Galaxy-scale Test of General Relativity with Strong Gravitational Lensing

• Published in: The Astrophysical journal 2022-03, Vol.927 (1), p.28
• Main Authors: Liu, Xiao-Hui, Li, Zhen-Hua, Qi, Jing-Zhao, Zhang, Xin
• Format: Article
• Language: English
• Subjects: Astronomical models; Astrophysics; Cosmology; Galaxies; Gaussian process; General relativity; Gravitational lenses; Modelling; Parameters; Relativity; Solar system; Stars & galaxies; Strong gravitational lensing; Supernova; Theory of relativity
• ISSN: 0004-637X; 1538-4357
• DOI: 10.3847/1538-4357/ac4c3b

Although general relativity (GR) has been precisely tested at the solar system scale, precise tests at a galactic or cosmological scale are still relatively insufficient. Here, in order to test GR at the galactic scale, we use the newly compiled galaxy-scale strong gravitational lensing (SGL) sample to constrain the parameter γ PPN in the parameterized post-Newtonian (PPN) formalism. We employ the Pantheon sample of Type Ia supernova observations to calibrate the distances in the SGL systems using the Gaussian Process method, which avoids the logical problem caused by assuming a cosmological model within GR to determine the distances in the SGL sample. Furthermore, we consider three typical lens models in this work to investigate the influences of the lens-mass distributions on the fitting results. We find that the choice of lens models has a significant impact on the constraints on the PPN parameter γ PPN . By using a minimum χ 2 comparison and the Bayesian information criterion as evaluation tools to make comparisons for the fitting results of the three lens models, we find that the most reliable lens model gives the result of γ PPN = 1.065 − 0.074 + 0.064 , which is in good agreement with the prediction of γ PPN = 1 by GR. As far as we know, our 6.4% constraint result is the best result so far among recent works using the SGL method.