Probabilistic Convergence Spaces Research Articles

On the Probabilistic Convergence Spaces: Monad and its Eilenberg–Moore Category

Motivated by the category of probabilistic convergence spaces — a supercategory of the category of topological spaces; recently, we brought to light the categories of probabilistic convergence groups, probabilistic metric probabilistic convergence groups, probabilistic convergence transformation groups, along with their underpinning natural examples. The purpose of this paper is, first, to establish a result on the isomorphism between the categories of probabilistic metric groups, and probabilistic metric probabilistic convergence groups. Second, among others, we explore a monad in relation with probabilistic convergence groups, and probabilistic convergence spaces, and their related algebras. In so doing, we consider a product of the categories of probabilistic convergence groups and probabilistic convergence spaces in an attempt to construct a monad on it such that the corresponding category of algebras, the so-called Eilenberg–Moore category, is isomorphic to the category of probabilistic convergence transformation groups. Finally, invoking so-called Beck’s theorem on characterization of algebras, and starting with a particular adjunction, we achieve a monad. Conversely, given a monad, we obtain an adjunction which coincides with the original monad.

A convergence theory for probabilistic metric spaces

We develop a theory of probabilistic convergence spaces based on Tardiff’s neighbourhood systems for probabilistic metric spaces. We show that the resulting category is a topological universe and we characterize a subcategory that is isomorphic to the category of probabilistic metric spaces.

Stratified LMN-convergence tower spaces

We develop a general theory of convergence for lattice-valued spaces based on the concept of s-stratified LM-filters. For different choices of the frames L and M, different kinds of filters arise, and suitable choices of the lattice N allow to view many existing fuzzy and probabilistic convergence spaces as special examples of our stratified LMN-convergence tower spaces. The stratification requires a certain relation between the frames L and M and we use a so-called stratification mapping to this end. The stratification condition is used to show that the resulting category is fiber-small and hence Cartesian closedness is equivalent to the existence of natural function spaces. We give several examples for our spaces for different choices of the lattices L, M and N with a special focus on enriched LM-fuzzy topological spaces. Finally, we study diagonal axioms and regularity.

Gähler’s neighbourhood condition for convergence approach spaces

We characterize convergence approach spaces that are approach spaces by generalizing a neighbourhood condition from the category of convergence spaces to the category of convergence approach spaces. We also study this condition in the categories of limit tower spaces and probabilistic convergence spaces.

Fuzzy convergence: open and proper maps

The notions of open and proper maps are introduced in the category FCS of fuzzy convergence spaces and each is shown to be an extension of the same notion with respect to the embedding functor from the category PCS of probabilistic convergence spaces. Proper maps in FCS are shown to be productive and, moreover, preserve closures of fuzzy sets, regularity and local precompactness. All projection maps in FCS are open and open maps are finitely productive.

A Generalization of Probabilistic Uniform Spaces

We develop a theory for probabilistic semiuniform convergence spaces. Probabilistic semiuniform convergence spaces generalize probabilistic uniform spaces in the sense of Florescu and probabilistic convergence spaces in the sense of Kent and Richardson. This theory includes a new branch in topology, namely, Convenient Topology, introduced by Preus. Thus, it includes semiuniform convergence spaces and uniform spaces, filter and Cauchy spaces and (symmetric) limit spaces and, therefore, (symmetric) topological spaces. The theory of probabilistic semiuniform convergence spaces reveals categories which are strong topological universes or have other convenient properties.

T-regular probabilistic convergence spaces

AbstractA probabilistic convergence structure assigns a probability that a given filter converges to a given element of the space. The role of the t-norm (triangle norm) in the study of regularity of probabilistic convergence spaces is investigated. Given a probabilistic convergence space, there exists a finest T-regular space which is coarser than the given space, and is referred to as the ‘T-regular modification’. Moreover, for each probabilistic convergence space, there is a sequence of spaces, indexed by nonnegative ordinals, whose first term is the given space and whose last term is its T-regular modification. The T-regular modification is illustrated in the example involving ‘convergence with probability λ’ for several t-norms. Suitable function space structures in terms of a given t-norm are also considered.

Categorical Properties of Probabilistic Convergence Spaces

The purpose of this paper is to discuss some categorical properties of probabilistic convergence spaces. Its main theses are: (1) the construct P-PrTop of probabilistic pretopological spaces is the extensional topological hull of the construct FTPcs of FT-diagonal probabilistic convergence spaces for every triangular norm T; (2) the construct P-PsTop of probabilistic pseudotopological spaces is the topological universe hull of FTPcs for every triangular norm T.

Approach Spaces, Limit Tower Spaces, and Probabilistic Convergence Spaces

The category LTS of limit tower spaces is defined and shown to be isomorphic to the category CAP of convergence approach spaces. The full subcategory of LTS determined by the objects satisfying a diagonal axiom due to Cook and Fischer is shown to be isomorphic to the category AP of approach spaces. A family of isomorphisms is also obtained between LTS and certain full subcategories of the category PCS of probabilistic convergence spaces.

Probabilistic convergence spaces

AbstractA basic theory for probabilistic convergence spaces based on filter convergence is introduced. As in Florescu's previous theory of probabilistic convergence structures based on nets, one is able to assign a probability that a given filter converges to a given point. Various concepts and theorems pertaining to convergence spaces are extended to the realm of probabilistic convergence spaces, and illustrated by means of examples based on convergence in probability and convergence almost everywhere. Diagonal axioms due to Kowalsky and Fischer are also studied, first for convergence spaces and then in the setting of probabilistic convergence spaces.

Probablistic convergence spaces and regularity

The usual definition of regularity for convergence spaces can be characterized by a diagonal axiom R due to Cook and Fischer. The generalization of R to the realm of probabilistic convergence spaces depends on a t‐norm T, and the resulting axiom RT defines “T‐regularity”, which is the primary focus of this paper. We give several characterizations of T‐regularity, both in general and for specific choices of T, and investigate some of its basic properties.