BibTeX

@article{2509.01937v1,
Author        = {Jonathan P. Williams and Myriam Benisty and Christian Ginski and Giuseppe Lodato and Maria Vincent},
Title         = {Radiative Transfer Modeling of a Shadowed Protoplanetary Disk assisted
  by a Neural Network},
Eprint        = {2509.01937v1},
ArchivePrefix = {arXiv},
PrimaryClass  = {astro-ph.EP},
Abstract      = {We present observations and detailed modeling of a protoplanetary disk around
the T Tauri star, V1098 Sco. Millimeter wavelength data from the Atacama Large
Millimeter Array (ALMA) show a ring of large dust grains with a central cavity
that is filled with molecular gas. Near-infrared data with the Very Large
Telescope (VLT) detect the scattered starlight from the disk surface and reveal
a large shadow that extends over it's entire southern half. We model the ALMA
continuum and line data to determine the outer disk geometry and the central
stellar mass. Using radiative transfer models, we demonstrate that a misaligned
inner disk, tilted in both inclination and position angle with respect to the
outer disk, can reproduce the salient scattered light features seen with the
VLT. Applying an image threshold algorithm to compare disk morphologies and
training a neural network on a set of high signal-to-noise models, we forward
model the data and determine the inner disk geometry. We find that the rotation
axes of the inner and outer disks are misaligned by 38 degrees and constrain
the mass and location of a perturbing planetary or substellar companion. The
technique of simulation based inference that is illustrated here is broadly
applicable for radiative transfer modeling of other objects.},
Year          = {2025},
Month         = {Sep},
Url           = {http://arxiv.org/abs/2509.01937v1},
File          = {2509.01937v1.pdf}
}