Quantum Federated Learning for Metaverse: Analysis, Design, and Implementation

Dev Gurung, Shiva Raj Pokhrel, Gang Li

Abstract: We present a novel decentralized and trustworthy Quantum Federated Learning (QFL) framework tailored for the emerging Metaverse. This virtual environment, enabling social interaction, gaming, and commerce, demands secure and transparent systems. By integrating blockchain, our QFL framework ensures integrity, resilience, and transparency. Comparative analysis with classical Federated Learning (CFL) highlights its practicality and advantages in distributed settings. New insights discovered emphasize the importance of decentralized systems for the Metaverse’s evolution, with a blockchain-based QFL application demonstrated in a hybrid model. Our evaluation, implementation details and code are publicly available.

External IDs:dblp:journals/tnsm/GurungPL25