Exploiting Low Scanwidth to Resolve Soft Polytomies

[2511.20771] Exploiting Low Scanwidth to Resolve Soft Polytomies Skip to main content Search Submit Donate Log in Computer Science > Data Structures and Algorithms arXiv:2511.20771 (cs) [Submitted on 25 Nov 2025 ( v1 ), last revised 24 Aug 2026 (this version, v4)] Title: Exploiting Low Scanwidth to Resolve Soft Polytomies Authors: Sebastian Bruchhold , Mathias Weller View PDF HTML (experimental) Abstract: Phylogenetic networks allow modeling reticulate evolution, capturing events such as hybridization and horizontal gene transfer. A fundamental computational problem in this context is the Tree Containment problem, which asks whether a given phylogenetic network is compatible with a given phylogenetic tree. However, the classical statement of the problem is not robust to poorly supported branches in biological data, possibly leading to false negatives. In an effort to address this, a relaxed version that accounts for uncertainty, called Soft Tree Containment, has been introduced by Bentert, Malík, and Weller [SWAT'18]. We present an algorithm that solves Soft Tree Containment in $2^{O(\Delta_T \cdot k \cdot \log(k))} \cdot n^{O(1)}$ time, where $k = \operatorname{sw}(\Gamma) + \Delta_N$, with $\Delta_T$ and $\Delta_N$ denoting the maximum out-degrees in the tree and the network, respectively, and $\operatorname{sw}(\Gamma)$ denoting the "scanwidth" [Berry, Scornavacca, and Weller, SOFSEM'20] of a given tree extension of the network, while $n$ is the input size. Our approach leverages the fact that phylogenetic networks encountered in practice often exhibit low scanwidth, making the problem more tractable. Comments: 24 pages. Accepted at DMTCS. An extended abstract appeared in the proceedings of SOFSEM 2026 Subjects: Data Structures and Algorithms (cs.DS) ACM classes: F.2.2 Cite as: arXiv:2511.20771 [cs.DS] (or arXiv:2511.20771v4 [cs.DS] for this version) https://doi.org/10.48550/arXiv.2511.20771 Focus to learn more arXiv-issued DOI via DataCite Journal reference: SOFSEM 2026: Theory and Practice of Computer Science, volume 16448 of Lecture Notes in Computer Science, pages 332-346, 2026 Related DOI : https://doi.org/10.1007/978-3-032-17801-5_25 Focus to learn more DOI(s) linking to related resources Submission history From: Sebastian Bruchhold [ view email ] [v1] Tue, 25 Nov 2025 19:07:20 UTC (26 KB) [v2] Thu, 12 Mar 2026 15:25:22 UTC (31 KB) [v3] Sun, 28 Jun 2026 18:22:24 UTC (37 KB) [v4] Mon, 24 Aug 2026 18:21:25 UTC (37 KB) Full-text links: Access Paper: View PDF HTML (experimental) TeX Source view license Additional Features Audio Summary Current browse context: cs.DS < prev | next > new | recent | 2025-11 Change to browse by: cs References & Citations SciX Google Scholar Semantic Scholar export BibTeX citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer ( What is the Explorer? ) Connected Papers Toggle Connected Papers ( What is Connected Papers? ) Litmaps Toggle Litmaps ( What is Litmaps? ) scite.ai Toggle scite Smart Citations ( What are Smart Citations? ) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv ( What is alphaXiv? ) Links to Code Toggle CatalyzeX Code Finder for Papers ( What is CatalyzeX? ) DagsHub Toggle DagsHub ( What is DagsHub? ) GotitPub Toggle Gotit.pub ( What is GotitPub? ) Huggingface Toggle Hugging Face ( What is Huggingface? ) ScienceCast Toggle ScienceCast ( What is ScienceCast? ) Demos Demos Replicate Toggle Replicate ( What is Replicate? ) Spaces Toggle Hugging Face Spaces ( What is Spaces? ) Spaces Toggle TXYZ.AI ( What is TXYZ.AI? ) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower ( What are Influence Flowers? ) Core recommender toggle CORE Recommender ( What is CORE? ) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs . Which authors of this paper are endorsers? | Disable MathJax ( What is MathJax? ) We gratefully acknowledge support from our major funders , member institutions , and all contributors. About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)

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