A learning-to-rank model over feature-model-sampled Qiskit transpiler pass configurations reliably outperforms Qiskit's fixed optimization levels on two-qubit gate reduction.
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Transpiler Autotuning with Predictive Models for Quantum Circuit Optimization
A learning-to-rank model over feature-model-sampled Qiskit transpiler pass configurations reliably outperforms Qiskit's fixed optimization levels on two-qubit gate reduction.