MosaiQ: Quantum Generative Adversarial Networks for Image Generation on NISQ Computers
Abstract
MosaiQ is a high-quality quantum image generation GAN framework designed for execution on current NISQ quantum computers, addressing deficiencies in previous quantum image generation techniques.
Quantum machine learning and vision have come to the fore recently, with hardware advances enabling rapid advancement in the capabilities of quantum machines. Recently, quantum image generation has been explored with many potential advantages over non-quantum techniques; however, previous techniques have suffered from poor quality and robustness. To address these problems, we introduce, MosaiQ, a high-quality quantum image generation GAN framework that can be executed on today's Near-term Intermediate Scale Quantum (NISQ) computers.
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