allowed modification of the surface metallicity due to microscopic diffusion, while in the alternative scenario we assumed that competing mixing from other sources cancels out this effect.

Results. Due to the fact that the primary star has already experienced the first dredge-up while the secondary has not, the tested scenarios show interesting differences. While the estimated age is quite robust, changing from 4.70_−0.14^+0.13 Gyr to 4.62_−0.06^+0.13 Gyr, the calibration of the convective core overshooting parameter β reveals noticeable differences. The reference scenario suggests a wide multi-modal range of possible values of β, peaking around 0.10; on the contrary the alternative scenario computations point towards a sharp and lower β, peaking around 0.04.

Conclusions. The impossibility to obtain an unambiguous fit confirms the difficulty in achieving a sensible calibration of the free parameters of stellar models using binary systems, even when very accurate masses and radii are available. The results also suggest that the biases due to the assumptions underlying the stellar track computations may be different from one binary system to another.