Automating the design of dynamically corrected gates using geometric space curves

Dynamically corrected gates are necessary for reaching the fidelities needed for quantum error correction thresholds. Space Curve Quantum Control provides a systematic way to construct such gates by mapping the problem to the task of designing space curves that satisfy certain geometric constraints. However, constructing space curves in higher dimensions that satisfy several constraints at once is challenging to do by hand, especially given that, in the original formulation, both the target operation and noise-robustness depend on the shape of the space curve, making it challenging to keep the target operation fixed while optimizing the shape to achieve robustness. In this talk, we introduce an automated approach to constructing space curves called the Bezier Ansatz for Robust Quantum (BARQ) control method. This approach numerically optimizes space curves using control points in such a way that the gate is a-priori fixed and the optimization only affects robustness properties, which are encoded in the shape of the curve. Our work is implemented in Python and provides a user-friendly interface to generate physically-realizable, noise-robust pulses.