Towards a comprehensive view of accretion, inner disks, and extinction in classical T Tauri stars: an ODYSSEUS study of the Orion OB1b association
Authors: Caeley V. Pittman, Catherine C. Espaillat, Connor E. Robinson, Thanawuth Thanathibodee, Nuria Calvet, John Wendeborn, Jesus Hernández, Carlo F. Manara, Fred Walter, Péter Ábrahám, Juan M. Alcalá, Sílvia H. P. Alencar, Nicole Arulanantham, Sylvie Cabrit, Jochen Eislöffel, Eleonora Fiorellino, Kevin France, Manuele Gangi, Konstantin Grankin, Gregory J. Herczeg, Ágnes Kóspál, Ignacio Mendigutía, Javier Serna, Laura Venuti
Abstract: The coevolution of T Tauri stars and their surrounding protoplanetary disks dictates the timescales of planet formation. In this paper, we present magnetospheric accretion and inner disk wall model fits to NUV-NIR spectra of nine classical T Tauri stars in Orion OB1b as part of the Outflows and Disks around Young Stars: Synergies for the Exploration of ULLYSES Spectra (ODYSSEUS) Survey. Using NUV-optical spectra from the Hubble UV Legacy Library of Young Stars as Essential Standards (ULLYSES) Director's Discretionary Program and optical-NIR spectra from the PENELLOPE VLT Large Programme, we find that the accretion rates of these targets are relatively high for the region's intermediate age of 5.0 Myr; rates range from $0.5-17.2 \times 10^{-8}$ M$_{\odot}$/yr, with a median value of $1.2\times 10^{-8}$ M$_{\odot}$/yr. The NIR excesses can be fit with 1200-1800 K inner disk walls located at 0.05-0.10 AU from the host stars. We discuss the significance of the choice in extinction law, as the measured accretion rate depends strongly on the adopted extinction value. This analysis will be extended to the complete sample of T Tauri stars being observed through ULLYSES to characterize accretion and inner disks in star-forming regions of different ages and stellar populations.
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.