Despite utilising a restricted gate set, AlphaClifford consistently reduces total and two-qubit (CNOT) gate counts compared with established circuit creation methods. This new reinforcement learning framework also surpasses other similar systems when adapting circuits for specific quantum computer architectures. The approach models complex relationships using algebraic properties, enabling more efficient optimisation of these essential building blocks for error correction.
Naples Team Cuts CNOT Gates in Clifford Circuits
Despite utilising a restricted gate set, AlphaClifford consistently reduces total and two-qubit (CNOT) gate counts compared with established circuit creation methods. This new reinforcement learning framework also surpasses other similar systems when adapting circuits for specific quantum computer architectures. The approach models complex relationships using algebraic properties, enabling more efficient optimisation of these essential building blocks for error correction.