mlsanityData to 7 Oct 2026

Practical and efficient quantum circuit synthesis and transpiling with Reinforcement Learning

arXiv 2405.13196 ↗First posted 21 May 2024quant-ph cs.AIcited by 21

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Abstract (arXiv)

This paper demonstrates the integration of Reinforcement Learning (RL) into quantum transpiling workflows, significantly enhancing the synthesis and routing of quantum circuits. By employing RL, we achieve near-optimal synthesis of Linear Function, Clifford, and Permutation circuits, up to 9, 11 and 65 qubits respectively, while being compatible with native device instruction sets and connectivity constraints, and orders of magnitude faster than optimization methods such as SAT solvers. We also achieve significant reductions in two-qubit gate depth and count for circuit routing up to 133 qubits with respect to other routing heuristics such as SABRE. We find the method to be efficient enough to be useful in practice in typical quantum transpiling pipelines. Our results set the stage for further AI-powered enhancements of quantum computing workflows.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). Builds on 12 of its 53 references that are in the map. First posted on arXiv 21 May 2024.

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12 of 53 references.

References · 12

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2019Optuna: A Next-generation Hyperparameter Optimization Frameworkcited by 2,455
  3. 2020Curriculum Learning for Reinforcement Learning Domains: A Framework and Surveycited by 350
  4. 2018Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Predictioncited by 225
  5. 2024A Thorough Examination of Decoding Methods in the Era of LLMscited by 112
  6. 2024Quantum Circuit Optimization with AlphaTensorcited by 36
  7. 2021Variational quantum compiling with double Q-learningcited by 13
  8. 2022Compiler Optimization for Quantum Computing Using Reinforcement Learningcited by 11
  9. 2021Optimizing Quantum Variational Circuits with Deep Reinforcement Learningcited by 8
  10. 2021Optimal qubit assignment and routing via integer programmingcited by 7
  11. 2022Improving Quantum Computation by Optimized Qubit Routingcited by 3
  12. 2022Towards a SAT Encoding for Quantum Circuits: A Journey From Classical Circuits to Clifford Circuits and Beyondcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 4; 2025: 4; 2026: 13.

21 papers.

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  1. 2024Qiskit Code Assistant: Training LLMs for generating Quantum Computing Codecited by 24
  2. 2025Optimizing the non-Clifford-count in unitary synthesis using Reinforcement Learningcited by 5
  3. 2024Quantum Artificial Intelligence: A Brief Surveycited by 3
  4. 2026QNAS: A Neural Architecture Search Framework for Accurate and Efficient Quantum Neural Networkscited by 3
  5. 2025Pauli Network Circuit Synthesis with Reinforcement Learningcited by 2
  6. 2026Beyond Reinforcement Learning: Fast and Scalable Quantum Circuit Synthesiscited by 2
  7. 2026AlphaCNOT: Learning CNOT Minimization with Model-Based Planningcited by 2
  8. 2024Attention-Based Deep Reinforcement Learning for Qubit Allocation in Modular Quantum Architecturescited by 1
  9. 2025CNOT Minimal Circuit Synthesis: A Reinforcement Learning Approachcited by 1
  10. 2026Replay-buffer engineering for noise-aware quantum circuit optimizationcited by 1
  11. 2026Aligning Quantum Operators with Large Language Modelscited by 1
  12. 2026When Close Enough Is Not Enough: Autoregressive Drift in Quantum Circuit Synthesiscited by 1
9 more
  1. 2024AI methods for approximate compiling of unitariescited by 0
  2. 2025AI Methods for Permutation Circuit Synthesis Across Generic Topologiescited by 0
  3. 2026QAP-Router: Tackling Qubit Routing as Dynamic Quadratic Assignment with Reinforcement Learningcited by 0
  4. 2026CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problemcited by 0
  5. 2026Transpiler Autotuning with Predictive Models for Quantum Circuit Optimizationcited by 0
  6. 2026AutoQuREO: A Framework for Automated Quantum Resource Estimation and Optimizationcited by 0
  7. 2026AlphaClifford: Efficient Clifford Synthesis and Transpilation with Model-based RLcited by 0
  8. 2026Predicting Resource Efficient Hamiltonian Decomposition for Continuous-Time Quantum Walk Simulationscited by 0
  9. 2026Generative Replay Mitigates Sample Starvation in Quantum Architecture Searchcited by 0