Two-size approximation: a simple way of treating the evolution of grain size distribution in galaxies

TL;DR

This paper introduces a two-size approximation model for galaxy dust evolution, simplifying complex grain size distribution calculations while accurately capturing key features and enabling efficient predictions of dust properties.

Contribution

The paper presents a novel, simplified two-size grain model that reproduces detailed grain size evolution features with less computational effort.

Findings

The model accurately reproduces grain size distribution features.

It predicts the timing of dust growth phases.

It efficiently estimates observational dust properties.

Abstract

Full calculations of the evolution of grain size distribution in galaxies are in general computationally heavy. In this paper, we propose a simple model of dust enrichment in a galaxy with a simplified treatment of grain size distribution by imposing a `two-size approximation'; that is, all the grain population is represented by small (grain radius a < 0.03 micron) and large (a > 0.03 micron) grains. We include in the model dust supply from stellar ejecta, destruction in supernova shocks, dust growth by accretion, grain growth by coagulation and grain disruption by shattering, considering how these processes work on the small and large grains. We show that this simple framework reproduces the main features found in full calculations of grain size distributions as follows. The dust enrichment starts with the supply of large grains from stars. At a metallicity level referred to as the critical metallicity of accretion, the abundance of the small grains formed by shattering becomes large enough to rapidly increase the grain abundance by accretion. Associated with this epoch, the mass ratio of the small grains to the large grains reaches the maximum. After that, this ratio converges to the value determined by the balance between shattering and coagulation, and the dust-to-metal ratio is determined by the balance between accretion and shock destruction. With a Monte Carlo simulation, we demonstrate that the simplicity of our model has an advantage in predicting statistical properties. We also show some applications for predicting observational dust properties such as extinction curves.