0 Assigned ID: 182 ----- Attempting Submission 1 (Wed Mar 04 21:13:24 GMT 2020) ----- HST Phase I Proposal 182 successfully submitted. Receipt: # 182-1 ----- Attempting Submission 2 (Thu Mar 05 15:33:58 GMT 2020) ----- The optimal approach to measuring the flux of a transient object present in a Hubble Space Telescope (HST) image is to subtract a deep pre- or post-transient image, and extract the transient's flux measurement from the resulting difference image. DOLPHOT is the most powerful and widely used software tool to measure stellar photometry in HST imaging. Currently, however, DOLPHOT cannot be used to measure the fluxes astrophysical transients from difference imaging, despite its powerful capabilities. Here we propose to develop Python tools that will make it possible to use DOLPHOT to extract light curves from difference images constructed from WFPC2, ACS WFC, and WFC3 data. The package will provide a powerful new tool for time-domain astronomy with HST. From our tests of field stars, we have found that DOLPHOT photometry is superior to point-spread function (PSF)-fitting photometry measured using currently available tools for time-domain astronomy. The capabilities of DOLPHOT absent from other time-domain packages include: 1) the ability to measure the flux of sources in individual exposures, 2) determination a PSF model for each HST visit, and 3) the ability to fit simultaneously multiple, overlapping variable point sources. Time-variable sources including multiply imaged quasars and supernovae as well as extremely magnified stars that have small separations on the sky require fits to overlapping point spread functions. The new capabilities provided by DOLPHOT will enable optimal extraction of photometry of transients, including Type Ia supernovae and the counterparts of compact-object mergers. PI Kelly has extensive experience with photometry, and has developed and publicly released photometric calibration tools. For the Weighing the Giants project (von der Linden et al. 2014; Kelly et al. 2014; Applegate et al. 2014), he wrote BigMACS calibrate (https://github.com/patkel/big-macs-calibrate), which uses a model of the SDSS stellar locus to calibrate photometry with high precision. The code was used for several years to calibrate imaging data from the Dark Energy Survey (DES). Large Scale Structure of the Universe Large Scale Structure of the Universe 0 Regular true true false false false SUPPORTED