Optimizing quantum control pulses with complex constraints and few variables through Tensorflow

Abstract

Applying optimal control algorithms on realistic quantum systems confronts two key challenges: to efficiently adopt physical constraints in the optimization and to minimize the variables for the convenience of experimental tune-ups. In order to resolve these issues, we propose a novel algorithm by incorporating multiple constraints into the gradient optimization over piece-wise pulse constant values, which are transformed to contained numbers of the finite Fourier basis for bandwidth control. Such complex constraints and variable transformation involved in the optimization introduce extreme difficulty in calculating gradients. We resolve this issue efficiently utilizing auto-differentiation on Tensorflow. We test our algorithm by finding smooth control pulses to implement single-qubit and two-qubit gates for superconducting transmon qubits with always-on interaction, which remains a challenge of quantum control in various qubit systems. Our algorithm provides a promising optimal quantum control approach that is friendly to complex and optional physical constraints.

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Cited by in corpus (11)

• QuTiP 5: The Quantum Toolbox in Python
• Reducing leakage of single-qubit gates for superconducting quantum processors using analytical control pulse envelopes
• QuanEstimation: An open-source toolkit for quantum parameter estimation
• Quantum control of hole spin qubits in double quantum dots
• Mitigated barren plateaus in the time-nonlocal optimization of analog quantum-algorithm protocols
• Quantum optimal control in quantum technologies. Strategic report on current status, visions and goals for research in Europe
• Geometric correspondence of noisy quantum dynamics and universal robust quantum gates
• Characterization of overparametrization in the simulation of realistic quantum systems
• Achieving fast and robust perfect entangling gates via reinforcement learning
• An automated geometric space curve approach for designing dynamically corrected gates
• Enhanced Quantum Signal Control and Sensing Under Multicolored Noise via Generalized Filter Function Framework