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We present an overview and status update of the 4MOST project at the Final Design Review. 4MOST is a major new wide-field, high-multiplex spectroscopic survey facility under development for the VISTA telescope at the Paranal Observatory of ESO. Starting in 2022, 4MOST will deploy 2436 optical fibres in a 4.1 square degree field-of-view using a fibre positioner based on the tilting spine principle. The fibres will feed one high-resolution (R~20,000) and two low-resolution (R~5000) spectrographs that all have fixed configuration, 3-channel designs with identical 6k x 6k CCD detectors. Updated performance estimates will be presented based on components already manufactured and pre-production prototypes of critical subsystems.
The 4MOST science goals are mostly driven by a number of large area, space-based observatories of prime European interest: Gaia and PLATO (Galactic Archeology and Stellar Physics), eROSITA (High-Energy Sky), and Euclid (Cosmology and Galaxy Evolution). Science cases based on these observatories, along with wide-area ground-based facilities such as LSST, VISTA and VST drive the ten Consortium Surveys covering a large fraction of the Southern sky, with bright time mostly devoted to the Milky Way disk and bulge areas and the Magellanic Clouds, and the dark/gray time largely devoted to extra-galactic targets. In addition there will be a significant fraction of the fibre-hours devoted to Community Surveys, making 4MOST a true general-purpose survey facility, capable of delivering spectra of samples of objects that are spread over a large fraction of the sky.
The 4MOST Facility Simulator was created to show the feasibility of the innovative operations scheme of 4MOST with all surveys operating in parallel. The simulator uses the mock catalogues created by the science teams, simulates the spectral throughput and detection of the objects, assigns the fibres at each telescope pointing, creates pointing distributions across the sky and simulates a 5-year survey (including overhead, calibration and weather losses), and finally does data quality analyses and computes the science Figure-of-Merits to assess the quality of science produced. The simulations prove the full feasibility of running different surveys in parallel.
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