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In direct imaging of exoplanets from space, achieving the required dynamicrange (i.e., planet-to-star contrast in brightness) currently relies oncoronagraphic technology combined with active control of one or more deformablemirrors (DMs) to create a dark region in the image plane, sometimes called a"dark hole." While many algorithms have been proposed for this purpose, all ofthem employ focal plane wavefront sensing (FPWS) in order to calculate theoptimal DM configuration to create the desired dark hole. All currentalgorithms are limited by their own success in that, as the dark hole isachieved, the FPWS procedure becomes shot-noise limited due to he low intensityin the dark hole. This article proposes a FPWS procedure that allowsdetermination of the optimal DM configuration without relying on informationobtained when the DM is near the optimal configuration. This article givesregression procedures for FPWS that do not assume the DM step size is small,which should allow two important improvements to the control loop: 1)performing informative FPWS observations with DM configurations that aresufficiently distant from the optimal dark hole configuration to mitigateshot-noise limitations, and 2) more accurately predicting the DM configurationthat will achieve the desired objective in the dark hole control loop. In orderto treat this more challenging FPWS problem, two different representations arepresented. The first of these, is called the empirical Green's function (EGF),is easy to implement, and has a block-diagonal matrix structure that iswell-suited to parallel processing. The other representation, based on anexplicit aberration expansion (EAE) requires the regression to estimate asmaller number of parameters than the EGF, but leads to a dense matrixstructure. The EGF and EAE methods both simultaneously estimate the planetaryimage.

Finding the Dark Hole with the Lights On: A New Approach to Focal Plane Wavefront Sensing