2021-10-27, 09:15–09:30, Grand Ballroom
Modern astrophysics faces new challenges that require high-quality spectral data. Stellar spectra are a crucial component that helps us to understand properties of individual stars as well as stellar populations in star clusters and galaxies. A significant fraction of state-of-the-art spectrographs are cross-dispersed Echelle and/or have multiple setups (segments), which are combined together. This approach covers longer wavelength range at high spectral resolution but makes data reduction and post-processing non-trivial. Here we describe how to bring multi-order/multi-segment spectra to perfection by identifying various issues that one could face when working with such spectra and methods of solving them. We use examples of NIR intermediate-resolution Echelle spectra from Folded InfraRed Echellete (R~6500, Magellan Baade) and high-resolution UV-optical spectra observed with UVES (R~80000, VLT). For the UVES spectra, we developed an algorithm for the correct stitching of echelle orders which eliminates "ripples" in regions where they overlap; this algorithm has been successfully integrated into the processing sequence consisting of procedures provided by ESO. For the FIRE spectrograph, we developed the entire data processing pipeline from scratch. The key issue is to understand how the general principles of the optical design (telecentricity violations, flexures) can affect the final data product when using standard internal calibration frames. Multi-segment spectra can suffer from another, fully astrophysical factor -- if different setups were obtained at different epochs and the source is variable (binary/multiple and/or pulsating star), they must not be merged together and processed fully independently; this can be tested using Virtual Observatory access to publicly available catalogs (e.g. using CDS Vizier). Finally, we use VO to collect all available broad- and middle-band photometry, which we then use to perform the global spectral sensitivity correction of final merged spectra. By using these dedicated algorithms, we were able to achieve the quality of the global spectrophotometric calibration of 1--2%, which fulfill the requirement for stellar spectra intended to be used in stellar population synthesis.
Modernizing and maintaining telescopes, FAIR standards for astronomical data, Other