How to Train Your Jacobian: Adaptive Algorithms for High-Contrast Wavefront Sensing & Control
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coronagraphy↗
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Meiji Nguyen
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How to Train Your Jacobian: Least-Squares System Identification for Space-Based Coronagraphy
Stellar coronagraphs use closed-loop focal-plane wavefront sensing and control algorithms to create high-contrast dark zones suitable for imaging exoplanets and exozodiacal dust clouds around nearby stars. Model-based algorithms are susceptible to model mismatch, wherein a departure of the coronagraph's true optical characteristics from the assumed model causes reduced control loop performance. Here, we describe a simple technique for empirically tuning the wavefront control Jacobian matrix using applied deformable mirror commands and observed images. This mitigates model mismatch and recovers near-optimal control loop performance.
coronagraphy↗