Discerning the Form of the Dense Core Mass Function

TL;DR

This study evaluates whether the observed mass function of dense cores in star-forming regions is better described by a lognormal or powerlaw form, highlighting the limitations of current data and the importance of dataset size and parameters.

Contribution

The paper introduces a comprehensive analysis method to distinguish between lognormal and powerlaw forms of the core mass function using simulated and real data, emphasizing dataset size requirements.

Findings

Current data cannot definitively distinguish between the two forms.

Datasets with over 500 cores are needed for reliable discrimination.

The width of the core mass function is more reliably estimated than the high-mass tail slope.

Abstract

We investigate the ability to discern between lognormal and powerlaw forms for the observed mass function of dense cores in star forming regions. After testing our fitting, goodness-of-fit, and model selection procedures on simulated data, we apply our analysis to 14 datasets from the literature. Whether the core mass function has a powerlaw tail or whether it follows a pure lognormal form cannot be distinguished from current data. From our simulations it is estimated that datasets from uniform surveys containing more than approximately 500 cores with a completeness limit below the peak of the mass distribution are needed to definitively discern between these two functional forms. We also conclude that the width of the core mass function may be more reliably estimated than the powerlaw index of the high mass tail and that the width may also be a more useful parameter in comparing with the stellar initial mass function to deduce the statistical evolution of dense cores into stars.