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Visual Algebraic Proofs for Unknot Detection

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Diagrammatic Representation and Inference (Diagrams 2018)

Abstract

A knot diagram looks like a two-dimensional drawing of a knotted rubberband. Proving that a given knot diagram can be untangled (that is, is a trivial knot, called an unknot) is one of the most famous problems of knot theory. For a small knot diagram, one can try to find a sequence of untangling moves explicitly, but for a larger knot diagram producing such a proof is difficult, and the produced proofs are hard to inspect and understand. Advanced approaches use algebra, with an advantage that since the proofs are algebraic, a computer can be used to produce the proofs, and, therefore, a proof can be produced even for large knot diagrams. However, such produced proofs are not easy to read and, for larger diagrams, not likely to be human readable at all. We propose a new approach combining advantages of these: the proofs are algebraic and can be produced by a computer, whilst each part of the proof can be represented as a reasonably small knot-like diagram (a new representation as a labeled tangle diagram), which can be easily inspected by a human for the purposes of checking the proof and finding out interesting facts about the knot diagram.

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Notes

  1. 1.

    In the implementation presented in Sect. 6 we did not use word reversion because, although reversing a word may make a proof shorter, it is not easy to implement it in the prover software we used.

  2. 2.

    Another approach that we tested (as presented in Sect. 6) is simply to place two tangle diagrams next to each other without connecting them by an arc; this corresponds, in terms of labelling words, to concatenating the words.

  3. 3.

    System used in experiments: Intel(R) Core(TM) i7-4790 CPU 3.60 Ghz, RAM 32 GB, Windows 7 Enterprise.

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Correspondence to Alexei Vernitski .

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Fish, A., Lisitsa, A., Vernitski, A. (2018). Visual Algebraic Proofs for Unknot Detection. In: Chapman, P., Stapleton, G., Moktefi, A., Perez-Kriz, S., Bellucci, F. (eds) Diagrammatic Representation and Inference. Diagrams 2018. Lecture Notes in Computer Science(), vol 10871. Springer, Cham. https://doi.org/10.1007/978-3-319-91376-6_12

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  • DOI: https://doi.org/10.1007/978-3-319-91376-6_12

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