Giant planet engulfment by evolved giant stars: light curves, asteroseismology, and survivability

Authors: Christopher E. O'Connor, Lars Bildsten, Matteo Cantiello, Dong Lai

arXiv: 2304.09882v1 - DOI (astro-ph.EP)
24 pages, 11 figures, 1 table. Submitted to AAS Journals; revised after initial review. Comments welcome

Abstract: About ten percent of Sun-like ($1$-$2 M_\odot$) stars will engulf a $1$-$10 M_{\rm J}$ planet as they expand during the red giant branch (RGB) or asymptotic giant branch (AGB) phase of their evolution. Once engulfed, these planets experience a strong drag force in the star's convective envelope and spiral inward, depositing energy and angular momentum. For these mass ratios, the inspiral takes $\sim 10$-$10^{2}$ years ($\sim 10^{2}$-$10^{3}$ orbits); the planet undergoes tidal disruption at a radius of $\sim R_\odot$. We use the Modules for Experiments in Stellar Astrophysics (MESA) software instrument to track the stellar response to the energy deposition while simultaneously evolving the planetary orbit. For RGB stars, as well as AGB stars with $M_{\rm p} \lesssim 5 M_{\rm J}$ planets, the star responds quasistatically but still brightens measurably on a timescale of years. In addition, asteroseismic indicators, such as the frequency spacing or rotational splitting, differ before and after engulfment. For AGB stars, engulfment of a $M_{\rm p} \gtrsim 5 M_{\rm J}$ planet drives supersonic expansion of the envelope, causing a bright, red, dusty eruption similar to a "luminous red nova." Based on the peak luminosity, color, duration, and expected rate of these events, we suggest that engulfment events on the AGB could be a significant fraction of low-luminosity red novae in the Galaxy. We do not find conditions where the envelope is ejected prior to the planet's tidal disruption, complicating the interpretation of short-period giant planets orbiting white dwarfs as survivors of common-envelope evolution.

Submitted to arXiv on 19 Apr. 2023

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.

Look for similar papers (in beta version)

By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.