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Until now, systematic errors in strong gravitational lens modeling have beenacknowledged but never been fully quantified. Here, we launch an investigationinto the systematics induced by constraint selection. We model the simulatedcluster Ares 362 times using random selections of image systems with andwithout spectroscopic redshifts and quantify the systematics using severaldiagnostics: image predictability, accuracy of model-predicted redshifts,enclosed mass, and magnification. We find that for models with $>15$ imagesystems, the image plane rms does not decrease significantly when more systemsare added; however the rms values quoted in the literature may be misleading asto the ability of a model to predict new multiple images. The mass is wellconstrained near the Einstein radius in all cases, and systematic error dropsto $<2\%$ for models using $>10$ image systems. Magnification errors aresmallest along the straight portions of the critical curve, and the value ofthe magnification is systematically lower near curved portions. For $>15$systems, the systematic error on magnification is $\sim2\%$. We report no trendin magnification error with fraction of spectroscopic image systems whenselecting constraints at random; however, when using the same selection ofconstraints, increasing this fraction up to $\sim0.5$ will increase modelaccuracy. The results suggest that the selection of constraints, rather thanquantity alone, determines the accuracy of the magnification. We note thatspectroscopic follow-up of at least a few image systems is crucial, as modelswithout any spectroscopic redshifts are inaccurate across all of ourdiagnostics.

astrophysical journal/the astrophysical journal

The systematics of strong lens modeling quantified: the effects of  constraint selection and redshift information on magnification, mass, and  multiple image predictability