We present the final development of our point spread function reconstruction algorithm for the Keck-II telescope adaptive optics system, in laser and natural guide star modes. The method makes use of AO loop teleme- try, nearby CN2 profiler data, and on-sky phase diversity. We describe the fundamental assumptions and the mathematical models for each components of the residual phase structure function. The reconstructed PSF is compared with on-sky single star PSF. We emphasize the importance of access to a good telemetry and the fact that non-common path aberrations also affects PSF-R. The global, statistical quality of the reconstructed PSF demonstrates the validity of the method. The algorithm is now ready for AO science data reduction (see the companion overview paper, Ragland et al.1 - this conference).

One of the primary scientific limitations of adaptive optics (AO) has been the incomplete knowledge of the point spread function (PSF), which has made it difficult to use AO for accurate photometry and astrometry in both crowded and sparse fields, for extracting intrinsic morphologies and spatially resolved kinematics, and for detecting faint sources in the presence of brighter sources. To address this we initiated a program to determine and demonstrate PSF determination for science observations obtained with Keck AO. This paper aims to give a broad view of the progress achieved in implementing this capability for Keck AO science observations.The concept and the implementation are briefly described. The design and development of prototype operational tools for automated PSF reconstruction is presented in detail. On-sky performance of the technique is discussed by comparing the reconstructed PSFs to the NIRC2 science camera’s PSFs. The PSF algorithm development for this program is presented in this conference in a separate paper (Jolissaint et al. 2016).