  High-contrast imaging from space must overcome two major noise sources to
successfully detect a terrestrial planet angularly close to its parent star:
photon noise from diffracted star light, and speckle noise from star light
scattered by instrumentally-generated wavefront perturbation. Coronagraphs
tackle only the photon noise contribution by reducing diffracted star light at
the location of a planet. Speckle noise should be addressed with
adaptative-optics systems. Following the tracks of Malbet, Yu and Shao (1995),
we develop in this paper two analytical methods for wavefront sensing and
control that aims at creating dark holes, i.e. areas of the image plane cleared
out of speckles, assuming an ideal coronagraph and small aberrations. The first
method, speckle field nulling, is a fast FFT-based algorithm that requires the
deformable-mirror influence functions to have identical shapes. The second
method, speckle energy minimization, is more general and provides the optimal
deformable mirror shape via matrix inversion. With a NxN deformable mirror, the
size of matrix to be inverted is either N^2xN^2 in the general case, or only
NxN if influence functions can be written as the tensor product of two
one-dimensional functions. Moreover, speckle energy minimization makes it
possible to trade off some of the dark hole area against an improved contrast.
For both methods, complex wavefront aberrations (amplitude and phase) are
measured using just three images taken with the science camera (no dedicated
wavefront sensing channel is used), therefore there are no non-common path
errors. We assess the theoretical performance of both methods with numerical
simulations, and find that these speckle nulling techniques should be able to
improve the contrast by several orders of magnitude.
