Probing multipartite entanglement through persistent homology
Gregory A. Hamilton, Felix Leditzky

TL;DR
This paper introduces a novel topological data analysis approach using persistent homology to visualize and quantify multipartite entanglement in quantum systems, providing more detailed insights than traditional measures.
Contribution
It applies persistent homology to quantum entanglement, linking topological features with entanglement measures like the n-tangle, and explores connections to entropy inequalities and resource theories.
Findings
Persistence barcodes reveal detailed entanglement structures.
Integrated Euler characteristic equals deformed interaction information.
Barcodes distinguish states with identical n-tangle.
Abstract
We propose a study of multipartite entanglement through persistent homology, a tool used in topological data analysis. In persistent homology, a 1-parameter filtration of simplicial complexes called persistence complex is used to reveal persistent topological features of the underlying data set. This is achieved via the computation of homological invariants that can be visualized as a persistence barcode encoding all relevant topological information. In this work, we apply this technique to study multipartite quantum systems by interpreting the individual systems as vertices of a simplicial complex. To construct a persistence complex from a given multipartite quantum state, we use a generalization of the bipartite mutual information called the deformed total correlation. Computing the persistence barcodes of this complex yields a visualization or `topological fingerprint' of the…
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Taxonomy
TopicsTopological and Geometric Data Analysis
