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We examine the use of string diagrams and the mathematics of category theory in the description of quantum states by tensor networks. This approach lead to a unification of several ideas, as well as several results and methods that have not…

Quantum Physics · Physics 2015-03-17 Jacob D. Biamonte , Stephen R. Clark , Dieter Jaksch

This paper introduces a formalism that aims to describe the intricacies of quantum computation by establishing a connection with the mathematical foundations of tensor theory and multilinear maps. The focus is on providing a comprehensive…

Quantum Physics · Physics 2024-09-17 Valentina Amitrano , Francesco Pederiva

Molecular graphs generally contain subgraphs (known as groups) that are identifiable and significant in composition, functionality, geometry, etc. Flat latent representations (node embeddings or graph embeddings) fail to represent, and…

Machine Learning · Computer Science 2019-04-05 Daniel T. Chang

We argue that the quantum-theoretical structures studied in several recent lines of research cannot be adequately described within the standard framework of quantum circuits. This is in particular the case whenever the combination of…

Quantum Physics · Physics 2021-07-14 Augustin Vanrietvelde , Hlér Kristjánsson , Jonathan Barrett

We consider a reducible unitary representation of Heisenberg-Weyl group in a tensor product of two Hilbert spaces. A non-commutative operator graph generated by this representation is introduced. It is shown that spectral projections of…

Quantum Physics · Physics 2021-05-25 G. G. Amosov , A. S. Mokeev

In this survey article we give basic introduction to the theory of quantum families of maps. We begin with a general look at non-commutative (or "quantum") topology. Then we formulate all our results in this language. Existence of quantum…

Operator Algebras · Mathematics 2012-11-06 Piotr M. Sołtan

We give arguments for the necessity to employ Quantum Clifford Hopf Gebras in quantum field theory. The role of the antipode is examined, Feynman diagrams are re-interpreted as tangles of graphical calculus. Regularization due to the design…

High Energy Physics - Theory · Physics 2007-05-23 Bertfried Fauser

Graphical tensor notation is a simple way of denoting linear operations on tensors, originating from physics. Modern deep learning consists almost entirely of operations on or between tensors, so easily understanding tensor operations is…

Machine Learning · Computer Science 2024-02-06 Jordan K. Taylor

Recent developments in quantum chemistry, perturbative quantum field theory, statistical physics or stochastic differential equations require the introduction of new families of Feynman-type diagrams. These new families arise in various…

Mathematical Physics · Physics 2011-03-17 Christian Brouder , Patras Frédéric

Several recent papers have proposed increasing the expressive power of graph neural networks by exploiting subgraphs or other topological structures. In parallel, researchers have investigated higher order permutation equivariant networks.…

Machine Learning · Statistics 2026-02-05 Andrew Hands , Tianyi Sun , Risi Kondor

We briefly review the r\^ole played by algebraic structures like combinatorial Hopf algebras in the renormalizability of (noncommutative) quantum field theory. After sketching the commutative case, we analyze the noncommutative…

Combinatorics · Mathematics 2011-03-28 Adrian Tanasa

One particular approach to quantum groups (matrix pseudo groups) provides the Manin quantum plane. Assuming an appropriate set of non-commuting variables spanning linearly a representation space one is able to show that the endomorphisms on…

Quantum Algebra · Mathematics 2009-10-31 Bertfried Fauser

A fundamental problem in quantum information is to describe efficiently multipartite quantum states. An efficient representation in terms of graphs exists for several families of quantum states (graph, cluster, stabilizer states),…

Quantum Physics · Physics 2012-07-04 Radu Ionicioiu , Tim P. Spiller

In this book authors for the first time introduce the notion of strong neutrosophic graphs. They are very different from the usual graphs and neutrosophic graphs. Using these new structures special subgraph topological spaces are defined.…

Artificial Intelligence · Computer Science 2016-11-03 W. B. Vasantha Kandasamy , Ilanthenral K , Florentin Smarandache

The Ben Geloun-Rivasseau quantum field theoretical model is the first tensor model shown to be perturbatively renormalizable. We define here an appropriate Hopf algebra describing the combinatorics of this new tensorial renormalization. The…

General Relativity and Quantum Cosmology · Physics 2014-08-15 Matti Raasakka , Adrian Tanasa

We introduce Quantum Graph Neural Networks (QGNN), a new class of quantum neural network ansatze which are tailored to represent quantum processes which have a graph structure, and are particularly suitable to be executed on distributed…

The tensor categories of oriented Kauffman diagrams are studied with description of fiber functors on them as well as the associated Hopf algebras.

Quantum Algebra · Mathematics 2007-05-23 Shigeru Yamagami

Graphs are a basic tool for the representation of modern data. The richness of the topological information contained in a graph goes far beyond its mere interpretation as a one-dimensional simplicial complex. We show how topological…

Combinatorics · Mathematics 2018-10-11 Mattia G. Bergomi , Massimo Ferri , Lorenzo Zuffi

Heterogeneous graphs generally refers to graphs with different types of nodes and edges. A common approach for extracting useful information from heterogeneous graphs is to use meta-graphs, which can be seen as a special kind of directed…

Machine Learning · Computer Science 2023-09-04 Hansi Yang , Peiyu Zhang , Quanming Yao

We give a definition of a noncommutative torsor by a subset of the axioms previously given by Grunspan. We show that noncommutative torsors are an equivalent description of Hopf-Galois objects (without specifying the Hopf algebra). In…

Quantum Algebra · Mathematics 2007-05-23 Peter Schauenburg