mlsanityData to 14 Oct 2026

AlphaRouter: Quantum Circuit Routing with Reinforcement Learning and Tree Search

arXiv 2410.05115 ↗First posted 7 Oct 2024quant-ph cs.AI cs.SYcited by 8

On the map: Deep reinforcement learning methods → Quantum reinforcement learning

Abstract (arXiv)

Quantum computers have the potential to outperform classical computers in important tasks such as optimization and number factoring. They are characterized by limited connectivity, which necessitates the routing of their computational bits, known as qubits, to specific locations during program execution to carry out quantum operations. Traditionally, the NP-hard optimization problem of minimizing the routing overhead has been addressed through sub-optimal rule-based routing techniques with inherent human biases embedded within the cost function design. This paper introduces a solution that integrates Monte Carlo Tree Search (MCTS) with Reinforcement Learning (RL). Our RL-based router, called AlphaRouter, outperforms the current state-of-the-art routing methods and generates quantum programs with up to 20% less routing overhead, thus significantly enhancing the overall efficiency and feasibility of quantum computing.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Placed in Quantum reinforcement learning, one of 15 directions in Deep reinforcement learning methods. Builds on 20 of its 61 references that are in the map. First posted on arXiv 7 Oct 2024.

Builds on

20 of 61 references.

References · 20

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  3. 2013Playing Atari with Deep Reinforcement Learningcited by 3,274
  4. 2020Deep Reinforcement Learning for Autonomous Driving: A Surveycited by 721
  5. 2018Machine Learning for Combinatorial Optimization: a Methodological Tour d'Horizoncited by 623
  6. 2018Reinforcement Learning for Solving the Vehicle Routing Problemcited by 333
  7. 2019Meta-Q-Learningcited by 62
  8. 2019P3O: Policy-on Policy-off Policy Optimizationcited by 37
  9. 2021Continuous Doubly Constrained Batch Reinforcement Learningcited by 27
  10. 2019Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computerscited by 22
  11. 2022Learning to Solve Vehicle Routing Problems: A Surveycited by 16
  12. 2019On the qubit routing problemcited by 11
8 more
  1. 2022Compiler Optimization for Quantum Computing Using Reinforcement Learningcited by 11
  2. 2021Qubit Routing using Graph Neural Network aided Monte Carlo Tree Searchcited by 9
  3. 2021Packet Routing with Graph Attention Multi-agent Reinforcement Learningcited by 8
  4. 2020Optimality Study of Existing Quantum Computing Layout Synthesis Toolscited by 7
  5. 2021Optimal qubit assignment and routing via integer programmingcited by 7
  6. 2020Noise-Robust End-to-End Quantum Control using Deep Autoregressive Policy Networkscited by 6
  7. 2022Arline Benchmarks: Automated Benchmarking Platform for Quantum Compilerscited by 5
  8. 2023Budgeting Counterfactual for Offline RLcited by 4

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 4; 2026: 3.

8 papers.

  1. 2024Reinforcement learning with learned gadgets to tackle hard quantum problems on real hardwarecited by 7
  2. 2025Quantum computing and artificial intelligence: status and perspectivescited by 6
  3. 2025BenchRL-QAS: Benchmarking reinforcement learning algorithms for quantum architecture searchcited by 2
  4. 2025Quantum-Efficient Reinforcement Learning Solutions for Last-Mile On-Demand Deliverycited by 1
  5. 2025Shuttling Compiler for Trapped-Ion Quantum Computers Based on Fine-Tuned Large Language Modelscited by 0
  6. 2026Reinforcement Learning for Adaptive Composition of Quantum Circuit Optimisation Passescited by 0
  7. 2026QAP-Router: Tackling Qubit Routing as Dynamic Quadratic Assignment with Reinforcement Learningcited by 0
  8. 2026Transpiler Autotuning with Predictive Models for Quantum Circuit Optimizationcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Practical and efficient quantum circuit synthesis and transpiling with Reinforcement Learning
  2. 2026Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing
  3. 2026AlphaCNOT: Learning CNOT Minimization with Model-Based Planning
  4. 2025Hybrid Reward-Driven Reinforcement Learning for Efficient Quantum Circuit Synthesis
  5. 2025RELiQ: Scalable Entanglement Routing via Reinforcement Learning in Quantum Networks
  6. 2024Quantum Circuit Optimization with AlphaTensor
  7. 2025Separating Ansatz Discovery from Deployment on Larger Problems: Reinforcement Learning for Modular Circuit Design
  8. 2025TensorRL-QAS: Reinforcement learning with tensor networks for improved quantum architecture search