The greedy leaf removal (GLR) procedure on a graph is an iterative removal of
any vertex with degree one (leaf) along with its nearest neighbor (root). Its
result has two faces: a residual subgraph as a core, and a set of removed
roots. While the emergence of cores on uncorrelated random graphs was solved
analytically, a theory for roots is ignored except in the case of
Erd\"{o}s-R\'{e}nyi random graphs. Here we analytically study roots on random
graphs. We further show that, with a simple geometrical interpretation and a
concise mean-field theory of the GLR procedure, we reproduce the
zero-temperature replica symmetric estimation of relative sizes of both minimal
vertex covers and maximum matchings on random graphs with or without cores.Comment: 39 pages, 5 figures, and 3 table