The SOFIA Massive (SOMA) Star Formation Survey. IV. Isolated Protostars

TL;DR

This study uses SOFIA-FORCAST imaging and radiative transfer modeling to analyze isolated protostars, revealing their properties and environmental conditions, and providing tools for future spectral energy distribution analysis.

Contribution

It introduces an automated method and the sedcreator Python package for constructing and fitting protostellar SEDs within the turbulent core accretion framework.

Findings

Protostars form across a wide range of clump surface densities.

Higher surface densities correlate with increased star formation efficiency.

No significant IR variability observed over 40 years.

Abstract

We present $\sim10-40\,\mu$m SOFIA-FORCAST images of 11 isolated protostars as part of the SOFIA Massive (SOMA) Star Formation Survey, with this morphological classification based on 37 $\mu$m imaging. We develop an automated method to define source aperture size using the gradient of its background-subtracted enclosed flux and apply this to build spectral energy distributions (SEDs). We fit the SEDs with radiative transfer models, developed within the framework of turbulent core accretion (TCA) theory, to estimate key protostellar properties. Here, we release the sedcreator python package that carries out these methods. The SEDs are generally well fitted by the TCA models, from which we infer initial core masses $M_c$ ranging from $20-430\:M_\odot$, clump mass surface densities $\Sigma_{\rm cl}\sim0.3-1.7\:{\rm{g\:cm}}^{-2}$ and current protostellar masses $m_*\sim3-50\:M_\odot$. From a uniform analysis of the 40 sources in the full SOMA survey to date, we find that massive protostars form across a wide range of clump mass surface density environments, placing constraints on theories that predict a minimum threshold $\Sigma_{\rm cl}$ for massive star formation. However, the upper end of the $m_*-\Sigma_{\rm cl}$ distribution follows trends predicted by models of internal protostellar feedback that find greater star formation efficiency in higher $\Sigma_{\rm cl}$ conditions. We also investigate protostellar far-IR variability by comparison with IRAS data, finding no significant variation over an $\sim$40 year baseline.