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Decompositions, Tangles, and Clusters

Subject Area Theoretical Computer Science
Term from 2019 to 2024
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 414230410
 
Final Report Year 2025

Final Report Abstract

Tree decompositions, which describe how a graph can be cut into largely independent pieces, have become a standard tool in designing algorithms with applications in many different areas of computer science. Structural graph theory offers various dual concepts to tree decompositions. Intuitively, these can be viewed as describing highly connected regions in graphs. Among them, arguably, tangles are the most important. A second interesting dual characterisation can be given via search games on graphs, which are also called Cops-an-Robber games in their most popular form. The main contribution of this project was to establish a close connection between tangles and clustering. The observation of an interesting conceptual similarity between tangles and clusters goes back to Diestel and Whittle (2016) and was one of the main motivations for this project. To turn this into a mathematical theorem, a crucial idea was to relax the notion of connectivity function on a dataset and consider connectivity functions that have a property we call max-submodularity. Then, we proved that tangles derived from max-submodular connectivity functions are in one-to-one correspondence with the hierarchical clusterings of the dataset. Transferring the connection between tangles and clusterings into a more practical direction, we studied the tangles of datasets generated by mixtures of Gaussian distributions. Another contribution we made in this project concerns search games for graph decompositions that simultaneously restrict width and depth. Finally, we also contributed to investigating a novel form of decomposition, so-called radial decompositions, which drop the requirement of decompositions being tree-shaped.

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