Papers
Topics
Authors
Recent
Search
2000 character limit reached

Interior characterization in multiplanetary systems: TRAPPIST-1

Published 6 Aug 2018 in astro-ph.EP | (1808.01803v1)

Abstract: Interior characterization traditionally relies on individual planetary properties, ignoring correlations between different planets of the same system. For multi-planetary systems, planetary data are generally correlated. This is because, the differential masses and radii are better constrained than absolute planetary masses and radii. We explore such correlations and data specific to the multiplanetary-system of TRAPPIST-1 and study their value for our understanding of planet interiors. Furthermore, we demonstrate that the rocky interior of planets in a multi-planetary system can be preferentially probed by studying the most dense planet representing a rocky interior analogue. Our methodology includes a Bayesian inference analysis that uses a Markov chain Monte Carlo scheme. Our interior estimates account for the anticipated variability in the compositions and layer thicknesses of core, mantle, water oceans and ice layers, and a gas envelope. Our results show that (1) interior estimates significantly depend on available abundance proxies and (2) that the importance of inter-dependent planetary data for interior characterization is comparable to changes in data precision by 30 %. For the interiors of TRAPPIST-1 planets, we find that possible water mass fractions generally range from 0-25 %. The lack of a clear trend of water budgets with orbital period or planet mass challenges possible formation scenarios. While our estimates change relatively little with data precision, they critically depend on data accuracy. If planetary masses varied within ~24 %, interiors would be consistent with uniform (~7 %) or an increasing water mass fractions with orbital period (~2-12 %).

Summary

No one has generated a summary of this paper yet.

Paper to Video (Beta)

No one has generated a video about this paper yet.

Whiteboard

No one has generated a whiteboard explanation for this paper yet.

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Continue Learning

We haven't generated follow-up questions for this paper yet.

Collections

Sign up for free to add this paper to one or more collections.