Search arXivSearch

arXiv · 2411.07435

The Volatile Composition and Activity Evolution of Main-Belt Comet 358P/PANSTARRS

Abstract

We report the detection of water vapor associated with main-belt comet 358P/PANSTARRS on UT 2024 January 8-9 using the NIRSPEC instrument aboard JWST. We derive a water production rate of Q(H2O)=(5.0+/-0.2)x10^25 molecules/s, marking only the second direct detection of sublimation products of any kind from a main-belt comet, after 238P/Read. Similar to 238P, we find a remarkable absence of hypervolatile species, finding Q(CO2)<7.6x10^22 molecules/s, corresponding to Q(CO2)/Q(H2O)<0.2%. Upper limits on CH3OH and CO emission are also estimated. Photometry from ground-based observations show that the dust coma brightened and faded slowly over ~250 days in 2023-2024, consistent with photometric behavior observed in 2012-2013, but also indicate a ~2.5x decline in the dust production rate between these two periods. Dynamical dust modeling shows that the coma's morphology as imaged by JWST's NIRCAM instrument on 2023 November 22 can be reproduced by asymmetric dust emission from a nucleus with a mid-range obliquity (~80 deg) with a steady-state mass loss rate of ~0.8 kg/s. Finally, we find similar Afrho-to-gas ratios of log10(Afrho/Q(H2O))=-24.8+/-0.2 for 358P and log10(Afrho/QH2O)=-24.4+/-0.2 for 238P, suggesting that Afrho could serve as an effective proxy for estimating water production rates in other active main-belt comets. The confirmation of water vapor outgassing in both main-belt comets observed by JWST to date reinforces the use of recurrent activity near perihelion as an indicator of sublimation-driven activity in active asteroids.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Henry H. Hsieh, John W. Noonan, Michael S. P. Kelley, Dennis Bodewits, Jana Pittichova, Audrey Thirouin, Marco Micheli, Matthew M. Knight, Michele T. Bannister, Colin O. Chandler, Carrie E. Holt, Matthew J. Hopkins, Yaeji Kim, Nicholas A. Moskovitz, William J. Oldroyd, Jack Patterson, Scott S. Sheppard, Nicole Tan, Chadwick A. Trujillo, Quanzhi Ye. 2024-11-11. The Volatile Composition and Activity Evolution of Main-Belt Comet 358P/PANSTARRS. https://arxiv.org/abs/2411.07435

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