Identification of criticality in star formation avalanches: A theoretical investigation of disk galaxy models driven by stochastic self-propagating star formation

Abstract

Stochastic self-propagating star formation (SSPSF) is a proposed mechanism for the propagation of star formation in spiral galaxies. In this mechanism, shockwaves produced by supernova explosions from dying massive stars induce new star formation sites in the surrounding regions, possibly causing a chain reaction of star formation events — analogous to avalanches found in sandpile models and neuronal research. We reconstruct the Gerola & Seiden [Astrophys. J. 223, 129 (1978)] SSPSF cellular automata model to generate a suite of simulated differentially-rotating spiral galaxies and analyze the behavior of the star formation chains for criticality. We report a transition in the chain size and chain duration CCDFs from the subcritical to the supercritical phase when the refractory time τ_r, a parameter controlling the downtime for star formation in a cell, is varied. Furthermore, we check whether the suspected critical systems exhibit other criteria, namely: the presence of multiple power law exponents, a relationship between the power law exponents, and universal scaling. We find that all of these are satisfied for our M101 galaxy model with τ_r = 4 and M81 galaxy model with τ_r = 5, indicating that criticality exists in the SSPSF model.