ExoRad 2.0: The generic point source radiometric model

ExoRad 2.0 is a generic radiometric simulator compatible with any instrument for point source photometry or spectroscopy. Given the descriptions of an observational target and the instrumentation, ExoRad 2.0 estimates several performance metrics for each photometric channel and spectral bin. These include the total optical efficiency, the measured signal from the target, the saturation times, the read noise, the photon noise, the dark current noise, the zodiacal emission, the instrument-self emission and the sky foreground emission. ExoRad 2.0 is written in Python and it is compatible with Python 3.8 and higher. The software is released under the BSD 3-Clause license, and it is available on PyPi, so it can be installed as pip install exorad. Alternatively, the software can be installed from the source code available on GitHub. Before each run, ExoRad 2.0 checks for updates and notifies the user if a new version is available. ExoRad 2.0 has an extensive documentation, available on readthedocs, including a quick-start guide, a tutorial, and a detailed description of the software functionalities. The documentation is continuously updated along with the code. The software source code, available on GitHub, also includes a set of examples of the simulation inputs (for instruments and targets) to run the software and reproduce the results reported in the documentation. The software has been extensively validated against the Ariel radiometric model ArielRad (Mugnai et al., 2020), the time domain simulator ExoSim (Sarkar et al., 2021) and custom simulations performed by the Ariel consortium. ExoRad 2.0 is now used not only by the Ariel consortium but also by other missions, such as the balloon-borne NASA EXCITE mission (Nagler et al., 2022), the space telescope Twinkle (Stotesbury et al., 2022), and an adaptation for the James Webb Space Telescope (Gardner et al., 2006) is under preparation. Such JWST adaptation has been tested against the JWST Exposure Time Calculator (Pontoppidan et al., 2016) and returned consistent results, providing a validation of the code against a working system. Although the code has been validated and used mostly for space and airborne-based telescopes, we foresee no practical limitation to adaptation for ground-based systems.