38,057 research outputs found
Small and large inductive dimension for ideal topological spaces
[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 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
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
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
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
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 -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 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
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
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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