Search arXivSearch

arXiv · 2007.05138

Comet 41P/Tuttle-Giacobini-Kresak, 45P/Honda-Mrkos-Pajdusakova, and 46P/Wirtanen: Water Production Activity over 21 Years with SOHO/SWAN

Abstract

In 2017, 2018 and 2019, comets 46P/Wirtanen, 45P/Honda-Mrkos-Pajdusakova, and 41P/Tuttle-Giacobini-Kresak all had perihelion passages. Their hydrogen comae were observed by the Solar Wind ANisotropies (SWAN) all-sky hydrogen Lyman-alpha Camera on the SOlar and Heliospheric Observer (SOHO) satellite: comet 46P for the fourth time and comets 45P and 41P for the third time each since 1997. Comet 46P/Wirtanen is one of a small class of so-called hyperactive comets whose gas production rates belie their small size. This comet was the original target comet of the Rosetta mission. The Solar Wind ANisotropies (SWAN) all-sky hydrogen Lyman-alpha camera on the SOlar and Heliospheric Observer (SOHO) satellite observed the hydrogen coma of comet 46P/Wirtanen during the apparitions of 1997, 2002, 2008 and 2018. Over the 22 years, the activity decreased and its variation with heliocentric distance has changed markedly in a way very similar to that of another hyperactive comet, 103P/Hartley 2. Comet 45P/Honda-Mrkos-Pajdusakova was observed by SWAN during its perihelion apparitions of 2001, 2011 and 2017. Over this time period the activity level has remained remarkably similar, with no long-term fading or abrupt decreases. Comet 41P/Tuttle-Giacobini-Kresak was observed by SWAN in its perihelion apparitions of 2001, 2006 and 2017 and has decreased in activity markedly over the same time period. In 1973 it was known for large outbursts, which continued during the 2001 (2 outbursts) and 2006 (1 outburst) apparitions. However, over the 2001 to 2017 time period covered by the SOHO/SWAN observations the water production rates have greatly decreased by factors of 10-30 over corresponding times during its orbit.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

M. R. Combi, T. Mäkinen, J. -L. Bertaux, E. Quémerais, S. Ferron, R. Coronel. 2020-07-13. Comet 41P/Tuttle-Giacobini-Kresak, 45P/Honda-Mrkos-Pajdusakova, and 46P/Wirtanen: Water Production Activity over 21 Years with SOHO/SWAN. https://arxiv.org/abs/2007.05138

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