ALMA Observations of the HD~110058 debris disk

Authors: Antonio S. Hales, SebastiÁn Marino, Patrick D. Sheehan, Silvio Ulloa, SebastiÁn PÉrez, Luca MatrÀ, Quentin Kral, Mark Wyatt, William Dent, John Carpenter

arXiv: 2210.12275v1 - DOI (astro-ph.SR)
License: CC BY 4.0

Abstract: We present Atacama Large Millimeter Array (ALMA) observations of the young, gas-rich debris disk around HD110058 at 0.3-0.6\arcsec resolution. The disk is detected in the 0.85 and 1.3~mm continuum, as well as in the J=2-1 and J=3-2 transitions of $^{12}$CO and $^{13}$CO. The observations resolve the dust and gas distributions and reveal that this is the smallest debris disk around stars of similar luminosity observed by ALMA. The new ALMA data confirm the disk is very close to edge-on, as shown previously in scattered light images. We use radiative transfer modeling to constrain the physical properties of dust and gas disks. The dust density peaks at around 31~au and has a smooth outer edge that extends out to $\sim70$~au. Interestingly, the dust emission is marginally resolved along the minor axis, which indicates that it is vertically thick if truly close to edge-on with an aspect ratio between 0.13 and 0.28. We also find that the CO gas distribution is more compact than the dust \ah{(similarly to the disk around 49 Ceti)}, which could be due to a low viscosity and a higher gas release rate at small radii. Using simulations of the gas evolution taking into account the CO photodissociation, shielding, and viscous evolution, we find that HD~110058's CO gas mass and distribution are consistent with a secondary origin scenario. Finally, we find that the gas densities may be high enough to cause the outward drift of small dust grains in the disk.

Submitted to arXiv on 21 Oct. 2022

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.