A transformer-based greybox surrogate trained on Monte Carlo data predicts single-qubit gate fidelities under telegraph and Ornstein-Uhlenbeck noise, and gradient-based control with this emulator yields simulated fidelities above 99 percent at low coupling.
Prac- tical quantum hardware may impose constraints on accessible control pulses
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Machine Learning-aided Optimal Control of a noisy qubit
A transformer-based greybox surrogate trained on Monte Carlo data predicts single-qubit gate fidelities under telegraph and Ornstein-Uhlenbeck noise, and gradient-based control with this emulator yields simulated fidelities above 99 percent at low coupling.