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        <identifier>oai:drops-oai.dagstuhl.de:27755</identifier>
        <datestamp>2026-09-09T12:19:37Z</datestamp>
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          <dc:title>Almost All Graphs Are Vertex-Minor Universal</dc:title>
          <dc:creator>Ascoli, Ruben</dc:creator>
          <dc:creator>Frederickson, Bryce</dc:creator>
          <dc:creator>Frederickson, Sarah</dc:creator>
          <dc:creator>McFarland, Caleb</dc:creator>
          <dc:creator>Post, Logan</dc:creator>
          <dc:subject>vertex-minors</dc:subject>
          <dc:subject>random graphs</dc:subject>
          <dc:subject>quantum networks</dc:subject>
          <dc:subject>graph states</dc:subject>
          <dc:description>Answering a question of Claudet, we prove that the uniformly random graph G∼ 𝔾(n, 1/2) is Ω(√n)-vertex-minor universal with high probability. That is, for some constant α≈ 0.911, any graph on any α√ n specified vertices of G can be obtained as a vertex-minor of G. This has direct implications for quantum communications networks: an n-vertex k-vertex-minor universal graph corresponds to an n-qubit k-stabilizer universal graph state, which has the property that one can induce any stabilizer state on any k qubits using only local operations and classical communications. &#13;
We further employ our methods in two other contexts. We obtain a bipartite pivot-minor version of our main result, and we use it to derive a universality statement for minors in random binary matroids. We also introduce the vertex-minor Ramsey number R_{vm}(k) to be the smallest value n such that every n-vertex graph contains an independent set of size k as a vertex-minor. Supported by our main result, we conjecture that R_{vm}(k) is polynomial in k. We prove Ω(k²) ≤ R_{vm}(k) ≤ 2^k - 1.</dc:description>
          <dc:publisher>Schloss Dagstuhl – Leibniz-Zentrum für Informatik</dc:publisher>
          <dc:contributor>Ruben Ascoli and Bryce Frederickson and Sarah Frederickson and Caleb McFarland and Logan Post</dc:contributor>
          <dc:date>2026</dc:date>
          <dc:relation>Is Part Of LIPIcs, Volume 392, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2026)</dc:relation>
          <dc:type>InProceedings</dc:type>
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          <dc:identifier>doi:10.4230/LIPIcs.APPROX/RANDOM.2026.38</dc:identifier>
          <dc:identifier>urn:nbn:de:0030-drops-277559</dc:identifier>
          <dc:identifier>https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2026.38</dc:identifier>
          <dc:language>eng</dc:language>
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