The confinement of surface plasmon modes in flat nanoparticles gives rise to plasmonic breathing modes. With a vanishing net dipole moment, breathing modes do not radiate, i.e., they are optically dark. Having thus escaped optical detection, breathing modes were only recently revealed in silver nanodisks with electron energy loss spectroscopy in an electron microscope. We show that for disk diameters >200 nm, retardation induced by oblique optical illumination relaxes the optically dark character. This makes breathing modes and thus the full plasmonic mode spectrum accessible to optical spectroscopy. The experimental spectroscopy data are in excellent agreement with numerical simulations.
In this work we consider the following problem. Given a planar graph G with maximum degree 4 and a function flex : E −→ N 0 that gives each edge a flexibility. Does G admit a planar embedding on the grid such that each edge e has at most flex(e) bends? Note that in our setting the combinatorial embedding of G is not fixed.We give a polynomial-time algorithm for this problem when the flexibility of each edge is positive. This includes as a special case the problem of deciding whether G admits a drawing with at most one bend per edge.
A k-degenerate graph is a graph in which every induced subgraph has a vertex with degree at most k. The class of k-degenerate graphs is interesting from a theoretical point of view and it plays an interesting role in the theory of fixed parameter tractability since some otherwise W[2]-hard domination problems become fixed-parameter tractable for k-degenerate graphs.It is a well-known fact that the k-degenerate graphs are exactly the graphs whose vertex-set can be well-ordered such that each vertex is incident to at most k larger vertices with respect to this ordering. A well-ordered k-degenerate graph is a labeled graph with vertex-labels 1, . . . , n such that the ordering of the vertices by their labels is a well-ordering of the graph.We consider the problem of enumerating and generating well-ordered k-degenerate graphs with a given number of vertices and with a given number of vertices and edges, respectively, uniformly at random. By generating wellordered k-degenerate graphs we generate at least one labeled copy of each unlabeled k-degenerate graph and we filter some but not all isomorphies compared to the classical labeled approach.We also introduce the class of strongly k-degenerate graphs, which are k-degenerate graphs with minimum degree k. These graphs are a natural generalization of k-regular graphs which can be used in order to generate graphs with predefined core-decomposition.We present efficient algorithms for generating wellordered k-degenerate graphs with given number of vertices (and edges). After a precomputation which must only be performed once when generating more than one well-ordered k-degenerate graph these algorithms are almost optimal. Additionally, we present complete non-uniform generators for these classes with optimal running time. We also present an efficient and complete generator for well-ordered strongly k-degenerate graphs with given number of vertices (and edges). Finally, we present efficient algorithms for enumerating well-ordered k-degenerate and strongly k-degenerate graphs.
Abstract. In this paper, we explore a new convention for drawing graphs, the (Manhattan-) geodesic drawing convention. It requires that edges are drawn as interior-disjoint monotone chains of axis-parallel line segments, that is, as geodesics with respect to the Manhattan metric. First, we show that geodesic embeddability on the grid is equivalent to 1-bend embeddability on the grid. For the latter question an efficient algorithm has been proposed. Second, we consider geodesic point-set embeddability where the task is to decide whether a given graph can be embedded on a given point set. We show that this problem is N P-hard. In contrast, we efficiently solve geodesic polygonization-the special case where the graph is a cycle. Third, we consider geodesic point-set embeddability where the vertex-point correspondence is given. We show that on the grid, this problem is N P-hard even for perfect matchings, but without the grid restriction, we solve the matching problem efficiently.
Coreference resolution (CR) is a key task in the automated analysis of characters in stories. Standard CR systems usually trained on newspaper texts have difficulties with literary texts, even with novels; a comparison with newspaper texts showed that average sentence length is greater in novels and the number of pronouns, as well as the percentage of direct speech is higher. We report promising evaluation results for a rule-based system similar to [Lee et al. 2011], but tailored to the domain which recognizes coreference chains in novels much better than CR systems like CorZu. Rule-based systems performed best on the CoNLL 2011 challenge [Pradhan et al. 2011]. Recent work in machine learning showed similar results as rule-based systems [Durett et al. 2013]. The latter has the advantage that its explanation component facilitates a fine grained error analysis for incremental refinement of the rules.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.