The direct detection and detailed characterization of exoplanets using extreme adaptive optics (ExAO) is a key science case of both current and future telescopes. However, both quasi-static and residual atmospheric wavefront errors currently limit the sensitivity of this endeavour, generating “speckles” in a coronagraphic image that initially obscure any faint exoplanet(s) from detection. I first demonstrate the current limits of exoplanet imaging using datasets taken with the Gemini Planet Imager and Subaru Coronagraphic ExAO systems. Even when using advanced post-processing algorithms, speckle evolution over time and wavelength is shown to limit the final contrasts that can be reached with current state- of-the-art instruments. A new approach is thus needed to detect fainter exoplanets below these limits. I then illustrate a path forward to reach contrasts near the fundamental photon noise limit: fast focal plane wavefront sensing of both quasi-static and atmospheric speckles. My new method, called the Fast Atmospheric Self-coherent camera Technique (FAST), deploys new hardware and software to overcome these limitations. Looking toward the future, the contrast improvements from fast focal plane wave- front sensing techniques such as FAST are expected to play an essential role in the ground-based detection and characterization of lower mass exoplanets. / Graduate

Astronomical data sets are growing ever larger, and the area of high contrast imaging of exoplanets is no exception. With the advent of fast, low-noise detectors operating at 10 to 1000 Hz, huge numbers of images can be taken during a single hours-long observation. High frame rates offer several advantages, such as improved registration, frame selection, and improved speckle calibration. However, advanced image processing algorithms are computationally challenging to apply. Here we describe a parallelized, cloud-based data reduction system developed for the Magellan Adaptive Optics VisAO camera, which is capable of rapidly exploring tens of thousands of parameter sets affecting the Karhunen-Loeve image processing (KLIP) algorithm to produce high-quality direct images of exoplanets. We demonstrate these capabilities with a visible-wavelength high contrast data set of a hydrogen-accreting brown dwarf companion.

Complex-mask coronagraphs destructively interfere unwanted starlight with itself to enable direct imaging of exoplanets. This is accomplished using a focal plane mask (FPM); a FPM can be a simple occulter mask, or in the case of a complex-mask, is a multi-zoned device designed to phase-shift starlight over multiple wavelengths to create a deep achromatic null in the stellar point spread function. Creating these masks requires microfabrication techniques, yet many such methods remain largely unexplored in this context. We explore methods of fabrication of complex FPMs for a Phased-Induced Amplitude Apodization Complex-Mask Coronagraph (PIAACMC). Previous FPM fabrication efforts for PIAACMC have concentrated on mask manufacturability while modeling science yield, as well as assessing broadband wavelength operation. Moreover current fabrication efforts are concentrated on assessing coronagraph performance given a single approach. We present FPMs fabricated using several process paths, including deep reactive ion etching and focused ion beam etching using a silicon substrate. The characteristic size of the mask features is 5 mu m with depths ranging over 1 mu m. The masks are characterized for manufacturing quality using an optical interferometer and a scanning electron microscope. Initial testing is performed at the Subaru Extreme Adaptive Optics testbed, providing a baseline for future experiments to determine and improve coronagraph performance within fabrication tolerances.