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Recent algorithmic advances in algebraic automata theory drew attention to semigroupoids (semicategories). These are mathematical descriptions of typed computational processes, but they have not been studied systematically in the context of…

Formal Languages and Automata Theory · Computer Science 2025-09-30 Attila Egri-Nagy , Chrystopher L. Nehaniv

This book is expository and is in Russian. It is shown how in the course of solution of interesting geometric problems (close to applications) naturally appear main notions of algebraic topology (homology groups, obstructions and…

Geometric Topology · Mathematics 2016-05-18 A. Skopenkov

This monograph develops the theory of Besov spaces for abelian group actions on semifinite von Neumann algebras and then proves Peller criteria for traceclass properties of associated Hankel operators. This allows to extend known index…

Mathematical Physics · Physics 2022-11-10 Hermann Schulz-Baldes , Tom Stoiber

Statistical Topology emerged since topological aspects continue to gain importance in many areas of physics. It is most desirable to study topological invariants and their statistics in schematic models that facilitate the identification of…

Mathematical Physics · Physics 2023-03-22 Thomas Guhr

We introduce orbifolds from the classical point of view, using charts, and present orbifold versions of elementary objects from Algebraic Topology, such as the fundamental group, coverings and Euler characteristic; Differential…

Differential Geometry · Mathematics 2022-04-13 Francisco C. Caramello

We give a new approach to the study of statistical mechanical systems: algebraic topology is used to investigate the statistical distributions of stochastic currents generated in graphs. In the adiabatic and low temperature limits we will…

Algebraic Topology · Mathematics 2012-07-04 Vladimir Y. Chernyak , John R. Klein , Nikolai A. Sinitsyn

Topological Coding consists of two different kinds of mathematics: topological structure and mathematical relation. The colorings and labelings of graph theory are main techniques in topological coding applied in asymmetric encryption…

Information Theory · Computer Science 2021-06-30 Bing Yao , Hongyu Wang

This work studies certain aspects of graphs embedded on surfaces. Initially, a colored graph model for a map of a graph on a surface is developed. Then, a concept analogous to (and extending) planar graph is introduced in the same spirit as…

Combinatorics · Mathematics 2007-05-23 Sostenes Lins

We present a mathematical framework for describing the topology of configuration spaces for particles on one-connected graphs. In particular, we compute the homology groups over integers for different classes of one-connected graphs. Our…

Mathematical Physics · Physics 2017-05-24 Tomasz Maciążek , Adam Sawicki

This paper introduces topological data analysis. Starting from notions of a metric space and some elementary graph theory, we take example sets of data and demonstrate some of their topological properties. We discuss simplicial complexes…

History and Overview · Mathematics 2020-04-09 Dayten Sheffar

Trophic coherence, a measure of a graph's hierarchical organisation, has been shown to be linked to a graph's structural and dynamical aspects such as cyclicity, stability and normality. Trophic levels of vertices can reveal their…

Physics and Society · Physics 2020-10-08 Giannis Moutsinas , Choudhry Shuaib , Weisi Guo , Stephen Jarvis

The state-of-the-art coding schemes for topological interference management (TIM) problems are usually handcrafted for specific families of network topologies, relying critically on experts' domain knowledge. This inevitably restricts the…

Information Theory · Computer Science 2023-05-15 Zhiwei Shan , Xinping Yi , Han Yu , Chung-Shou Liao , Shi Jin

We present an introduction to the theory of algebraic geometry codes. Starting from evaluation codes and codes from order and weight functions, special attention is given to one-point codes and, in particular, to the family of Castle codes.

Information Theory · Computer Science 2015-05-13 Carlos Munuera , Wilson Olaya-León

We present a framework for representing and modeling data on graphs. Based on this framework, we study three typical classes of graph signals: smooth graph signals, piecewise-constant graph signals, and piecewise-smooth graph signals. For…

Artificial Intelligence · Computer Science 2015-12-18 Siheng Chen , Rohan Varma , Aarti Singh , Jelena Kovačević

Complex networks are universal, arising in fields as disparate as sociology, physics, and biology. In the past decade, extensive research into the properties and behaviors of complex systems has uncovered surprising commonalities among the…

Other Quantitative Biology · Quantitative Biology 2015-06-26 Claire Christensen , Reka Albert

Geometric, topological and graph theory modeling and analysis of biomolecules are of essential importance in the conceptualization of molecular structure, function, dynamics, and transport. On the one hand, geometric modeling provides…

Biomolecules · Quantitative Biology 2016-12-07 Kelin Xia , Guo-Wei Wei

In this paper, we introduce the notion of a dual topological graph of a given topological graph, and show that it defines a C*-algebra isomorphic to the C*-algebra of the given one. Repeating to take a dual, and taking a projective limit,…

Operator Algebras · Mathematics 2021-07-06 Takeshi Katsura

The context of this paper is the use of formal methods for topology-based geometric modelling. Topology-based geometric modelling deals with objects of various dimensions and shapes. Usually, objects are defined by a graph-based topological…

Graphics · Computer Science 2011-02-15 Thomas Bellet , Agnès Arnould , Pascale Le Gall

These lecture notes offer a pedagogical yet concise introduction to topological quantum computing. The material focuses on topological superconductors and Majorana qubits. It concludes with a discussion of more general braiding phenomena.…

Quantum Physics · Physics 2024-10-22 Fabian Hassler

Probabilistic graphical modeling is a branch of machine learning that uses probability distributions to describe the world, make predictions, and support decision-making under uncertainty. Underlying this modeling framework is an elegant…

Machine Learning · Computer Science 2025-07-24 Jacqueline Maasch , Willie Neiswanger , Stefano Ermon , Volodymyr Kuleshov