Finite-Dimensional ZX-Calculus for Loop Quantum Gravity
- URL: http://arxiv.org/abs/2511.15966v1
- Date: Thu, 20 Nov 2025 01:36:52 GMT
- Title: Finite-Dimensional ZX-Calculus for Loop Quantum Gravity
- Authors: Ben Priestley,
- Abstract summary: We offer a more radical rephrasing of spin network calculations by translating them into the finite-dimensional ZX-calculus.<n>We derive the forms for several fundamental LQG objects in the finite-dimensional ZX-calculus for the first time.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Loop quantum gravity (LQG) attempts to unify general relativity with quantum physics to offer a complete description of the universe by quantising spacetime geometry, but the numerical calculations we encounter are extraordinarily difficult. Progress has been made in the covariant formulation of LQG, but the tools do not carry over to the canonical formulation. These tools are graphical by nature, describing space with spin networks to make calculations in LQG more intuitive to the human hand. Recently, a new notation for working with spin networks has been used by arXiv:2412.20272 to offer the first accurate numerical results in canonical LQG by allowing the underlying graphs to change throughout the calculation, though they are forced to concede visual intuitiveness. In this thesis, we offer a more radical rephrasing of spin network calculations by translating them into the finite-dimensional ZX-calculus, extending previous attempts to translate into the standard (qubit) ZX-calculus (arXiv:2111.03114). Specifically, we derive the mixed-dimensional ZX-diagrams representing the generating objects of spin networks and the rules for the Penrose Spin Calculus (arXiv:2511.06012), and use these to present the ZX-form and correctness of "loop removal". We also derive the forms for several fundamental LQG objects in the finite-dimensional ZX-calculus for the first time. This gives us a high-level, intuitive graphical language that retains a flexibility to handle changing graph structures, and thus we argue positions the PSC as the new definitive language for canonical LQG. Furthermore, we investigate the possibility for a matrix-like normal form for spin networks deriving from a novel perspective of the PSC in terms of W-nodes.
Related papers
- Beyond Penrose tensor diagrams with the ZX calculus: Applications to quantum computing, quantum machine learning, condensed matter physics, and quantum gravity [0.0]
We introduce the Spin-ZX calculus as an elevation of Penrose's diagrams and associated binor calculus.<n>We apply it to: permutational quantum computing, quantum machine learning, condensed matter physics, and quantum gravity.<n>Our results establish the Spin-ZX calculus as a powerful tool for representing and computing with SU(2) systems graphically.
arXiv Detail & Related papers (2025-11-08T13:42:53Z) - The Focked-up ZX Calculus: Picturing Continuous-Variable Quantum Computation [0.0]
We formulate a graphical language for continuous-variable quantum computation.
We present exciting new graphical rules capturing heftier CVQC interactions.
Applying our calculus for quantum error correction, we derive graphical representations of the Gottesman-Kitaev-Preskill code encoder, syndrome measurement, and magic state distillation of Hadamard eigenstates.
arXiv Detail & Related papers (2024-06-05T03:56:18Z) - ZX-calculus is Complete for Finite-Dimensional Hilbert Spaces [0.09831489366502298]
The ZX-calculus is a graphical language for quantum computing and quantum information theory.<n>We prove completeness of finite-dimensional ZX-calculus, incorporating only the mixed-dimensional Z-spider and the qudit X-spider as generators.<n>Our approach builds on the completeness of another graphical language, the finite-dimensional ZW-calculus, with direct translations between these two calculi.
arXiv Detail & Related papers (2024-05-17T16:35:07Z) - Tempered Calculus for ML: Application to Hyperbolic Model Embedding [70.61101116794549]
Most mathematical distortions used in ML are fundamentally integral in nature.
In this paper, we unveil a grounded theory and tools which can help improve these distortions to better cope with ML requirements.
We show how to apply it to a problem that has recently gained traction in ML: hyperbolic embeddings with a "cheap" and accurate encoding along the hyperbolic vsean scale.
arXiv Detail & Related papers (2024-02-06T17:21:06Z) - Transolver: A Fast Transformer Solver for PDEs on General Geometries [66.82060415622871]
We present Transolver, which learns intrinsic physical states hidden behind discretized geometries.
By calculating attention to physics-aware tokens encoded from slices, Transovler can effectively capture intricate physical correlations.
Transolver achieves consistent state-of-the-art with 22% relative gain across six standard benchmarks and also excels in large-scale industrial simulations.
arXiv Detail & Related papers (2024-02-04T06:37:38Z) - Machine learning detects terminal singularities [49.1574468325115]
Q-Fano varieties are positively curved shapes which have Q-factorial terminal singularities.
Despite their importance, the classification of Q-Fano varieties remains unknown.
In this paper we demonstrate that machine learning can be used to understand this classification.
arXiv Detail & Related papers (2023-10-31T13:51:24Z) - The Basis of Design Tools for Quantum Computing: Arrays, Decision
Diagrams, Tensor Networks, and ZX-Calculus [55.58528469973086]
Quantum computers promise to efficiently solve important problems classical computers never will.
A fully automated quantum software stack needs to be developed.
This work provides a look "under the hood" of today's tools and showcases how these means are utilized in them, e.g., for simulation, compilation, and verification of quantum circuits.
arXiv Detail & Related papers (2023-01-10T19:00:00Z) - From Quantum Graph Computing to Quantum Graph Learning: A Survey [86.8206129053725]
We first elaborate the correlations between quantum mechanics and graph theory to show that quantum computers are able to generate useful solutions.
For its practicability and wide-applicability, we give a brief review of typical graph learning techniques.
We give a snapshot of quantum graph learning where expectations serve as a catalyst for subsequent research.
arXiv Detail & Related papers (2022-02-19T02:56:47Z) - Towards Quantum Graph Neural Networks: An Ego-Graph Learning Approach [47.19265172105025]
We propose a novel hybrid quantum-classical algorithm for graph-structured data, which we refer to as the Ego-graph based Quantum Graph Neural Network (egoQGNN)
egoQGNN implements the GNN theoretical framework using the tensor product and unity matrix representation, which greatly reduces the number of model parameters required.
The architecture is based on a novel mapping from real-world data to Hilbert space.
arXiv Detail & Related papers (2022-01-13T16:35:45Z) - Simplification Strategies for the Qutrit ZX-Calculus [0.0]
The ZX-calculus is a graphical language for suitably represented tensor networks, called ZX-diagrams.
The ZX-calculus has found applications in reasoning about quantum circuits, condensed matter systems, quantum algorithms, quantum error codes, and counting problems.
arXiv Detail & Related papers (2021-03-11T19:17:28Z) - AKLT-states as ZX-diagrams: diagrammatic reasoning for quantum states [1.1470070927586016]
We introduce the ZXH-calculus, a graphical language that we use to represent and reason about many-body states entirely graphically.
We show how we recover the AKLT matrix-product state representation, the existence of topologically protected edge states, and the non-vanishing of a string order parameter.
We also provide an alternative proof that the 2D AKLT state on a hexagonal lattice can be reduced to a graph state, demonstrating that it is a universal quantum computing resource.
arXiv Detail & Related papers (2020-12-02T14:03:27Z) - PBS-Calculus: A Graphical Language for Coherent Control of Quantum
Computations [77.34726150561087]
We introduce the PBS-calculus to represent and reason on quantum computations involving coherent control of quantum operations.
We equip the language with an equational theory, which is proved to be sound and complete.
We consider applications like the implementation of controlled permutations and the unrolling of loops.
arXiv Detail & Related papers (2020-02-21T16:15:58Z)
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.