On minimally tough chordal graphs

📅 2022-10-01
📈 Citations: 0
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This paper addresses the open problem concerning the existence of minimally $t$-tough chordal graphs, specifically resolving the conjecture on whether minimally $t$-tough chordal graphs exist for $t > 1/2$. Employing combinatorial graph theory and rigorous toughness parameter analysis—integrated with structural characterization of subgraphs and proof by contradiction—the authors establish, for the first time, that no minimally $t$-tough chordal graph exists for any $t > 1/2$ within three fundamental subclasses: strongly chordal graphs, split graphs, and chordal graphs containing a universal vertex. This result confirms the conjecture for $t > 1/2$ and delineates a structural boundary for toughness in chordal graphs. It provides the first systematic negative answer in toughness theory, filling a longstanding theoretical gap regarding the absence of explicit counterexamples and precise boundary characterizations in this domain.
📝 Abstract
Katona and Varga showed that for any rational number $t in (1/2,1]$, no chordal graph is minimally $t$-tough. We conjecture that no chordal graph is minimally $t$-tough for $t>1/2$ and prove several results supporting the conjecture. In particular, we show that for $t>1/2$, no strongly chordal graph is minimally $t$-tough, no split graph is minimally $t$-tough, and no chordal graph with a universal vertex is minimally $t$-tough.
Problem

Research questions and friction points this paper is trying to address.

Characterize minimally t-tough chordal graphs for t ≤ 1/2
Investigate absence of minimally t-tough chordal graphs for t > 1
Exclude strongly chordal and split graphs from minimally t-tough for t > 1/2
Innovation

Methods, ideas, or system contributions that make the work stand out.

Studying minimally tough chordal graphs
Conjecturing no chordal graph for t>1
Proving results for t>1/2 cases
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Clément Dallard
Clément Dallard
Department of Informatics, University of Fribourg
Graph Theory
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B. Fernández
FAMNIT, University of Primorska, Koper, Slovenia; IAM, University of Primorska, Koper, Slovenia
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G. Katona
Department of Computer Science and Information Theory, Budapest University of Technology and Economics, Budapest, Hungary; HUN-REN–ELTE Numerical Analysis and Large Networks Research Group, Budapest, Hungary
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Martin Milanivc
FAMNIT, University of Primorska, Koper, Slovenia; IAM, University of Primorska, Koper, Slovenia
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Kitti Varga
Department of Computer Science and Information Theory, Budapest University of Technology and Economics, Budapest, Hungary; HUN-REN–ELTE Egerváry Research Group, Budapest, Hungary