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Researchers at University College London have developed new algorithms that significantly reduce the number of two-qubit gates required for quantum circuits, outperforming established tools like tket and qiskit. By leveraging graph isomorphism for small circuits and a novel vector heuristic for large ones, this open-source approach achieves higher efficiency even on complex error correction codes like the 23-qubit Golay code. This advancement represents a tangible step forward in optimizing quantum circuit design without relying on reinforcement learning.

Sources coveringQuantum Zeitgeist, Quantum Computing Report, The Quantum Insider, itbusinessnet.com

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New algorithms beat existing methods for quantum circuits

Quantum ZeitgeistSeptember 21, 20265 min read

New methods for CNOT and Clifford circuit synthesis outperform rustiq, tket, and qiskit, achieving lower two-qubit gate counts.

Mark Webster, Stergios Koutsioumpas, and Dan E Browne University College London have developed new algorithms that reduce the number of two-qubit gates needed for quantum circuits. The team benchmarked optimal, A*, and greedy algorithms against existing methods, and show that their approach results in circuits with lower two-qubit gate count. Their approach surpasses previous results achieved using reinforcement learning, even discovering a circuit for the 23-qubit Golay code with a lower two-qubit gate count than previously known. The algorithms are available as an open-source Python package for use by the classical and quantum computing community. The Golay code, an important component in quantum…

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