mlsanityData to 7 Oct 2026

Monte Carlo Tree Search based Hybrid Optimization of Variational Quantum Circuits

arXiv 2203.16707 ↗First posted 30 Mar 2022quant-ph cond-mat.quant-gas cs.LGcited by 10

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Abstract (arXiv)

Variational quantum algorithms stand at the forefront of simulations on near-term and future fault-tolerant quantum devices. While most variational quantum algorithms involve only continuous optimization variables, the representational power of the variational ansatz can sometimes be significantly enhanced by adding certain discrete optimization variables, as is exemplified by the generalized quantum approximate optimization algorithm (QAOA). However, the hybrid discrete-continuous optimization problem in the generalized QAOA poses a challenge to the optimization. We propose a new algorithm called MCTS-QAOA, which combines a Monte Carlo tree search method with an improved natural policy gradient solver to optimize the discrete and continuous variables in the quantum circuit, respectively. We find that MCTS-QAOA has excellent noise-resilience properties and outperforms prior algorithms in challenging instances of the generalized QAOA.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 29 of its 95 references that are in the map. First posted on arXiv 30 Mar 2022.

Builds on

29 of 95 references.

References · 29

  1. 2015Continuous control with deep reinforcement learningcited by 3,279
  2. 2018DARTS: Differentiable Architecture Searchcited by 1,782
  3. 2016Neural Architecture Search with Reinforcement Learningcited by 1,489
  4. 2019Mastering Atari, Go, Chess and Shogi by Planning with a Learned Modelcited by 1,327
  5. 2018Soft Actor-Critic Algorithms and Applicationscited by 1,179
  6. 2020Variational Quantum Algorithmscited by 687
  7. 2018ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardwarecited by 666
  8. 2018Maximum a Posteriori Policy Optimisationcited by 318
  9. 2021Mastering Atari Games with Limited Datacited by 235
  10. 2020AutoML-Zero: Evolving Machine Learning Algorithms From Scratchcited by 137
  11. 2021QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuitscited by 97
  12. 2020Learning Search Space Partition for Black-box Optimization using Monte Carlo Tree Searchcited by 87
17 more
  1. 2021Conservative Objective Models for Effective Offline Model-Based Optimizationcited by 87
  2. 2018Simple random search provides a competitive approach to reinforcement learningcited by 75
  3. 2021Quantum Architecture Search via Deep Reinforcement Learningcited by 58
  4. 2020Self-Paced Deep Reinforcement Learningcited by 49
  5. 2018Universal Quantum Control through Deep Reinforcement Learningcited by 44
  6. 2020Continuous-Discrete Reinforcement Learning for Hybrid Control in Roboticscited by 42
  7. 2019Discrete and Continuous Action Representation for Practical RL in Video Gamescited by 34
  8. 2018Optimizing Quantum Error Correction Codes with Reinforcement Learningcited by 28
  9. 2021Enabling Multi-programming Mechanism for Quantum Computing in the NISQ Eracited by 22
  10. 2020Natural Evolutionary Strategies for Variational Quantum Computationcited by 15
  11. 2020Policy Gradient based Quantum Approximate Optimization Algorithmcited by 14
  12. 2018Fidelity-based Probabilistic Q-learning for Control of Quantum Systemscited by 10
  13. 2018Measurement-based adaptation protocol with quantum reinforcement learningcited by 6
  14. 2020Noise-Robust End-to-End Quantum Control using Deep Autoregressive Policy Networkscited by 6
  15. 2020Active Learning Approach to Optimization of Experimental Controlcited by 4
  16. 2018Taking gradients through experiments: LSTMs and memory proximal policy optimization for black-box quantum controlcited by 3
  17. 2018Glassy Phase of Optimal Quantum Controlcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 0; 2024: 6; 2025: 1; 2026: 1.

10 papers.

  1. 2024Quantum Circuit Optimization with AlphaTensorcited by 36
  2. 2024Quantum Architecture Search: A Surveycited by 31
  3. 2024Differentiable Quantum Architecture Search in Asynchronous Quantum Reinforcement Learningcited by 13
  4. 2024'Eliv'agar: Efficient Quantum Circuit Search for Classificationcited by 12
  5. 2024Quantum Machine Learning Architecture Search via Deep Reinforcement Learningcited by 12
  6. 2024Evolutionary Optimization for Designing Variational Quantum Circuits with High Model Capacitycited by 9
  7. 2022QuACK: Accelerating Gradient-Based Quantum Optimization with Koopman Operator Learningcited by 7
  8. 2022Decoding surface codes with deep reinforcement learning and probabilistic policy reusecited by 1
  9. 2025Quantum Architecture Search for Solving Quantum Machine Learning Taskscited by 0
  10. 2026Classical State Preparation for Variational Quantum Algorithms via Reinforcement Learningcited by 0