“…The most important tool of TDA is the persistent homology method [12,13], which is proven as useful in many real-world applications. The abundance of applications covers a broad range of phenomena in biological and medical science, like breast cancer research [14], brain science [15][16][17][18][19][20][21], biomolecules [22][23][24], evolution [25] and bacteria [26], followed by the applications in sensor networks [27,28], signal analysis [29], image processing [30], musical data [31], text mining [32], phase space reconstruction of dynamical systems [33,34], as well as complex networks related to either dynamics taking place on networks [35] or structural properties [36,37].…”