Sulphur monoxide emission tracing an embedded planet in the HD 100546 protoplanetary disk
Authors: Alice S. Booth, John D. Ilee, Catherine Walsh, Mihkel Kama, Luke Keyte, Ewine F. van Dishoeck, Hideko Nomura
Abstract: Molecular line observations are powerful tracers of the physical and chemical conditions across the different evolutionary stages of star, disk and planet formation. Using the high angular resolution and unprecedented sensitivity of the Atacama Large Millimeter Array (ALMA) there is now a drive to detect small-scale gas structures in protoplanetary disks that can be attributed directly to forming planets. We report high angular resolution ALMA Band 7 observations of sulphur monoxide (SO) in the nearby planet-hosting disk around Herbig star HD 100546. SO is rarely detected in evolved protoplanetary disks but in other environments, it is most often utilised as a tracer of shocks. The SO emission from the HD 100546 disk is primarily originating from gas within the approx. 20 au mm-dust cavity and shows a clear azimuthal brightness asymmetry of a factor of 2. In addition, we see a significant difference in the line profile shape when comparing these new Cycle 7 data to Cycle 0 data of the same SO transitions. We discuss the different physical/chemical mechanisms that could be responsible for this asymmetry and time variability including disk winds, disk warps, and a shock triggered by a (forming) planet. We propose that the SO is enhanced in the cavity due to the presence of a giant planet. The SO asymmetry complements evidence for hot circumplanetary material around the giant planet HD 100546 c traced via CO ro-vibrational emission. This work sets the stage for further observational and modelling efforts to detect and understand the chemical imprint of a forming planet on its parent disk.
Explore the paper tree
Click on the tree nodes to be redirected to a given paper and access their summaries and virtual 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.