Born Dry or Born Wet? A Palette of Water Growth Histories in TRAPPIST-1 Analogs and Compact Planetary Systems

Authors: Howard Chen, Matthew S. Clement, Le-Chris Wang, Jesse T. Gu

Chen, H., Clement, M. S., Wang, L. C., & Gu, J. T. 2025, ApJL, 991, L11
arXiv: 2510.12794v1 - DOI (astro-ph.EP)
21 pages, 7 figures, 3 tables, published in the Astrophysical Journal Letters
License: CC BY 4.0

Abstract: It is still unclear whether exoplanets in compact multiplanet systems such as TRAPPIST-1 are able to accrete large quantities of volatiles, grow to sufficient mass, and maintain robust atmospheres and hydrospheres. Previous estimates of water content in M-dwarf systems have largely relied on population synthesis or atmosphere-interior evolution models, often treating impacts and atmospheric loss in isolation. In this work, we couple impact delivery, impact erosion, and mantle-atmosphere exchange within a model that tracks volatile evolution through stochastic collision histories. By explicitly including both planetesimal accretion and the prolonged luminous pre-main-sequence phase of M dwarfs, we find lower water inventories for the inner TRAPPIST-1 analogs (b-e), spanning only $10^{-4}$-$10^{-2} M_{\oplus,\rm ocn}$ across a wide range of disk structures and impact scenarios. By contrast, the outer planets (f-h analogs) frequently retain water inventories exceeding an Earth ocean mass. This systematic volatile gradient provides a physically motivated explanation for JWST's nondetections of atmospheres on TRAPPIST-1 b and c, implying an origin rooted in formation conditions rather than in post-formation escape. Our results suggest that many rocky planets in compact M-dwarf systems may form already depleted in volatile compounds, fundamentally limiting their capacity to sustain atmospheres or surface oceans. More broadly, our multistage framework for volatile tracking can help interpret future observations of compact systems and set more realistic initial conditions for exoplanet interior compositions and atmospheric models.

Submitted to arXiv on 14 Oct. 2025

Explore the paper tree

Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant

Also access our AI generated Summaries, or ask questions about this paper to our AI assistant.

Beta

Look for similar papers (in beta version)

By clicking on the button above, our algorithm compares the title and abstract of this paper with all the papers of the same arXiv category that we have summarized, and finds the closest ones. You can rerun it from time to time: the results improve as our database grows.