MosaiQ: Quantum Generative Adversarial Networks for Image Generation on NISQ Computers
Daniel Silver, Aditya Ranjan, Tirthak Patel, Harshitta Gandhi, William W. Cutler, Devesh Tiwari
Abstract
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.
Topics & Concepts
Computer scienceAdversarial systemGenerative grammarQuantum computerTheoretical computer scienceImage (mathematics)QuantumComputer engineeringArtificial intelligenceQuantum mechanicsPhysicsComputational Physics and Python ApplicationsGenerative Adversarial Networks and Image SynthesisAdvanced Image Processing Techniques