Quantifying topological indices in bipartite and tripartite graphs using Lyndon words and Python algorithms

Lyndon Word Representable Graphs (LWRGs) present a novel intersection between graph structures and symbolic sequences, with significant implications for chemical graph theory. This study enhances the understanding of LWRGs by deriving specific topological indices for binary and ternary core words. By linking LWRGs to topological indices, we provide new insights into the structural relationships between words and graphs. This interdisciplinary approach highlights the utility of Lyndon words in representing graph properties and underscores the relevance of topological indices in various applications, from network analysis to molecular chemistry.