Observing Simulated Protostars with Outflows: How Accurate are Protostellar Properties Inferred from SEDs?
Stella S. R. Offner, Thomas P. Robitaille, Charles E. Hansen,, Christopher F. McKee, and Richard I. Klein

TL;DR
This study assesses the accuracy of protostellar properties inferred from SED fitting by comparing synthetic observations from detailed star formation simulations with radiative transfer modeling, revealing significant discrepancies and limitations.
Contribution
It provides a comprehensive evaluation of the reliability of SED-based protostellar property inference using realistic simulations and advanced radiative transfer post-processing.
Findings
SED models correctly identify evolutionary stages
Discrepancies in disk and stellar parameters are common
Complex gas morphology affects classification and parameter accuracy
Abstract
The properties of unresolved protostars and their local environment are frequently inferred from spectral energy distributions (SEDs) using radiative transfer modeling. We perform synthetic observations of realistic star formation simulations to evaluate the accuracy of properties inferred from fitting model SEDs to observations. We use ORION, an adaptive mesh refinement (AMR) three-dimensional gravito-radiation-hydrodynamics code, to simulate low-mass star formation in a turbulent molecular cloud including the effects of protostellar outflows. To obtain the dust temperature distribution and SEDs of the forming protostars, we post-process the simulations using HYPERION, a state-of-the-art Monte-Carlo radiative transfer code. We find that the ORION and HYPERION dust temperatures typically agree within a factor of two. We compare synthetic SEDs of embedded protostars for a range of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
