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In this paper, we explore the interaction between two monoidal structures: a multiplicative one, for the encoding of pairing, and an additive one, for the encoding of choice. We propose a colored PROP to model computation in this framework,…

Logic in Computer Science · Computer Science 2025-05-21 Kostia Chardonnet , Marc de Visme , Benoît Valiron , Renaud Vilmart

Applied category theory often studies symmetric monoidal categories (SMCs) whose morphisms represent open systems. These structures naturally accommodate complex wiring patterns, leveraging (co)monoidal structures for splitting and merging…

Category Theory · Mathematics 2026-03-11 Marius Furter , Yujun Huang , Gioele Zardini

We introduce nominal string diagrams as, string diagrams internal in the category of nominal sets. This requires us to take nominal sets as a monoidal category, not with the cartesian product, but with the separated product. To this end, we…

Logic in Computer Science · Computer Science 2019-04-17 Samuel Balco , Alexander Kurz

As an intuitive description of complex physical, social, or brain systems, complex networks have fascinated scientists for decades. Recently, to abstract a network's structural and dynamical attributes for utilization, network…

Social and Information Networks · Computer Science 2022-10-21 Yue Deng

"The Spin Foams for People Without the 3d/4d Imagination" could be an alternative title of our work. We derive spin foams from operator spin network diagrams} we introduce. Our diagrams are the spin network analogy of the Feynman diagrams.…

General Relativity and Quantum Cosmology · Physics 2015-05-28 Marcin Kisielowski , Jerzy Lewandowski , Jacek Puchta

In the first part of this paper we present a theory of proof nets for full multiplicative linear logic, including the two units. It naturally extends the well-known theory of unit-free multiplicative proof nets. A linking is no longer a set…

Logic in Computer Science · Computer Science 2017-01-11 Francois Lamarche , Lutz Strassburger

A representation theorem relates different mathematical structures by providing an isomorphism between them: that is, a one-to-one correspondence preserving their original properties. Establishing that the two structures substantially…

Logic in Computer Science · Computer Science 2023-06-02 Marco B. Caminati , Juliana K. F. Bowles

In fields ranging from business to systems biology, directed graphs with edges labeled by signs are used to model systems in a simple way: the nodes represent entities of some sort, and an edge indicates that one entity directly affects…

Category Theory · Mathematics 2026-03-20 John C. Baez , Adittya Chaudhuri

We initiate the systematic study of modular representations of symmetric groups that arise via the braiding in (symmetric) tensor categories over fields of positive characteristic. We determine what representations appear for certain…

Representation Theory · Mathematics 2026-03-09 Kevin Coulembier

A causal-net is a finite acyclic directed graph. In this paper, we introduce a category, denoted by $\mathbf{Cau}$ and called causal-net category, whose objects are causal-nets and morphisms between two causal-nets are the functors between…

Category Theory · Mathematics 2023-05-09 Xuexing Lu

The vast corpus of physics equations forms an implicit network of mathematical relationships that traditional analysis cannot fully explore. This work introduces a graph-based framework combining neural networks with symbolic analysis to…

Machine Learning · Computer Science 2025-08-15 Massimiliano Romiti

Let $\mathcal C$ be a category with finite colimits, and let $(\mathcal E,\mathcal M)$ be a factorisation system on $\mathcal C$ with $\mathcal M$ stable under pushouts. Writing $\mathcal C;\mathcal M^{\mathrm{op}}$ for the symmetric…

Category Theory · Mathematics 2017-03-30 Brendan Fong

Network science can offer fundamental insights into the structural and functional properties of complex systems. For example, it is widely known that neuronal circuits tend to organize into basic functional topological modules, called…

Adaptation and Self-Organizing Systems · Physics 2022-08-03 Matteo Zambra , Alberto Testolin , Amos Maritan

A tensor network is a type of decomposition used to express and approximate large arrays of data. A given data-set, quantum state or higher dimensional multi-linear map is factored and approximated by a composition of smaller multi-linear…

Quantum Physics · Physics 2022-07-08 Richik Sengupta , Soumik Adhikary , Ivan Oseledets , Jacob Biamonte

Network theory has proven to be a powerful tool in describing and analyzing systems by modelling the relations between their constituent objects. In recent years great progress has been made by augmenting `traditional' network theory.…

Data Analysis, Statistics and Probability · Physics 2016-06-03 Dominik Traxl , Niklas Boers , Jürgen Kurths

Applied category theory often studies symmetric monoidal categories (SMCs) whose morphisms represent open systems. These structures naturally accommodate complex wiring patterns, leveraging (co)monoidal structures for splitting and merging…

Category Theory · Mathematics 2025-09-03 Marius Furter , Yujun Huang , Gioele Zardini

This thesis (defended 10/07/2019) develops a theory of networks of hybrid open systems and morphisms. It builds upon a framework of networks of continuous-time open systems as product and interconnection. We work out categorical notions for…

Dynamical Systems · Mathematics 2019-12-30 James Schmidt

Coherence in a monoidal category asserts that all morphisms built from structural isomorphisms with a fixed source and target coincide. These structural isomorphisms include, in particular, the associators. Linearly distributive categories…

Combinatorics · Mathematics 2026-05-06 Max Demirdilek , Christian Reiher , Christoph Schweigert

Controlled commands -- computations whose execution depends on a separate input -- play a central role in reversible Boolean circuits and quantum circuits. However, existing formalisms typically treat control only implicitly, entangled with…

Logic in Computer Science · Computer Science 2026-05-04 Chris Heunen , Robin Kaarsgaard , Louis Lemonnier

Neural networks have become an increasingly popular tool for solving many real-world problems. They are a general framework for differentiable optimization which includes many other machine learning approaches as special cases. In this…

Machine Learning · Computer Science 2019-07-22 Bruno Gavranović