3 Search Results for "Johnson, Robert F."

Document
DOI: 10.4230/LIPIcs.MFCS.2022.54
The Hamilton Compression of Highly Symmetric Graphs

Authors: Petr Gregor, Arturo Merino, and Torsten Mütze

Published in: LIPIcs, Volume 241, 47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022)

Abstract
We say that a Hamilton cycle C = (x₁,…,x_n) in a graph G is k-symmetric, if the mapping x_i ↦ x_{i+n/k} for all i = 1,…,n, where indices are considered modulo n, is an automorphism of G. In other words, if we lay out the vertices x₁,…,x_n equidistantly on a circle and draw the edges of G as straight lines, then the drawing of G has k-fold rotational symmetry, i.e., all information about the graph is compressed into a 360^∘/k wedge of the drawing. We refer to the maximum k for which there exists a k-symmetric Hamilton cycle in G as the Hamilton compression of G. We investigate the Hamilton compression of four different families of vertex-transitive graphs, namely hypercubes, Johnson graphs, permutahedra and Cayley graphs of abelian groups. In several cases we determine their Hamilton compression exactly, and in other cases we provide close lower and upper bounds. The cycles we construct have a much higher compression than several classical Gray codes known from the literature. Our constructions also yield Gray codes for bitstrings, combinations and permutations that have few tracks and/or that are balanced.
Cite as

Petr Gregor, Arturo Merino, and Torsten Mütze. The Hamilton Compression of Highly Symmetric Graphs. In 47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 241, pp. 54:1-54:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{gregor_et_al:LIPIcs.MFCS.2022.54,
  author =	{Gregor, Petr and Merino, Arturo and M\"{u}tze, Torsten},
  title =	{{The Hamilton Compression of Highly Symmetric Graphs}},
  booktitle =	{47th International Symposium on Mathematical Foundations of Computer Science (MFCS 2022)},
  pages =	{54:1--54:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-256-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{241},
  editor =	{Szeider, Stefan and Ganian, Robert and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2022.54},
  URN =		{urn:nbn:de:0030-drops-168529},
  doi =		{10.4230/LIPIcs.MFCS.2022.54},
  annote =	{Keywords: Hamilton cycle, Gray code, hypercube, permutahedron, Johnson graph, Cayley graph, abelian group, vertex-transitive}
}
Document
DOI: 10.4230/LIPIcs.DNA.2020.2
Simplifying Chemical Reaction Network Implementations with Two-Stranded DNA Building Blocks

Authors: Robert F. Johnson and Lulu Qian

Published in: LIPIcs, Volume 174, 26th International Conference on DNA Computing and Molecular Programming (DNA 26) (2020)

Abstract
In molecular programming, the Chemical Reaction Network model is often used to describe real or hypothetical systems. Often, an interesting computational task can be done with a known hypothetical Chemical Reaction Network, but often such networks have no known physical implementation. One of the important breakthroughs in the field was that any Chemical Reaction Network can be physically implemented, approximately, using DNA strand displacement mechanisms. This allows us to treat the Chemical Reaction Network model as a programming language and the implementation schemes as its compiler. This also suggests that it would be useful to optimize the result of such a compilation, and in general to find effective ways to design better DNA strand displacement systems. We discuss DNA strand displacement systems in terms of "motifs", short sequences of elementary DNA strand displacement reactions. We argue that describing such motifs in terms of their inputs and outputs, then building larger systems out of the abstracted motifs, can be an efficient way of designing DNA strand displacement systems. We discuss four previously studied motifs in this abstracted way, and present a new motif based on cooperative 4-way strand exchange. We then show how Chemical Reaction Network implementations can be built out of abstracted motifs, discussing existing implementations as well as presenting two new implementations based on 4-way strand exchange, one of which uses the new cooperative motif. The new implementations both have two desirable properties not found in existing implementations, namely both use only at most 2-stranded DNA complexes for signal and fuel complexes and both are physically reversible. There are reasons to believe that those properties may make them more robust and energy-efficient, but at the expense of using more fuel complexes than existing implementation schemes.
Cite as

Robert F. Johnson and Lulu Qian. Simplifying Chemical Reaction Network Implementations with Two-Stranded DNA Building Blocks. In 26th International Conference on DNA Computing and Molecular Programming (DNA 26). Leibniz International Proceedings in Informatics (LIPIcs), Volume 174, pp. 2:1-2:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{johnson_et_al:LIPIcs.DNA.2020.2,
  author =	{Johnson, Robert F. and Qian, Lulu},
  title =	{{Simplifying Chemical Reaction Network Implementations with Two-Stranded DNA Building Blocks}},
  booktitle =	{26th International Conference on DNA Computing and Molecular Programming (DNA 26)},
  pages =	{2:1--2:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-163-4},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{174},
  editor =	{Geary, Cody and Patitz, Matthew J.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.DNA.2020.2},
  URN =		{urn:nbn:de:0030-drops-129557},
  doi =		{10.4230/LIPIcs.DNA.2020.2},
  annote =	{Keywords: Molecular programming, DNA computing, Chemical Reaction Networks, DNA strand displacement}
}
Document
RANDOM
DOI: 10.4230/LIPIcs.APPROX-RANDOM.2019.47
Near-Neighbor Preserving Dimension Reduction for Doubling Subsets of l_1

Authors: Ioannis Z. Emiris, Vasilis Margonis, and Ioannis Psarros

Published in: LIPIcs, Volume 145, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019)

Abstract
Randomized dimensionality reduction has been recognized as one of the fundamental techniques in handling high-dimensional data. Starting with the celebrated Johnson-Lindenstrauss Lemma, such reductions have been studied in depth for the Euclidean (l_2) metric, but much less for the Manhattan (l_1) metric. Our primary motivation is the approximate nearest neighbor problem in l_1. We exploit its reduction to the decision-with-witness version, called approximate near neighbor, which incurs a roughly logarithmic overhead. In 2007, Indyk and Naor, in the context of approximate nearest neighbors, introduced the notion of nearest neighbor-preserving embeddings. These are randomized embeddings between two metric spaces with guaranteed bounded distortion only for the distances between a query point and a point set. Such embeddings are known to exist for both l_2 and l_1 metrics, as well as for doubling subsets of l_2. The case that remained open were doubling subsets of l_1. In this paper, we propose a dimension reduction by means of a near neighbor-preserving embedding for doubling subsets of l_1. Our approach is to represent the pointset with a carefully chosen covering set, then randomly project the latter. We study two types of covering sets: c-approximate r-nets and randomly shifted grids, and we discuss the tradeoff between them in terms of preprocessing time and target dimension. We employ Cauchy variables: certain concentration bounds derived should be of independent interest.
Cite as

Ioannis Z. Emiris, Vasilis Margonis, and Ioannis Psarros. Near-Neighbor Preserving Dimension Reduction for Doubling Subsets of l_1. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 145, pp. 47:1-47:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{emiris_et_al:LIPIcs.APPROX-RANDOM.2019.47,
  author =	{Emiris, Ioannis Z. and Margonis, Vasilis and Psarros, Ioannis},
  title =	{{Near-Neighbor Preserving Dimension Reduction for Doubling Subsets of l\underline1}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019)},
  pages =	{47:1--47:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-125-2},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{145},
  editor =	{Achlioptas, Dimitris and V\'{e}gh, L\'{a}szl\'{o} A.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX-RANDOM.2019.47},
  URN =		{urn:nbn:de:0030-drops-112628},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2019.47},
  annote =	{Keywords: Approximate nearest neighbor, Manhattan metric, randomized embedding}
}
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