submission 5 1335139425 Assigned ID: 5350 ----- Attempting Submission 1 (Tue Mar 26 06:29:10 GMT 2024) ----- HST Phase I Proposal 5350 successfully submitted. Receipt: # 5350-1 ----- Attempting Submission 2 (Tue Mar 26 08:52:07 GMT 2024) ----- HST Phase I Proposal 5350 successfully submitted. Receipt: # 5350-2 ----- Attempting Submission 3 (Tue Mar 26 15:07:13 GMT 2024) ----- HST Phase I Proposal 5350 successfully submitted. Receipt: # 5350-3 ----- Attempting Submission 4 (Tue Mar 26 23:04:35 GMT 2024) ----- HST Phase I Proposal 5350 successfully submitted. Receipt: # 5350-4 ----- Attempting Submission 5 (Tue Mar 26 23:57:59 GMT 2024) ----- To date there is no well validated end-to-end lens modeling pipeline which is scalable, robust, and uniform. To be generally applicable such a pipeline would need to be validated on a large sample of real strong lenses with extended background sources which have been imaged with HST. The goal of this HST Archival Program will be to develop and validate such a pipeline which will prove to be critically important in the pursuit of key strong lensing science objectives. This will be the first step towards population level inferences and robust statistical analyses for a wide range of strong lensing science including measuring cosmological parameters such as H0, testing the cold dark matter model via detection of low mass dark matter halos, and a wide variety of galaxy evolution studies. Our team includes experts in state-of-the-art lens modeling, machine learning and data reduction. C. Storfer has extensive experience in handling and reduction of HST imaging as well as a wealh of domain expertise in strong gravitational lensing and machine learning including a high level of productivity in strong lens searches in collaboration with X. Huang (Huang+ 2020, Huang+2021, Storfer+ 2023). Huang is a co-developer of the GPU-based lens modeling package GIGA-Lens (Gu+ 2022) and has experience in strong lens modeling using HST data (Broadhurst, Huang+ 2000). E. Magnier is a co-lead of the PanSTARRS survey and is an expert in data handling, quality control, and reduction. A. Shajib has carried out uniform modeling of the largest sample of lensed quasars (N=13) using multi-band HST imaging (Shajib+ 2019) and the largest of sample galaxy-galaxy lenses (Tan, Shajib et al. 2024).. Shajib proposed the efficient computational method that we will apply in this analysis to model the lens mass distribution of non-analytical profiles, such as the elliptical cored generalized-NFW profile or the elliptical Sersic profile (Shajib 2019). Shajib has a wealth of experience in lens modeling and is the contributing developer of the state-of-the-art lens modeling software "lenstronomy" (Birrer+ 2018). D. Rubin has high-level expertise in HST data reduction. D. Schlegel is the Co-Project Scientist for the Dark Energy Spectroscopic Instrument (DESI). E. Silver has developed a pipeline to produce some of the most realistic strong lens simulations to-date by making use of the VELA simulations. R. Wang is a machine learning expert and has developed an image segmentation model which will be utilized for this program. S. Baltasar Jimenez and N. Ratier Werbin are both experts in strong lens modeling using GIGA-Lens and are responsible for implentation of point source modeling within GIGA-Lens. S. Agarwal and A. Cikota both have experience with data reduction and photometry. Galaxies 0 false false false false false false false SUPPORTED