Asynchronous accretion can mimic diverse white dwarf pollutants II: water content

TL;DR

This study investigates how asynchronous accretion affects the inferred water content of white dwarf pollutants, revealing that observational biases can misrepresent the true composition and proposing methods to improve accuracy.

Contribution

The paper introduces a model showing how sublimation during accretion influences observed pollutant compositions and provides testable predictions for future observations.

Findings

Cooler stars more often show signs of wet pollutants.

Rare accretion events may appear to have excessive volatiles.

Current data only weakly detect water due to uncertainties.

Abstract

Volatiles, notably water, are key to the habitability of rocky planets. The presence of water in planetary material can be inferred from the atmospheric oxygen abundances of polluted white dwarfs, but this interpretation is often complex. We study the accretion process, and find that ices may sublimate and accrete before more refractory minerals reach the star. As a result, a white dwarf's relative photospheric abundances may vary with time during a single accretion event, and do not necessarily reflect the bulk composition of a pollutant. We offer two testable predictions for this hypothesis: 1. cooler stars will more often be inferred to have accreted wet pollutants, and 2. there will be rare occurrences of accretion events with inferred volatile levels far exceeding those of pristine comets. To observationally test these predictions, we statistically constrain the water content of white dwarf pollutants. We find that in the current sample, only three stars show statistically significant evidence of water at the 2$\sigma$ level, due to large typical uncertainties in atmospheric abundances and accretion states. In the future, an expanded sample of polluted white dwarfs with hydrogen-dominated atmospheres will allow for the corroboration of our theoretical predictions. Our work also shows the importance of interpreting pollutant compositions statistically, and emphasizes the requirement to reduce uncertainties on measured abundances to allow for statistically significant constraints on their water content.