Search arXivSearch

arXiv · 2112.12623

The origin of the high metallicity of close-in giant exoplanets II The nature of the sweet spot for accretion

Abstract

The composition of giant planets reflects their formation history. Planetesimal accretion during the phase of planetary migration could lead to the delivery of heavy elements into giant planets. In our previous paper (Shibata et al. 2020) we showed that planetesimal accretion during planetary migration occurs in a rather narrow region of the protoplanetary disk, which we refer as "the sweet spot for accretion". The goal of this paper is to reveal the nature of the sweet spot and investigate the role of the sweet spot in determining the composition of gas giant planets. We analytically derive the required conditions for the sweet spot. Then, we compare the derived equations with the numerical simulations. We find that the conditions required for the sweet spot can be expressed by the ratio of the gas damping timescale of the planetesimal orbits and the planetary migration timescale. If the planetary migration timescale depends on the surface density of disk gas inversely, the location of the sweet spot does not change with the disk evolution. The mass of planetesimals accreted by the planet depends on the amount of planetesimals that are shepherded by mean motion resonances. Our analysis suggests that tens Earth-mass of planetesimals can be shepherded into the sweet spot without planetesimal collisions. However, as more planetesimals are trapped into mean motion resonances, collisional cascade can lead to fragmentation of planetesimals. This could affect the location of the sweet spot and the population of small objects in planetary systems. We conclude that the composition of gas giant planets depends on whether the planets crossed the sweet spot during their formation. Constraining the metallicity of cold giant planets, that are expected to be outer than the sweet spot, would reveal key information for understanding the origin of heavy elements in giant planets.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sho Shibata, Ravit Helled, Masahiro Ikoma. 2021-12-23. The origin of the high metallicity of close-in giant exoplanets II The nature of the sweet spot for accretion. https://doi.org/10.1051/0004-6361%2F202142180

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Strict Limits on Helium Absorption from LHS 1140 b from Four JWST NIRISS Transits

Orbiting in the habitable zone of its host star, the 1.7 $R_\oplus$, 5.6 $M_\oplus$ planet LHS 1140 b is a target of great interest. Recently Cherubim et al. (2026) published a detection of metastable He escaping from the atmosphere of LHS 1140 b, simultaneously providing the first concrete inference of an atmosphere on this planet and indicating that the atmosphere is He-rich and H-poor as would be expected due to Gyrs of fractionated mass loss. In this work, we analyze four archival transits of LHS 1140 b, spanning Dec 2023 to Jul 2026, taken with the NIRISS instrument on JWST, for evidence of He absorption. Each of the four visits disfavours the presence of He absorption compared to a flat continuum with odds ratios ranging from 3.9--11.6:1. He absorption with an amplitude and width equivalent to that observed by Cherubim et al. (2026) is strongly ruled out by the data with odds ratios from 300--8.6$\times$10$^4$:1 compared to a flat continuum --- though it should be noted that none of the JWST transits are contemporaneous with the Cherubim et al. (2026) detection. We also fit the absolute out-of-transit stellar spectra from these four visits, as well as an additional JWST NIRISS transit of planet c, to search for evidence of stellar variability, but find consistent photosphere and herterogeneity parameters in all five datasets. In all, our work provides a set of strict limits on He escape from LHS 1140 b that will be valuable to future studies into the nature and evolution of this intriguing world.

astro-ph.EP

Bridging magnetothermal winds and photoevaporation to model discs dispersal

Protoplanetary disc dispersal is driven by two processes usually modelled separately: photoevaporative and magnetohydrodynamic (MHD) disc winds. Global simulations indicate that in the inner disc these are not distinct outflows but a single magnetothermal wind. We assemble a closed-form, two-phase model that respects it. A single-field-line wind, whose base is fixed by the irradiated temperature and penetration column, supplies the launch and feeds a secular evolution, with photoevaporation convolved on as a sink. The flux closure $B_z\proptoΣ^q$ is self-limiting: for $q\le1/2$ depletion alone cannot demagnetise the disc, so dispersal requires independent flux loss, parameterised by the magnetic Reynolds number $\mathcal{R}_m$. Integrating the coupled system yields two regimes. Efficient flux loss ($\mathcal{R}_m\lesssim1$) lets the magnetisation front recede by over an order of magnitude and opens a photoevaporative gap. Flux retention ($\mathcal{R}_m\gg1$) drives the front outward, sustains accretion, and defers dispersal by $\approx2.7$~Myr. Deriving the base from stellar irradiation instead of prescribing it, we find that the cold-launch approximation is valid during the early stages of disc evolution: anchoring the base at plasma equipartition ($β_{\rm base} \sim 1$) confines irradiation's influence on the magnetic lever arm to the magnetothermal annulus, decoupling the peak accretion rate from the incident flux. Both regimes clear the disc inside-out, through either a photoevaporatively amplified cavity wall or an expanding magnetothermal front.

astro-ph.EP

Faithful Neural Embeddings for 3D Exoplanet Climate Modeling

With the rapid advancement of telescopes like JWST and Ariel, there is an urgent need for efficient 3D climate models to interpret observations of exoplanet atmospheres. Traditional 3D general circulation models (GCMs) are computationally intensive, prompting the development of machine learning (ML) emulators to accelerate simulations. Recent work, such as that by Plaschzug et al. 2026 \cite{plaschzug2026accelerating}, uses a dense neural network (DNN) to predict local gas temperatures and winds from input parameters, including local gas pressure, spatial coordinates (longitude and latitude), and global temperature. However, this model relies on predicting individual temperature values (points) at specific grid points, which can be limited by the resolution and constraints of the training grid. In this work, we investigate a couple of alternative frameworks based on latent-space representations of local gas temperature ($\text{T}_{\text{gas}}$) to obtain a faithful, low-dimensional representation of these profiles. This represents the first step toward developing a latent space regression model, offering a structurally cohesive alternative to the existing point-wise prediction method \cite{plaschzug2026accelerating}. By capturing the optimal embedding space of atmospheric data, our proposed framework can produce simulated profiles while maintaining computational efficiency, making it suitable for large-scale exoplanet ensemble studies.

astro-ph.EP