mlsanityData to 14 Oct 2026

Quantum Convolutional Neural Networks for High Energy Physics Data Analysis

arXiv 2012.12177 ↗First posted 22 Dec 2020cs.LG cs.AI hep-excited by 64

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Abstract (arXiv)

This work presents a quantum convolutional neural network (QCNN) for the classification of high energy physics events. The proposed model is tested using a simulated dataset from the Deep Underground Neutrino Experiment. The proposed architecture demonstrates the quantum advantage of learning faster than the classical convolutional neural networks (CNNs) under a similar number of parameters. In addition to faster convergence, the QCNN achieves greater test accuracy compared to CNNs. Based on experimental results, it is a promising direction to study the application of QCNN and other quantum machine learning models in high energy physics and additional scientific fields.

Key facts. Cited by 64 papers in the map (data through 14 Oct 2026). First posted on arXiv 22 Dec 2020.

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Citing papers per year: 2021: 9; 2022: 5; 2023: 9; 2024: 18; 2025: 18; 2026: 5.

64 papers.

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  1. 2021Federated Quantum Machine Learningcited by 82
  2. 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 60
  3. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  4. 2024Quantum Convolutional Neural Networks are Effectively Classically Simulablecited by 37
  5. 2021Quantum machine learning with differential privacycited by 31
  6. 2023Machine Learning for Anomaly Detection in Particle Physicscited by 30
  7. 2021Quantum Architecture Search via Continual Reinforcement Learningcited by 22
  8. 2021Hybrid Quantum-Classical Graph Convolutional Networkcited by 21
  9. 2023Asynchronous training of quantum reinforcement learningcited by 20
  10. 2023Federated Quantum Machine Learning with Differential Privacycited by 17
  11. 2023Federated Quantum Long Short-term Memory (FedQLSTM)cited by 15
  12. 2025Learning to Measure Quantum Neural Networkscited by 15
38 more
  1. 2022Reservoir Computing via Quantum Recurrent Neural Networkscited by 14
  2. 2024Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learningcited by 14
  3. 2024Quantum-Train-Based Distributed Multi-Agent Reinforcement Learningcited by 14
  4. 2025Toward Large-Scale Distributed Quantum Long Short-Term Memory with Modular Quantum Computerscited by 14
  5. 2022Quantum Neural Network Classifiers: A Tutorialcited by 13
  6. 2024Quantum Machine Learning Architecture Search via Deep Reinforcement Learningcited by 13
  7. 2021Quantum Quantile Mechanics: Solving Stochastic Differential Equations for Generating Time-Seriescited by 10
  8. 2023Unravelling physics beyond the standard model with classical and quantum anomaly detectioncited by 9
  9. 2024Quantum Gradient Class Activation Map for Model Interpretabilitycited by 9
  10. 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
  11. 2024An Introduction to Quantum Reinforcement Learning (QRL)cited by 7
  12. 2025Adaptive Non-local Observable on Quantum Neural Networkscited by 7
  13. 2025Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generationcited by 7
  14. 2025Learning to Program Quantum Measurements for Machine Learningcited by 7
  15. 2023QAmplifyNet: Pushing the Boundaries of Supply Chain Backorder Prediction Using Interpretable Hybrid Quantum-Classical Neural Networkcited by 6
  16. 2025Efficient Quantum Convolutional Neural Networks for Image Classification: Overcoming Hardware Constraintscited by 5
  17. 2022Implementation of Trained Factorization Machine Recommendation System on Quantum Annealercited by 4
  18. 2023Quantum Convolutional Neural Networks for Multi-Channel Supervised Learningcited by 4
  19. 2024Resource-efficient equivariant quantum convolutional neural networkscited by 4
  20. 2022Classical ensemble of Quantum-classical ML algorithms for Phishing detection in Ethereum transaction networkscited by 3
  21. 2023Quantum-Enhanced Support Vector Machine for Large-Scale Stellar Classification with GPU Accelerationcited by 3
  22. 2024Jet Discrimination with Quantum Complete Graph Neural Networkcited by 3
  23. 2025Transfer Learning Analysis of Variational Quantum Circuitscited by 3
  24. 2025Introduction to Quantum Machine Learning and Quantum Architecture Searchcited by 3
  25. 2025Addressing the Current Challenges of Quantum Machine Learning through Multi-Chip Ensemblescited by 3
  26. 2024ResQuNNs: Towards Enabling Deep Learning in Quantum Convolution Neural Networkscited by 2
  27. 2024Quantum Adjoint Convolutional Layers for Effective Data Representationcited by 2
  28. 2024Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learningcited by 2
  29. 2025QGAN-based data augmentation for hybrid quantum-classical neural networkscited by 2
  30. 2025Breaking Through Barren Plateaus: Reinforcement Learning Initializations for Deep Variational Quantum Circuitscited by 2
  31. 2025Meta-Learning for Quantum Optimization via Quantum Sequence Modelcited by 2
  32. 2021Feasible Architecture for Quantum Fully Convolutional Networkscited by 1
  33. 2023Hybrid quantum-classical convolutional neural network for phytoplankton classificationcited by 1
  34. 2024Multi-GPU-Enabled Hybrid Quantum-Classical Workflow in Quantum-HPC Middleware: Applications in Quantum Simulationscited by 1
  35. 2024Image and Point-cloud Classification for Jet Analysis in High-Energy Physics: A surveycited by 1
  36. 2024TriQXNet: Forecasting Dst Index from Solar Wind Data Using an Interpretable Parallel Classical-Quantum Framework with Uncertainty Quantificationcited by 1
  37. 2024Leveraging Pre-Trained Neural Networks to Enhance Machine Learning with Variational Quantum Circuitscited by 1
  38. 2025VQC-MLPNet: An Unconventional Hybrid Quantum-Classical Architecture for Scalable and Robust Quantum Machine Learningcited by 1

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