Optimality Study of Existing Quantum Computing Layout Synthesis Tools
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Abstract (arXiv)
Layout synthesis, an important step in quantum computing, processes quantum circuits to satisfy device layout constraints. In this paper, we construct QUEKO benchmarks for this problem, which have known optimal depths and gate counts. We use QUEKO to evaluate the optimality of current layout synthesis tools, including Cirq from Google, Qiskit from IBM, mathsft|mathsfketrangle from Cambridge Quantum Computing, and recent academic work. To our surprise, despite over a decade of research and development by academia and industry on compilation and synthesis for quantum circuits, we are still able to demonstrate large optimality gaps: 1.5-12x on average on a smaller device and 5-45x on average on a larger device. This suggests substantial room for improvement of the efficiency of quantum computer by better layout synthesis tools. Finally, we also prove the NP-completeness of the layout synthesis problem for quantum computing. We have made the QUEKO benchmarks open-source.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Feb 2020.
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Citing papers per year: 2023: 2; 2024: 2; 2025: 1; 2026: 2.
7 papers.
- 2024AlphaRouter: Quantum Circuit Routing with Reinforcement Learning and Tree Searchcited by 8
- 2023Optimal Layout Synthesis for Quantum Circuits as Classical Planning (full version)cited by 7
- 2024Optimal Layout Synthesis for Deep Quantum Circuits on NISQ Processors with 100+ Qubitscited by 3
- 2023Quantum Kernel Estimation With Neutral Atoms For Supervised Classification: A Gate-Based Approachcited by 0
- 2025Depth-Optimal Quantum Layout Synthesis as SATcited by 0
- 2026QAP-Router: Tackling Qubit Routing as Dynamic Quadratic Assignment with Reinforcement Learningcited by 0
- 2026CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problemcited by 0
- 2026CO-MAP: A Reinforcement Learning Approach to the Qubit Allocation Problem13 May 2026
- 2026QAP-Router: Tackling Qubit Routing as Dynamic Quadratic Assignment with Reinforcement Learning12 May 2026
- 2025Depth-Optimal Quantum Layout Synthesis as SAT7 Jun 2025
- 2024AlphaRouter: Quantum Circuit Routing with Reinforcement Learning and Tree Search7 Oct 2024
- 2024Optimal Layout Synthesis for Deep Quantum Circuits on NISQ Processors with 100+ Qubits18 Mar 2024
- 2023Quantum Kernel Estimation With Neutral Atoms For Supervised Classification: A Gate-Based Approach28 Jul 2023
- 2023Optimal Layout Synthesis for Quantum Circuits as Classical Planning (full version)24 Apr 2023