Poor man's adaptive optics with high Strehl and low anisoplanatic effects: holographic imaging in crowded fields
(1 vote over all institutions)
We present an algorithm for speckle holography that is optimised for crowded fields. The key features of this algorithm are an iterative approach, the possibility to use several guide stars simultaneously, and cleaning of the instantaneous PSFs of the reference stars from faint secondary sources. High signal-to-noise and accuracy can in this way be reached on the PSFs extracted from the speckle frames. We find that relatively faint (K~12) reference stars are sufficient to reconstruct images with Strehl ratios. If the instrumental FOV is larger than the isoplanatic angle, then the algorithm can be used to reconstruct small sub-fields if the density of reference sources is sufficiently high. The reconstructed sub-images can then be combined to a final mosaic that is largely free of anisoplanatic effects. We have performed experiments with near-infrared and optical speckle data that show the excellent performance of the algorithm. A Strehl ratio of almost 20% was reached on I-band speckle data under average seeing conditions and a Strehl ratio >60% was reached in the K-band. Simultations show that holographic imaging works also when the PSF is under-sampled as long as the angular resolution of the reconstructed image is at least twice the resolution imposed by Nyquist sampling. Thus, if one gives up on the goal of imaging atthe diffraction limit, one can increase the sensitivity and use fainter guide stars. Our work opens new possibilities for sub-arcsecond resolution imaging of large crowded fields with high PSF stability, while keeping the complexity and costs of instruments small.
