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Quantum Architecture Search via Deep Reinforcement Learning

arXiv 2104.07715 ↗First posted 15 Apr 2021quant-ph cs.AI cs.LGcited by 58

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Abstract (arXiv)

Recent advances in quantum computing have drawn considerable attention to building realistic application for and using quantum computers. However, designing a suitable quantum circuit architecture requires expert knowledge. For example, it is non-trivial to design a quantum gate sequence for generating a particular quantum state with as fewer gates as possible. We propose a quantum architecture search framework with the power of deep reinforcement learning (DRL) to address this challenge. In the proposed framework, the DRL agent can only access the Pauli-X, Y, Z expectation values and a predefined set of quantum operations for learning the target quantum state, and is optimized by the advantage actor-critic (A2C) and proximal policy optimization (PPO) algorithms. We demonstrate a successful generation of quantum gate sequences for multi-qubit GHZ states without encoding any knowledge of quantum physics in the agent. The design of our framework is rather general and can be employed with other DRL architectures or optimization methods to study gate synthesis and compilation for many quantum states.

Key facts. Cited by 58 papers in the map (data through 7 Oct 2026). Builds on 37 of its 94 references that are in the map. First posted on arXiv 15 Apr 2021.

Builds on

37 of 94 references.

References · 37

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25 more
  1. 2016Designing Neural Network Architectures using Reinforcement Learningcited by 277
  2. 2019Variational Quantum Circuits for Deep Reinforcement Learningcited by 165
  3. 2018Quantum generative adversarial networkscited by 128
  4. 2020Quantum Long Short-Term Memorycited by 118
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  8. 2021Reinforcement learning for optimization of variational quantum circuit architecturescited by 76
  9. 2020Reinforcement Learning with Quantum Variational Circuitscited by 74
  10. 2020Quantum Convolutional Neural Networks for High Energy Physics Data Analysiscited by 64
  11. 2020Decentralizing Feature Extraction with Quantum Convolutional Neural Network for Automatic Speech Recognitioncited by 56
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  13. 2018Universal Quantum Control through Deep Reinforcement Learningcited by 44
  14. 2018Path-Level Network Transformation for Efficient Architecture Searchcited by 43
  15. 2018Optimizing Quantum Error Correction Codes with Reinforcement Learningcited by 28
  16. 2020Hybrid quantum-classical classifier based on tensor network and variational quantum circuitcited by 26
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  18. 2021Hybrid Quantum-Classical Graph Convolutional Networkcited by 21
  19. 2021Quantum Self-Supervised Learningcited by 20
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  22. 2020Quantum Circuit Design Searchcited by 13
  23. 2019Quantum Unsupervised and Supervised Learning on Superconducting Processorscited by 9
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 7; 2023: 6; 2024: 17; 2025: 16; 2026: 10.

58 papers.

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  1. 2021Variational Quantum Reinforcement Learning via Evolutionary Optimizationcited by 50
  2. 2024Curriculum reinforcement learning for quantum architecture search under hardware errorscited by 37
  3. 2024Quantum Circuit Optimization with AlphaTensorcited by 36
  4. 2024KANQAS: Kolmogorov-Arnold Network for Quantum Architecture Searchcited by 36
  5. 2024Quantum Architecture Search: A Surveycited by 31
  6. 2021Quantum Architecture Search via Continual Reinforcement Learningcited by 22
  7. 2022Quantum Neural Architecture Search with Quantum Circuits Metric and Bayesian Optimizationcited by 16
  8. 2022Automated Quantum Circuit Design with Nested Monte Carlo Tree Searchcited by 16
  9. 2025Learning to Measure Quantum Neural Networkscited by 15
  10. 2024Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learningcited by 13
  11. 2024Quantum Machine Learning Architecture Search via Deep Reinforcement Learningcited by 12
  12. 2023Enhancing variational quantum state diagonalization using reinforcement learning techniquescited by 11
38 more
  1. 2023Reinforcement Learning for Generative AI: A Surveycited by 11
  2. 2022Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuitscited by 10
  3. 2024Reinforcement learning-assisted quantum architecture search for variational quantum algorithmscited by 10
  4. 2023Challenges for Reinforcement Learning in Quantum Circuit Designcited by 9
  5. 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
  6. 2024Reinforcement learning-based architecture search for quantum machine learningcited by 8
  7. 2024Quantum Circuit Synthesis and Compilation Optimization: Overview and Prospectscited by 8
  8. 2024Reinforcement Learning for Variational Quantum Circuits Designcited by 8
  9. 2025Differentiable Quantum Architecture Search in Quantum-Enhanced Neural Network Parameter Generationcited by 7
  10. 2022Efficient and practical quantum compiler towards multi-qubit systems with deep reinforcement learningcited by 6
  11. 2022Power of Quantum Generative Learningcited by 6
  12. 2023The quantum cost function concentration dependency on the parametrization expressivitycited by 6
  13. 2025TensorRL-QAS: Reinforcement learning with tensor networks for improved quantum architecture searchcited by 6
  14. 2025Quantum Circuit Design using a Progressive Widening Enhanced Monte Carlo Tree Searchcited by 5
  15. 2025Quantum Reinforcement Learning Trading Agent for Sector Rotation in the Taiwan Stock Marketcited by 5
  16. 2024Quantum Architecture Search with Unsupervised Representation Learningcited by 4
  17. 2024MG-Net: Learn to Customize QAOA with Circuit Depth Awarenesscited by 4
  18. 2025Q-Fusion: Diffusing Quantum Circuitscited by 4
  19. 2025Quantum Long Short-term Memory with Differentiable Architecture Searchcited by 4
  20. 2022Review of Ansatz Designing Techniques for Variational Quantum Algorithmscited by 3
  21. 2023Toward Automated Quantum Variational Machine Learningcited by 3
  22. 2025Introduction to Quantum Machine Learning and Quantum Architecture Searchcited by 3
  23. 2025FlowQ-Net: A Generative Framework for Automated Quantum Circuit Designcited by 3
  24. 2026Generative Quantum-inspired Kolmogorov-Arnold Eigensolvercited by 3
  25. 2024Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learningcited by 2
  26. 2025Improving thermal state preparation of Sachdev-Ye-Kitaev model with reinforcement learning on quantum hardwarecited by 2
  27. 2025BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture searchcited by 2
  28. 2025Quantum Reinforcement Learning-Guided Diffusion Model for Image Synthesis via Hybrid Quantum-Classical Generative Model Architecturescited by 2
  29. 2026How to find expressible and trainable parameterized quantum circuits?cited by 2
  30. 2026Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptationcited by 2
  31. 2022Decoding surface codes with deep reinforcement learning and probabilistic policy reusecited by 1
  32. 2024Enhancing Quantum Memory Lifetime with Measurement-Free Local Error Correction and Reinforcement Learningcited by 1
  33. 2025RhoDARTS: Differentiable Quantum Architecture Search with Density Matrix Simulationscited by 1
  34. 2025Neural Architecture Search for Quantum Autoencoderscited by 1
  35. 2026Replay-buffer engineering for noise-aware quantum circuit optimizationcited by 1
  36. 2026Hybrid Quantum-Classical Neural Architecture Searchcited by 1
  37. 2023CQural: A Novel CNN based Hybrid Architecture for Quantum Continual Machine Learningcited by 0
  38. 2024QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuitscited by 0

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