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

arXiv: https://arxiv.org/abs/2306.11297 · HTML: https://mlsanity.com/paper/2306.11297/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 20 of its 43 references that are in the map.
- First posted on arXiv 20 Jun 2023.

## Builds on (most cited first, 20 of 20)

- [On the Convergence of FedAvg on Non-IID Data](https://mlsanity.com/paper/1907.02189/) (2019)
- [data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language](https://mlsanity.com/paper/2202.03555/) (2022)
- [Variational Quantum Algorithms](https://mlsanity.com/paper/2012.09265/) (2020)
- [The power of quantum neural networks](https://mlsanity.com/paper/2011.00027/) (2020)
- [Quantum machine learning beyond kernel methods](https://mlsanity.com/paper/2110.13162/) (2021)
- [Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognition](https://mlsanity.com/paper/2010.13309/) (2020)
- [Quantum Federated Learning with Quantum Data](https://mlsanity.com/paper/2106.00005/) (2021)
- [Slimmable Quantum Federated Learning](https://mlsanity.com/paper/2207.10221/) (2022)
- [QuantumFed: A Federated Learning Framework for Collaborative Quantum Training](https://mlsanity.com/paper/2106.09109/) (2021)
- [Advances in Quantum Deep Learning: An Overview](https://mlsanity.com/paper/2005.04316/) (2020)
- [Federated Learning with Quantum Secure Aggregation](https://mlsanity.com/paper/2207.07444/) (2022)
- [Metaverse for Social Good: A University Campus Prototype](https://mlsanity.com/paper/2108.08985/) (2021)
- [Fusing Blockchain and AI with Metaverse: A Survey](https://mlsanity.com/paper/2201.03201/) (2022)
- [Robust Blockchained Federated Learning with Model Validation and Proof-of-Stake Inspired Consensus](https://mlsanity.com/paper/2101.03300/) (2021)
- [Federated Quantum Natural Gradient Descent for Quantum Federated Learning](https://mlsanity.com/paper/2209.00564/) (2022)
- [HFedMS: Heterogeneous Federated Learning with Memorable Data Semantics in Industrial Metaverse](https://mlsanity.com/paper/2211.03300/) (2022)
- [Quantum Distributed Deep Learning Architectures: Models, Discussions, and Applications](https://mlsanity.com/paper/2202.11200/) (2022)
- [6G-enabled Edge AI for Metaverse: Challenges, Methods, and Future Research Directions](https://mlsanity.com/paper/2204.06192/) (2022)
- [A Hybrid Quantum-Classical Neural Network Architecture for Binary Classification](https://mlsanity.com/paper/2201.01820/) (2022)
- [Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learning](https://mlsanity.com/paper/2208.11270/) (2022)

## Built on by (most cited first, 5 of 5)

- [Quantum Federated Learning: A Comprehensive Survey](https://mlsanity.com/paper/2508.15998/) (2025)
- [Prospects of Privacy Advantage in Quantum Machine Learning](https://mlsanity.com/paper/2405.08801/) (2024)
- [Adversarial Robustness in Distributed Quantum Machine Learning](https://mlsanity.com/paper/2508.11848/) (2025)
- [Quantum Federated Learning: Architectural Elements and Future Directions](https://mlsanity.com/paper/2510.17642/) (2025)
- [New Insights on Unfolding and Fine-tuning Quantum Federated Learning](https://mlsanity.com/paper/2506.20016/) (2025)

## Abstract (arXiv)

With the emerging developments of the Metaverse, a virtual world where people can interact, socialize, play, and conduct their business, it has become critical to ensure that the underlying systems are transparent, secure, and trustworthy. To this end, we develop a decentralized and trustworthy quantum federated learning (QFL) framework. The proposed QFL leverages the power of blockchain to create a secure and transparent system that is robust against cyberattacks and fraud. In addition, the decentralized QFL system addresses the risks associated with a centralized server-based approach. With extensive experiments and analysis, we evaluate classical federated learning (CFL) and QFL in a distributed setting and demonstrate the practicality and benefits of the proposed design. Our theoretical analysis and discussions develop a genuinely decentralized financial system essential for the Metaverse. Furthermore, we present the application of blockchain-based QFL in a hybrid metaverse powered by a metaverse observer and world model. Our implementation details and code are publicly available 1.