Quantum Diffusion Models

• URL: http://arxiv.org/abs/2311.15444v1
• Date: Sun, 26 Nov 2023 22:07:12 GMT
• Title: Quantum Diffusion Models
• Authors: Andrea Cacioppo, Lorenzo Colantonio, Simone Bordoni and Stefano Giagu
• Abstract summary: We propose a quantum version of a generative diffusion model. In this algorithm, artificial neural networks are replaced with parameterized quantum circuits, in order to directly generate quantum states. We present both a full quantum and a latent quantum version of the algorithm; we also present a conditioned version of these models.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose a quantum version of a generative diffusion model. In this algorithm, artificial neural networks are replaced with parameterized quantum circuits, in order to directly generate quantum states. We present both a full quantum and a latent quantum version of the algorithm; we also present a conditioned version of these models. The models' performances have been evaluated using quantitative metrics complemented by qualitative assessments. An implementation of a simplified version of the algorithm has been executed on real NISQ quantum hardware.

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