Heuristic and Optimal Synthesis of CNOT and Clifford Circuits

Efficiently implementing Clifford circuits is crucial for quantum error correction and quantum algorithms. Linear reversible circuits, equivalent to circuits composed of CNOT\\xspace gates, have important applications in classical computing. In this work we present methods for CNOT\\xspace and general Clifford circuit synthesis which can be used to minimise either the entangling two-qubit gate count or the circuit depth. We present three families of algorithms - optimal synthesis which works on small circuits, A* synthesis for intermediate-size circuits and greedy synthesis for large circuits. We benchmark against existing methods, including rustiq, tket and qiskit and show that our approach results in circuits with lower two-qubit gate count. For encoding circuits, our methods outperform previous reinforcement learning results and find a lower two-qubit gate count circuit for the Golay code than previously known. The algorithms have been implemented in a GitHub repository for use by the classical and quantum computing community.

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Publication Details

Journal
Quantum
Published
2026-09-21
DOI
https://doi.org/10.22331/q-2026-09-21-2212
Primary Topic
Quantum-Dot Cellular Automata
Type
article
Field-Weighted Citation Impact
0.00

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article

Heuristic and Optimal Synthesis of CNOT and Clifford Circuits

Dan E. Browne, Stergios Koutsioumpas, Mark Webster
Quantum
Quantum-Dot Cellular Automata
article

Heuristic and Optimal Synthesis of CNOT and Clifford Circuits

Dan E. Browne, Stergios Koutsioumpas, Mark Webster
article en

Abstract

Efficiently implementing Clifford circuits is crucial for quantum error correction and quantum algorithms. Linear reversible circuits, equivalent to circuits composed of CNOT\xspace gates, have important applications in classical computing. In this work we present methods for CNOT\xspace and general Clifford circuit synthesis which can be used to minimise either the entangling two-qubit gate count or the circuit depth. We present three families of algorithms - optimal synthesis which works on small circuits, A* synthesis for intermediate-size circuits and greedy synthesis for large circuits. We benchmark against existing methods, including rustiq, tket and qiskit and show that our approach results in circuits with lower two-qubit gate count. For encoding circuits, our methods outperform previous reinforcement learning results and find a lower two-qubit gate count circuit for the Golay code than previously known. The algorithms have been implemented in a GitHub repository for use by the classical and quantum computing community.

QuantumVol. 10
University College London (GB)
Engineering and Physical Sciences Research Council
Openalex Percentile: Top 97%
Quantum-Dot Cellular Automata
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Heuristic and Optimal Synthesis of CNOT and Clifford Circuits — Dan E. Browne, Stergios Koutsioumpas, et al. · Quantum (2026) | TGRS Research Map | TGRS