Local Laplacian: theory and models for data analysis
This paper introduces the persistent local Laplacian formalism, a theoretically grounded and highly parallelizable framework that overcomes the sensitivity and scalability limitations of traditional topological data analysis by establishing a generalized persistent Hodge isomorphism and unitary equivalence to efficiently extract fine-grained local structural signatures from large-scale datasets.