STRIDES: Automated uniform models for 30 quadruply imaged quasars

TL;DR

This paper introduces an automated pipeline for modeling 30 quadruply imaged quasars, significantly reducing time and computational resources needed, and demonstrating the potential for large-scale cosmography studies with minimal human intervention.

Contribution

The authors develop and apply an automated modeling pipeline that achieves cosmography-grade models for multiple lenses efficiently, enabling large-scale time delay cosmography.

Findings

Models for 10/30 lenses are cosmography grade (<3% variation).

Models for 6/30 lenses are close to cosmography grade (5-10%).

Pipeline reduces modeling time to hours and CPU hours, facilitating large lens sample analysis.

Abstract

Gravitational time delays provide a powerful one step measurement of $H_0$, independent of all other probes. One key ingredient in time delay cosmography are high accuracy lens models. Those are currently expensive to obtain, both, in terms of computing and investigator time (10$^{5-6}$ CPU hours and $\sim$ 0.5-1 year, respectively). Major improvements in modeling speed are therefore necessary to exploit the large number of lenses that are forecast to be discovered over the current decade. In order to bypass this roadblock, building on the work by Shajib et al. (2019), we develop an automated modeling pipeline and apply it to a sample of 30 quadruply imaged quasars and one lensed compact galaxy, observed by the Hubble Space Telescope in multiple bands. Our automated pipeline can derive models for 30/31 lenses with few hours of human time and <100 CPU hours of computing time for a typical system. For each lens, we provide measurements of key parameters and predictions of magnification as well as time delays for the multiple images. We characterize the cosmography-readiness of our models using the stability of differences in Fermat potential (proportional to time delay) w.r.t. modeling choices. We find that for 10/30 lenses our models are cosmography or nearly cosmography grade (<3% and 3-5% variations). For 6/30 lenses the models are close to cosmography grade (5-10%). These results are based on informative priors and will need to be confirmed by further analysis. However, they are also likely to improve by extending the pipeline modeling sequence and options. In conclusion, we show that uniform cosmography grade modeling of large strong lens samples is within reach.