Quantum Noise Spectroscopy Informed Optimized Gates

In recent years, a number of quantum noise spectroscopy (QNS) protocols have been developed to characterize spatio-temporally correlated noise processes. Estimates of the noise power spectral density from QNS protocols are meant to inform optimized control protocols designed to mitigate noise while simultaneously implementing a particular quantum operation. While it is widely accepted that QNS should yield an added advantage to optimized control, there has yet to be an experimental demonstration of QNS-informed optimized control on a non-trivial gate. In this talk, we experimentally demonstrate the advantage of Gradient Ascent in Function Space (Filter GrAFS) optimized control, using injected noise as a probe. Injected noise is generated using the Schrodinger Wave Autoregressive Moving Average (SchWARMA) model, phase-modulating an ideal control signal to mimic the noise spectrum of pure-tone dephasing noise.  By subjecting optimized and non-optimized controls to different noise environments, we experimentally demonstrate the advantage of Filter GrAFS optimized control.