Multiple graph realizations method: improving the accuracy and the efficiency of the shortest path method through random sampling

SUMMARY We present a new implementation of the shortest path method (SPM) that calculates accurate traveltimes in arbitrarily large model spaces without requirement computational times and amounts memory, an inherent problem Dijkstra's-like algorithms. The multiple graph realizations is based upon sampling space, using numerous random graphs. performance this compared against conventional way to improve accuracy SPM, which use denser grids connectivity stencils higher order. Our results suggest although for relatively small models, single runs SPM are more suitable achieve desired accuracy, after certain level approach becomes inefficient or even unfeasible, as requirements memory time increases dramatically. On contrary our can with linear impact negligible required memory.