Core Formation, Coherence and Collapse: A New Core Evolution Paradigm
  Revealed by Machine Learning
  We study the formation, evolution and collapse of dense cores by tracking
density structures in a magnetohydrodynamic (MHD) simulation. We identify cores
using the dendrogram algorithm and utilize machine learning techniques,
including principal component analysis (PCA) and the k-means clustering
algorithm to analyze the full density and velocity dispersion profiles of these
cores. We find that there exists an evolutionary sequence consisting of three
distinct phases: i) the formation of turbulent density structures (Phase I),
ii) the dissipation of turbulence and the formation of coherent cores (Phase
II), and iii) the transition to protostellar cores through gravitational
collapse (Phase III). In dynamically evolving molecular clouds, the existence
of these three phases corresponds to the coexistence of three populations of
cores with distinct physical properties. The prestellar and protostellar cores
frequently analyzed in previous studies of observations and simulations belong
to the last phase in this evolutionary picture. We derive typical lifetimes of
1.4$\pm$1.0$\times$10$^5$ yr, 3.3$\pm$1.4$\times$10$^5$ yr and
3.3$\pm$1.4$\times$10$^5$ yr, respectively for Phase I, II and III. We find
that cores can form from both converging flows and filament fragmentation and
that cores may form both inside and outside the filaments. We then compare our
results to previous observations of coherent cores and provide suggestions for
future observations to study cores belonging to the three phases.
