Replication Data for: Lunar Crater Radio Telescope Science Model Dataset

This dataset was generated during a NIAC funded effort to create a ‘science forward model’ for the Lunar Crater Radio Telescope (LCRT). It uses the PyLinex framework developed by Jack Burns’ group at the University of Colorado to generate training and test data sets which combine radio sky foreground models in the 4.7-47 MHz frequency band with instantiations of the Turning point model for the 21-cm Dark Ages signal. The foreground map was generated by scaling the signal from its original frequency of 408 MHz, using a power law with a spectral index, whose variation with galactic latitude and longitude was chosen randomly. The maps were then transformed to a frame associated with the location of LCRT on the far side of the moon. These sky maps were then convolved with the radiation pattern of the LCRT antenna to generate beam-weighted foregrounds. The dataset also includes the Python source code and files for generating the dataset.