MosaiQ: Quantum Generative Adversarial Networks for Image Generation on
  NISQ Computers
Daniel Silver Tirthak Patel William Cutler Aditya Ranjan Harshitta Gandhi Devesh Tiwari
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.