KMOS is a multi-object near-infrared integral field spectrometer with 24 deployable cryogenic pick-off arms. Inevitably, data processing is a complex task that requires careful calibration and quality control. In this paper we describe all the steps
involved in producing science-quality data products from the raw observations. In particular, we focus on the following issues: (i) the calibration scheme which produces maps of the spatial and spectral locations of all illuminated pixels on the detectors; (ii) our concept of minimising the number of interpolations, to the limiting case of a single reconstruction that simultaneously uses raw data from multiple exposures; (iii) a comparison of the various interpolation methods implemented, and an assessment of the performance of true 3D interpolation schemes; (iv) the way in which instrumental flexure is measured and compensated. We finish by presenting some examples of data processed using the pipeline.
We describe several projects addressing the growth of galaxies and massive black holes, for which adaptive optics is mandatory to reach high spatial resolution but is also a challenge due to the lack of guide stars and long integrations. In each case
kinematics of the stars and gas, derived from integral field spectroscopy, plays a key role. We explain why deconvolution is not an option, and that instead the PSF is used to convolve a physical model to the required resolution. We discuss the level of detail with which the PSF needs to be known, and the ways available to derive it. We explain how signal-to-noise can limit the resolution achievable and show there are many science cases that require high, but not necessarily diffraction limited, resolution. Finally, we consider what requirements astrometry and photometry place on adaptive optics performance and design.
