SHOCKFIND - An algorithm to identify magnetohydrodynamic shock waves in turbulent clouds

TL;DR

The paper introduces SHOCKFIND, an algorithm to identify and characterize different types of MHD shocks in turbulent molecular clouds, providing insights into shock distributions and their impact on cloud evolution.

Contribution

It presents a novel, publicly available algorithm for detecting and analyzing MHD shock families in turbulent clouds, with application to simulation data.

Findings

Both fast and slow MHD shocks are present in the simulation.

The distribution of shock Mach numbers is characterized.

Approximately 0.03% of the cloud volume is shock heated above 50 K.

Abstract

The formation of stars occurs in the dense molecular cloud phase of the interstellar medium. Observations and numerical simulations of molecular clouds have shown that supersonic magnetised turbulence plays a key role for the formation of stars. Simulations have also shown that a large fraction of the turbulent energy dissipates in shock waves. The three families of MHD shocks --- fast, intermediate and slow --- distinctly compress and heat up the molecular gas, and so provide an important probe of the physical conditions within a turbulent cloud. Here we introduce the publicly available algorithm, SHOCKFIND, to extract and characterise the mixture of shock families in MHD turbulence. The algorithm is applied to a 3-dimensional simulation of a magnetised turbulent molecular cloud, and we find that both fast and slow MHD shocks are present in the simulation. We give the first prediction of the mixture of turbulence-driven MHD shock families in this molecular cloud, and present their distinct distributions of sonic and Alfvenic Mach numbers. Using subgrid one-dimensional models of MHD shocks we estimate that ~0.03 % of the volume of a typical molecular cloud in the Milky Way will be shock heated above 50 K, at any time during the lifetime of the cloud. We discuss the impact of this shock heating on the dynamical evolution of molecular clouds.