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ABSTRACT A large fraction of white dwarfs (WDs) have metal-polluted atmospheres, which are produced by accreting material from remnant planetary systems. The composition of the accreted debris broadly resembles that of rocky Solar system objects. Volatile-enriched debris with compositions similar to long-period comets (LPCs) is rarely observed. We attempt to reconcile this dearth of volatiles with the premise that exo-Oort clouds (XOCs) occur around a large fraction of planet-hosting stars. We estimate the comet accretion rate from an XOC analytically, adapting the ‘loss cone’ theory of LPC delivery in the Solar system. We investigate the dynamical evolution of an XOC during late stellar evolution. Using numerical simulations, we show that 1–30 per cent of XOC objects remain bound after anisotropic stellar mass-loss imparting a WD natal kick of $${\sim}1 \, {\rm km \, s^{-1}}$$. We also characterize the surviving comets’ distribution function. Surviving planets orbiting a WD can prevent the accretion of XOC comets by the star. A planet’s ‘dynamical barrier’ is effective at preventing comet accretion if the energy kick imparted by the planet exceeds the comet’s orbital binding energy. By modifying the loss cone theory, we calculate the amount by which a planet reduces the WD’s accretion rate. We suggest that the scarcity of volatile-enriched debris in polluted WDs is caused by an unseen population of 10–$$100 \, \mathrm{au}$$ scale giant planets acting as barriers to incoming LPCs. Finally, we constrain the amount of volatiles delivered to a planet in the habitable zone of an old, cool WD.
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Hunting for Polluted White Dwarfs and Other Treasures with Gaia XP Spectra and Unsupervised Machine Learning
Abstract White dwarfs (WDs) polluted by exoplanetary material provide the unprecedented opportunity to directly observe the interiors of exoplanets. However, spectroscopic surveys are often limited by brightness constraints, and WDs tend to be very faint, making detections of large populations of polluted WDs difficult. In this paper, we aim to increase considerably the number of WDs with multiple metals in their atmospheres. Using 96,134 WDs with Gaia DR3 BP/RP (XP) spectra, we constructed a 2D map using an unsupervised machine-learning technique called Uniform Manifold Approximation and Projection (UMAP) to organize the WDs into identifiable spectral regions. The polluted WDs are among the distinct spectral groups identified in our map. We have shown that this selection method could potentially increase the number of known WDs with five or more metal species in their atmospheres by an order of magnitude. Such systems are essential for characterizing exoplanet diversity and geology.
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- PAR ID:
- 10528986
- Publisher / Repository:
- DOI PREFIX: 10.3847
- Date Published:
- Journal Name:
- The Astrophysical Journal
- Volume:
- 970
- Issue:
- 2
- ISSN:
- 0004-637X
- Format(s):
- Medium: X Size: Article No. 181
- Size(s):
- Article No. 181
- Sponsoring Org:
- National Science Foundation
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