# A modular set of synthetic spectral energy distributions for young stellar objects

## TL;DR

This paper introduces a new, flexible set of synthetic spectral energy distributions for young stellar objects, designed for initial modeling and broad parameter exploration across various evolutionary stages.

## Contribution

The paper presents a new set of simplified, wide-parameter-space SED models for YSOs, improving coverage and suitability for far-infrared and sub-mm observations, with publicly available tools.

## Key findings

- Models cover a wider range of YSO stages.
- Models are less dependent on complex parameters.
- Fitting examples demonstrate utility in real observations.

## Abstract

In this paper, I present a new set of synthetic spectral energy distributions (SEDs) for young stellar objects (YSOs) spanning a wide range of evolutionary stages, from the youngest deeply embedded protostars to pre-main-sequence stars with few or no disks. These models include significant improvements on the previous generation of published models: in particular, the new models cover a much wider and more uniform region of parameter space, do not include highly model-dependent parameters, and include a number of improvements that make them more suited to modeling far-infrared and sub-mm observations of forming stars. Rather than all being part of a single monolithic set of models, the new models are split up into sets of varying complexity. The aim of the new set of models is not to provide the most physically realistic models for young stars, but rather to provide deliberately simplified models for initial modeling, which allows a wide range of parameter space to be explored. I present the design of the model set, and show examples of fitting these models to real observations to show how the new grid design can help us better understand what can be determined from limited unresolved observations. The models, as well as a Python-based fitting tool are publicly available to the community.