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The CARMENES instrument is a pair of high-resolution (R 80, 000) spectrographs covering the wavelength range from 0.52 to 1.71 µm, optimized for precise radial velocity measurements. It was installed and commissioned at the 3.5 m telescope of the Calar Alto observatory in Southern Spain in 2015. The first large science program of CARMENES is a survey of ∼ 300 M dwarfs, which started on Jan 1, 2016.We present an overview of all subsystems of CARMENES (front end, fiber system, visible-light spectrograph, near-infrared spectrograph, calibration units, etalons, facility control, interlock system, instrument control system, data reduction pipeline, data flow, and archive), and give an overview of the assembly, integration, verification, and commissioning phases of the project. We show initial results and discuss further plans for the scientific use of CARMENES.

MEGARA is the multi-object medium-resolution spectrograph for the GTC 10m telescope. MEGARA offers two observing modes, the LCB mode, a large central IFU; and a MOS mode composed by 92 robotic positioners carrying 7 fibers minibundles. Microlens are required to fit the GTC f/17 to the f/3 at the fiber entrance, where pupil image is oversized to have a fiber-to-fiber flux variation better than 10%. This tight requirement imposed manufacturing tolerances for the different components and required the development of a gluing station to provide a centering precision better than 5μm. We present the overview of the optical bundles, the gluing station and the final performance obtained during the integration and tests.

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The aim of a data reduction process is to minimize the influence of data acquisition imperfections on the estimation of the desired astronomical quantity. For this purpose, one must perform appropriate manipulations with data and calibration frames. In addition, random-error frames (computed from first principles: expected statistical distribution of photo-electrons, detector gain, readout-noise, etc.), corresponding to the raw-data frames, can also be properly reduced. This parallel treatment of data and errors guarantees the correct propagation of random errors due to the arithmetic manipulations throughout the reduction procedure. However, due to the unavoidable fact that the information collected by detectors is physically sampled, this approach collides with a major problem: errors are correlated when applying image manipulations involving non-integer pixel shifts of data. Since this is actually the case for many common reduction steps (wavelength calibration into a linear scale, image rectification when correcting for geometric distortions,...), we discuss the benefits of considering the data reduction as the full characterization of the raw-data frames, but avoiding, as far as possible, the arithmetic manipulation of that data until the final measure of the image properties with a scientific meaning for the astronomer. For this reason, it is essential that the software tools employed for the analysis of the data perform their work using that characterization. In that sense, the real reduction of the data should be performed during the analysis, and not before, in order to guarantee the proper treatment of errors.