The White Dwarf Pareto: Tracing Mass Loss in Binary Systems

TL;DR

This paper introduces a new method using a Pareto distribution to analyze how binary interactions influence white dwarf masses, revealing significant mass loss and differences from isolated stars.

Contribution

It presents a novel application of a truncated Pareto profile to constrain white dwarf populations and their evolutionary history in binary systems.

Findings

White dwarfs in these binaries are ~20% less massive than isolated ones.

Progenitors lost 80-85% of their mass, with binary interactions increasing mass loss.

Typical white dwarf mass in the sample is ~0.55 Msun.

Abstract

The white dwarf mass distribution has been studied primarily at two extremes: objects that presumably evolved as single stars and members of close binaries that likely underwent substantial interaction. This work considers the intermediate separation regime of ~1 au and demonstrates how binary interaction affects white dwarf masses. The binary mass ratio distribution is utilized for this purpose. Modeled as a truncated Pareto profile, this distribution provides insights into the populations' properties and evolutionary history. When applied to homogeneous samples of binaries with giant primaries of similar age, the distribution's shape constrains the fraction of white dwarf companions, the white dwarf mass distribution, and the properties of their progenitors. As a test case, this method is applied to a small spectroscopic sample of binaries in open clusters with red giant primaries and orbital periods between 0.5 and 20 years. The analysis reveals that white dwarfs in these systems are ~20% less massive than their isolated counterparts, with a typical mass of ~0.55 Msun. Their progenitors likely lost 80-85% of their mass, with binary interactions enhancing mass loss by an additional ~0.2 Msun. These findings highlight the utility of this approach for studying binary evolution and improving population models, particularly with future datasets from Gaia and other large-scale surveys.