Enforcing exact permutation and rotational symmetries in the application of quantum neural network on point cloud datasets Article Swipe

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YOU? · · 2024 · Open Access · · DOI: https://doi.org/10.48550/arxiv.2405.11150

Recent developments in the field of quantum machine learning have promoted the idea of incorporating physical symmetries in the structure of quantum circuits. A crucial milestone in this area is the realization of $S_{n}$-permutation equivariant quantum neural networks (QNN) that are equivariant under permutations of input objects. In this work, we focus on encoding the rotational symmetry of point cloud datasets into the QNN. The key insight of the approach is that all rotationally invariant functions with vector inputs are equivalent to a function with inputs of vector inner products. We provide a novel structure of QNN that is exactly invariant to both rotations and permutations, with its efficacy demonstrated numerically in the problems of two-dimensional image classifications and identifying high-energy particle decays, produced by proton-proton collisions, with the $SO(1,3)$ Lorentz symmetry.

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Artificial Intelligence

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Homogeneous space Point cloud Permutation (music) Point (geometry) Cloud computing Artificial neural network Quantum Computer science Statistical physics Theoretical physics Artificial intelligence Physics Mathematics Quantum mechanics Geometry Operating system Acoustics

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Type: preprint
Language: en
Landing Page: http://arxiv.org/abs/2405.11150
PDF: https://arxiv.org/pdf/2405.11150
OA Status: green
Related Works: 10
OpenAlex ID: https://openalex.org/W4398191698

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DOI: https://doi.org/10.48550/arxiv.2405.11150

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Title: Enforcing exact permutation and rotational symmetries in the application of quantum neural network on point cloud datasets

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Type: preprint

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Language: en

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Publication year: 2024

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Publication date: 2024-05-18

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Authors: Zhelun Li, Lento Nagano, K. Terashi

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Landing page: https://arxiv.org/abs/2405.11150

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PDF URL: https://arxiv.org/pdf/2405.11150

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Concepts: Homogeneous space, Point cloud, Permutation (music), Point (geometry), Cloud computing, Artificial neural network, Quantum, Computer science, Statistical physics, Theoretical physics, Artificial intelligence, Physics, Mathematics, Quantum mechanics, Geometry, Operating system, Acoustics

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