Geometry of Interaction for ZX-Diagrams
- URL: http://arxiv.org/abs/2206.10916v2
- Date: Wed, 3 Aug 2022 14:06:07 GMT
- Title: Geometry of Interaction for ZX-Diagrams
- Authors: Kostia Chardonnet, Beno\^it Valiron, Renaud Vilmart
- Abstract summary: ZX-Calculus is a versatile graphical language for quantum computation equipped with an equational theory.
We propose a token-machine-based asynchronous model of both pure ZX-Calculus and its extension to mixed processes.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: ZX-Calculus is a versatile graphical language for quantum computation
equipped with an equational theory. Getting inspiration from Geometry of
Interaction, in this paper we propose a token-machine-based asynchronous model
of both pure ZX-Calculus and its extension to mixed processes. We also show how
to connect this new semantics to the usual standard interpretation of
ZX-diagrams. This model allows us to have a new look at what ZX-diagrams
compute, and give a more local, operational view of the semantics of
ZX-diagrams.
Related papers
- Equivalence Classes of Quantum Error-Correcting Codes [49.436750507696225]
Quantum error-correcting codes (QECC's) are needed to combat the inherent noise affecting quantum processes.
We represent QECC's in a form called a ZX diagram, consisting of a tensor network.
arXiv Detail & Related papers (2024-06-17T20:48:43Z) - Simple qudit ZX and ZH calculi, via integrals [0.0]
ZX calculus and ZH calculus use diagrams to denote quantum operations, using rewrite rules' to transform between diagrams which denote the same operator through a functorial semantic map.
We describe semantic maps for ZX and ZH diagrams, well-suited to analyse unitary circuits and measurements on qudits of any fixed dimension D>1 as a single ZXH-calculus'
We demonstrate rewrite rules for the stabiliser fragment' of the ZX calculus and a multicharacter fragment' of the ZH calculus.
arXiv Detail & Related papers (2023-04-06T18:00:31Z) - Joint Graph and Vertex Importance Learning [47.249968772606145]
We propose a novel method to learn a graph with smaller edge weight upper bounds compared to Laplacian approaches.
Experimentally, our approach yields much sparser graphs compared to a Laplacian approach, with a more interpretable model.
arXiv Detail & Related papers (2023-03-15T12:12:13Z) - Qudit lattice surgery [91.3755431537592]
We observe that lattice surgery, a model of fault-tolerant qubit computation, generalises straightforwardly to arbitrary finite-dimensional qudits.
We relate the model to the ZX-calculus, a diagrammatic language based on Hopf-Frobenius algebras.
arXiv Detail & Related papers (2022-04-27T23:41:04Z) - Addition and Differentiation of ZX-diagrams [0.0]
We introduce a general, inductive definition of the addition of ZX-diagrams.
We provide an inductive differentiation of ZX-diagrams.
We also apply our results to deduce a diagram for an Ising Hamiltonian.
arXiv Detail & Related papers (2022-02-23T09:52:26Z) - Differentiating and Integrating ZX Diagrams with Applications to Quantum Machine Learning [0.09831489366502298]
We elevate ZX to an analytical perspective by realising differentiation and integration entirely within the framework of ZX-calculus.
We explicitly illustrate the new analytic framework of ZX-calculus by applying it in context of quantum machine learning for the analysis of barren plateaus.
arXiv Detail & Related papers (2022-01-31T13:59:28Z) - Learning Graphon Autoencoders for Generative Graph Modeling [91.32624399902755]
Graphon is a nonparametric model that generates graphs with arbitrary sizes and can be induced from graphs easily.
We propose a novel framework called textitgraphon autoencoder to build an interpretable and scalable graph generative model.
A linear graphon factorization model works as a decoder, leveraging the latent representations to reconstruct the induced graphons.
arXiv Detail & Related papers (2021-05-29T08:11:40Z) - GraphSVX: Shapley Value Explanations for Graph Neural Networks [81.83769974301995]
Graph Neural Networks (GNNs) achieve significant performance for various learning tasks on geometric data.
In this paper, we propose a unified framework satisfied by most existing GNN explainers.
We introduce GraphSVX, a post hoc local model-agnostic explanation method specifically designed for GNNs.
arXiv Detail & Related papers (2021-04-18T10:40:37Z) - ZX-calculus for the working quantum computer scientist [0.0]
The ZX-calculus is a graphical language for reasoning about quantum computation.
This review gives a gentle introduction to the ZX-calculus suitable for those familiar with the basics of quantum computing.
The latter sections give a condensed overview of the literature on the ZX-calculus.
arXiv Detail & Related papers (2020-12-27T15:54:25Z) - Hamiltonian systems, Toda lattices, Solitons, Lax Pairs on weighted
Z-graded graphs [62.997667081978825]
We identify conditions which allow one to lift one dimensional solutions to solutions on graphs.
We show that even for a simple example of a topologically interesting graph the corresponding non-trivial Lax pairs and associated unitary transformations do not lift to a Lax pair on the Z-graded graph.
arXiv Detail & Related papers (2020-08-11T17:58:13Z) - Entanglement and Quaternions: The graphical calculus ZQ [0.0]
We introduce the graphical calculus ZQ, which uses quaternions to represent arbitrary rotations.
We show that this calculus is sound and complete for qubit quantum computing, while also showing that a fully spider-based representation would have been impossible.
arXiv Detail & Related papers (2020-03-22T21:34:59Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.