The HST Frontier Fields: High-Level Science Data Products for the First 4 Completed Clusters, and for the Last 2 Clusters Currently in Progress

The Hubble Space Telescope Frontier Fields program (PI: J. Lotz) is a large Director's Discretionary program of 840 orbits, to obtain ultra-deep observations of six strong lensing clusters of galaxies, together with parallel deep blank fields, making use of the strong lensing amplification by these clusters of distant background galaxies to detect the faintest galaxies currently observable in the high-redshift universe. The first four of these clusters are now complete, namely Abell 2744, MACS J0416.1-2403, MACS J0717.5+3745 and MACS J1149.5+2223, with each of these having been observed over two epochs, to a total depth of 140 orbits on the main cluster and an associated parallel field, using ACS (F435W, F606W, F814W) and WFC3/IR (F105W, F125W, F140W, F160W). The remaining two clusters, Abell 370 and Abell S1063, are currently in progress, with the first epoch for each having been completed. Full sets of high-level science products have been generated for all these clusters by the team at STScI, including cumulative-depth v0.5 data releases during each epoch, as well as full-depth version 1.0 releases after the completion of each epoch. These products include all the full-depth distortion-corrected mosaics and associated products for each cluster, which are science-ready to facilitate the construction of lensing models as well as enabling a wide range of other science projects. Many improvements beyond default calibration for ACS and WFC3/IR are implemented in these data products, including corrections for persistence, time-variable sky, and low-level dark current residuals, as well as improvements in astrometric alignment to achieve milliarcsecond-level accuracy. The full set of resulting high-level science products are publicly delivered to the community via the Mikulski Archive for Space Telescopes (MAST) to enable the widest scientific use of these data, as well as ensuring a public legacy dataset of the highest possible quality that is of lasting value to the entire community.