ObsMap: Preparing observing maps with the best comparison stars for photometry

English (OpenAlex)

We present ObsMap, a Python framework that allows for the interactive creation of various alternative observation maps to maximize the potential of each observing night. The code requires the user to input the star's name or equatorial coordinates, the passband of observation, field of view (FoV), and desired count level together with the minimum and maximum count limits in ADUs for the detector. ObsMap queries the stars in the Gaia DR3 archive within an area four times the size of the FoV, as the target star could be located anywhere within the FoV. It then generates a list of stars in that area, along with additional information about each star. Variable stars are eliminated from the list using Gaia's variability flag. The total incoming light in the specified filter is calculated with the blackbody approach for the remaining stars, utilizing Gaia's effective temperature, stellar radius, and parallax data. Using the filter-specific fluxes, the count levels of the stars are determined relative to that input by the user for the target. As a result, ObsMap creates three maps: a) A large map that is four times the size of the FoV, where the effective temperature and count levels of the stars are annotated. The user can manually select the appropriate FoV, based on this map. b) A suggested map that minimizes photon noise (scatter). c) A suggested map to maximize the number of comparison stars. In some cases, a single comparison star with a high count level could outperform a combination of dim comparison stars. However, if that bright comparison star is variable and not flagged as such in the Gaia archive, choosing dimmer comparison stars could be a better option.