38,057 research outputs found

    Small and large inductive dimension for ideal topological spaces

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    [EN] Undoubtedly, the small inductive dimension, ind, and the large inductive dimension, Ind, for topological spaces have been studied extensively, developing an important field in Topology. Many of their properties have been studied in details (see for example [1,4,5,9,10,18]). However, researches for dimensions in the field of ideal topological spaces are in an initial stage. The covering dimension, dim, is an exception of this fact, since it is a meaning of dimension, which has been studied for such spaces in [17]. In this paper, based on the notions of the small and large inductive dimension, new types of dimensions for ideal topological spaces are studied. They are called *-small and *-large inductive dimension, ideal small and ideal large inductive dimension. Basic properties of these dimensions are studied and relations between these dimensions are investigated.Sereti, F. (2021). Small and large inductive dimension for ideal topological spaces. Applied General Topology. 22(2):417-434. https://doi.org/10.4995/agt.2021.15231OJS417434222M. G. Charalambous, Dimension Theory, A Selection of Theorems and Counterexample, Springer Nature Switzerland AG, Cham, Switzerland, 2019. https://doi.org/10.1007/978-3-030-22232-1M. Coornaert, Topological Dimension, In: Topological dimension and dynamical systems, Universitext. Springer, Cham, 2015. https://doi.org/10.1007/978-3-319-19794-4J. Dontchev, M. Maximilian Ganster and D. Rose, Ideal resolvability, Topology Appl. 93, no. 1 (1999), 1-16. https://doi.org/10.1016/S0166-8641(97)00257-5R. Engelking, General Topology, Heldermann Verlag, Berlin, 1989.R. Engelking, Theory of Dimensions, Finite and Infinite, Heldermann Verlag, Berlin, 1995.D. N. Georgiou, S. E. Han and A. C. Megaritis, Dimensions of the type dim and Alexandroff spaces, J. Egypt. Math. Soc. 21 (2013), 311-317. https://doi.org/10.1016/j.joems.2013.02.015D. N. Georgiou and A. C. Megaritis, An algorithm of polynomial order for computing the covering dimension of a finite space, Applied Mathematics and Computation 231 (2014), 276-283. https://doi.org/10.1016/j.amc.2013.12.185D. N. Georgiou and A. C. Megaritis, Covering dimension and finite spaces, Applied Mathematics and Computation 218 (2014), 3122-3130. https://doi.org/10.1016/j.amc.2011.08.040D. N. Georgiou, A. C. Megaritis and S. Moshokoa, A computing procedure for the small inductive dimension of a finite T0T_0 space, Computational and Applied Mathematics 34, no. 1 (2015), 401-415. https://doi.org/10.1007/s40314-014-0125-zD. N. Georgiou, A. C. Megaritis and S. Moshokoa, Small inductive dimension and Alexandroff topological spaces, Topology Appl. 168 (2014), 103-119. https://doi.org/10.1016/j.topol.2014.02.014D. N. Georgiou, A. C. Megaritis and F. Sereti, A study of the quasi covering dimension for finite spaces through matrix theory, Hacettepe Journal of Mathematics and Statistics 46, no. 1 (2017), 111-125.D. N. Georgiou, A. C. Megaritis and F. Sereti, A study of the quasi covering dimension of Alexandroff countable spaces using matrices, Filomat 32, no. 18 (2018), 6327-6337. https://doi.org/10.2298/FIL1818327GD. N. Georgiou, A. C. Megaritis and F. Sereti, A topological dimension greater than or equal to the classical covering dimension, Houston Journal of Mathematics 43, no. 1 (2017), 283-298.T. R. Hamlett, D. Rose and D. Janković, Paracompactness with respect to an ideal, Internat. J. Math. Math. Sci. 20, no. 3 (1997), 433-442. https://doi.org/10.1155/S0161171297000598D. Janković and T. R. Hamlett, New topologies from old via ideals, Amer. Math. Monthly 97, no. 4 (1990), 295-310. https://doi.org/10.1080/00029890.1990.11995593K. Kuratowski, Topologie I, Monografie Matematyczne 3, Warszawa-Lwów, 1933.A. C. Megaritis, Covering dimension and ideal topological spaces, Quaestiones Mathematicae, to appear. https://doi.org/10.2989/16073606.2020.1851309A. R. Pears, Dimension theory of general spaces, Cambridge University Press, Cambridge, 1975.P. Samuels, A topology formed from a given topology and ideal, J. London Math. Soc. 10, no. 4 (1975), 409-416. https://doi.org/10.1112/jlms/s2-10.4.40

    Topological Qubit Design and Leakage

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    We examine how best to design qubits for use in topological quantum computation. These qubits are topological Hilbert spaces associated with small groups of anyons. Op- erations are performed on these by exchanging the anyons. One might argue that, in order to have as many simple single qubit operations as possible, the number of anyons per group should be maximized. However, we show that there is a maximal number of particles per qubit, namely 4, and more generally a maximal number of particles for qudits of dimension d. We also look at the possibility of having topological qubits for which one can perform two-qubit gates without leakage into non-computational states. It turns out that the requirement that all two-qubit gates are leakage free is very restrictive and this property can only be realized for two-qubit systems related to Ising-like anyon models, which do not allow for universal quantum computation by braiding. Our results follow directly from the representation theory of braid groups which means they are valid for all anyon models. We also make some remarks on generalizations to other exchange groups.Comment: 13 pages, 3 figure

    Permanence results for dimension-theoretic coarse notions

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    Coarse topology is the study of interesting topological properties of discrete spaces. In this dissertation, we will discuss a coarse analog of dimension and several generalizations. We begin by extending the class of metric spaces for which these properties are known. The next few chapters are devoted to generalizing these properties to all coarse spaces and exploring the relationships between these generalizations. Finally, we give a brief discussion of computational topology, highlighting how to generate the Rips and Cech simplicial complexes from a set of data. We end with some code written to generate these complexes, and present some thoughts on how to use this to compute certain coarse properties

    Finite Boolean Algebras for Solid Geometry using Julia's Sparse Arrays

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    The goal of this paper is to introduce a new method in computer-aided geometry of solid modeling. We put forth a novel algebraic technique to evaluate any variadic expression between polyhedral d-solids (d = 2, 3) with regularized operators of union, intersection, and difference, i.e., any CSG tree. The result is obtained in three steps: first, by computing an independent set of generators for the d-space partition induced by the input; then, by reducing the solid expression to an equivalent logical formula between Boolean terms made by zeros and ones; and, finally, by evaluating this expression using bitwise operators. This method is implemented in Julia using sparse arrays. The computational evaluation of every possible solid expression, usually denoted as CSG (Constructive Solid Geometry), is reduced to an equivalent logical expression of a finite set algebra over the cells of a space partition, and solved by native bitwise operators.Comment: revised version submitted to Computer-Aided Geometric Desig

    Linear-Size Approximations to the Vietoris-Rips Filtration

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    The Vietoris-Rips filtration is a versatile tool in topological data analysis. It is a sequence of simplicial complexes built on a metric space to add topological structure to an otherwise disconnected set of points. It is widely used because it encodes useful information about the topology of the underlying metric space. This information is often extracted from its so-called persistence diagram. Unfortunately, this filtration is often too large to construct in full. We show how to construct an O(n)-size filtered simplicial complex on an nn-point metric space such that its persistence diagram is a good approximation to that of the Vietoris-Rips filtration. This new filtration can be constructed in O(nlogn)O(n\log n) time. The constant factors in both the size and the running time depend only on the doubling dimension of the metric space and the desired tightness of the approximation. For the first time, this makes it computationally tractable to approximate the persistence diagram of the Vietoris-Rips filtration across all scales for large data sets. We describe two different sparse filtrations. The first is a zigzag filtration that removes points as the scale increases. The second is a (non-zigzag) filtration that yields the same persistence diagram. Both methods are based on a hierarchical net-tree and yield the same guarantees

    Sheaf-Theoretic Stratification Learning from Geometric and Topological Perspectives

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    In this paper, we investigate a sheaf-theoretic interpretation of stratification learning from geometric and topological perspectives. Our main result is the construction of stratification learning algorithms framed in terms of a sheaf on a partially ordered set with the Alexandroff topology. We prove that the resulting decomposition is the unique minimal stratification for which the strata are homogeneous and the given sheaf is constructible. In particular, when we choose to work with the local homology sheaf, our algorithm gives an alternative to the local homology transfer algorithm given in Bendich et al. (2012), and the cohomology stratification algorithm given in Nanda (2017). Additionally, we give examples of stratifications based on the geometric techniques of Breiding et al. (2018), illustrating how the sheaf-theoretic approach can be used to study stratifications from both topological and geometric perspectives. This approach also points toward future applications of sheaf theory in the study of topological data analysis by illustrating the utility of the language of sheaf theory in generalizing existing algorithms

    Persistent Homology analysis of Phase Transitions

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    Persistent homology analysis, a recently developed computational method in algebraic topology, is applied to the study of the phase transitions undergone by the so-called XY-mean field model and by the phi^4 lattice model, respectively. For both models the relationship between phase transitions and the topological properties of certain submanifolds of configuration space are exactly known. It turns out that these a-priori known facts are clearly retrieved by persistent homology analysis of dynamically sampled submanifolds of configuration space.Comment: 10 pages; 10 figure
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