mlsanityData to 14 Oct 2026

Towards Quantum Federated Learning

arXiv 2306.09912 ↗First posted 16 Jun 2023cs.LG quant-phcited by 20

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Abstract (arXiv)

Quantum Federated Learning (QFL) is an emerging interdisciplinary field that merges the principles of Quantum Computing (QC) and Federated Learning (FL), with the goal of leveraging quantum technologies to enhance privacy, security, and efficiency in the learning process. Currently, there is no comprehensive survey for this interdisciplinary field. This review offers a thorough, holistic examination of QFL. We aim to provide a comprehensive understanding of the principles, techniques, and emerging applications of QFL. We discuss the current state of research in this rapidly evolving field, identify challenges and opportunities associated with integrating these technologies, and outline future directions and open research questions. We propose a unique taxonomy of QFL techniques, categorized according to their characteristics and the quantum techniques employed. As the field of QFL continues to progress, we can anticipate further breakthroughs and applications across various industries, driving innovation and addressing challenges related to data privacy, security, and resource optimization. This review serves as a first-of-its-kind comprehensive guide for researchers and practitioners interested in understanding and advancing the field of QFL.

Key facts. Cited by 20 papers in the map (data through 14 Oct 2026). Builds on 32 of its 127 references that are in the map. First posted on arXiv 16 Jun 2023.

Builds on

32 of 127 references.

References · 32

  1. 2016Communication-Efficient Learning of Deep Networks from Decentralized Datacited by 7,669
  2. 2016Federated Learning: Strategies for Improving Communication Efficiencycited by 1,475
  3. 2021Towards Personalized Federated Learningcited by 464
  4. 2018Adaptive Federated Learning in Resource Constrained Edge Computing Systemscited by 409
  5. 2018Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edgecited by 352
  6. 2023Challenges and Opportunities in Quantum Machine Learningcited by 203
  7. 2021Federated Learning for Open Bankingcited by 141
  8. 2018Quantum generative adversarial networkscited by 128
  9. 2020Quantum Long Short-Term Memorycited by 120
  10. 2019Transfer learning in hybrid classical-quantum neural networkscited by 114
  11. 2021Federated Quantum Machine Learningcited by 82
  12. 2020Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognitioncited by 57
20 more
  1. 2022Vertical Federated Learning: Challenges, Methodologies and Experimentscited by 55
  2. 2021Quantum Federated Learning with Quantum Datacited by 53
  3. 2021Quantum federated learning through blind quantum computingcited by 44
  4. 2021Federated Learning Meets Natural Language Processing: A Surveycited by 43
  5. 2022When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computingcited by 40
  6. 2022Slimmable Quantum Federated Learningcited by 23
  7. 2021QuantumFed: A Federated Learning Framework for Collaborative Quantum Trainingcited by 22
  8. 2022Federated Learning with Quantum Secure Aggregationcited by 21
  9. 2021Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challengescited by 17
  10. 2022Decentral and Incentivized Federated Learning Frameworks: A Systematic Literature Reviewcited by 15
  11. 2022Non-IID Quantum Federated Learning with One-shot Communication Complexitycited by 15
  12. 2022Federated Quantum Natural Gradient Descent for Quantum Federated Learningcited by 14
  13. 2023Optimizing Quantum Federated Learning Based on Federated Quantum Natural Gradient Descentcited by 14
  14. 2022Quantum Distributed Deep Learning Architectures: Models, Discussions, and Applicationscited by 13
  15. 2022A Hybrid Quantum-Classical Neural Network Architecture for Binary Classificationcited by 11
  16. 2022Adaptive Resource Allocation in Quantum Key Distribution (QKD) for Federated Learningcited by 7
  17. 2022Privacy-preserving Intelligent Resource Allocation for Federated Edge Learning in Quantum Internetcited by 5
  18. 2022Quantum Split Neural Network Learning using Cross-Channel Poolingcited by 4
  19. 2022Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Codingcited by 4
  20. 2023Post Quantum Secure Blockchain-based Federated Learning for Mobile Edge Computingcited by 4

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 6; 2025: 9; 2026: 1.

20 papers.

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  1. 2024Advances and Open Challenges in Federated Foundation Modelscited by 36
  2. 2024FedQNN: Federated Learning using Quantum Neural Networkscited by 20
  3. 2023Hybrid quantum image classification and federated learning for hepatic steatosis diagnosiscited by 15
  4. 2023Privacy-preserving quantum federated learning via gradient hidingcited by 15
  5. 2023Federated Quantum Long Short-term Memory (FedQLSTM)cited by 15
  6. 2025Quantum Federated Learning: A Comprehensive Surveycited by 10
  7. 2024Federated Learning with Quantum Computing and Fully Homomorphic Encryption: A Novel Computing Paradigm Shift in Privacy-Preserving MLcited by 8
  8. 2024MQFL-FHE: Multimodal Quantum Federated Learning Framework with Fully Homomorphic Encryptioncited by 7
  9. 2023Quantum Federated Learning: Analysis, Design and Implementation Challengescited by 6
  10. 2025Experimentally validated quantum-secure federated learning over a multi-user quantum networkcited by 5
  11. 2025When Federated Learning Meets Quantum Computing: Survey and Research Opportunitiescited by 5
  12. 2024Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data Sourcescited by 4
8 more
  1. 2025Adversarial Robustness in Distributed Quantum Machine Learningcited by 2
  2. 2025SimQFL: A Quantum Federated Learning Simulator with Real-Time Visualizationcited by 2
  3. 2025New Insights on Unfolding and Fine-tuning Quantum Federated Learningcited by 1
  4. 2024Quantum-machine-assisted Drug Discoverycited by 0
  5. 2025orb-QFL: Orbital Quantum Federated Learningcited by 0
  6. 2025Towards Heterogeneous Quantum Federated Learning: Challenges and Solutionscited by 0
  7. 2025Towards Explainable Quantum AI: Informing the Encoder Selection of Quantum Neural Networks via Visualizationcited by 0
  8. 2026Can Quantum Federated Learning Withstand Circuit-Level Backdoors?cited by 0