Reconstructs mass distributions and magnified high-redshift sources via lensing.Gravitational lensing modeling is the process of reconstructing the mass distribution of foreground matter (like galaxies or galaxy clusters) and the properties of background sources (like distant galaxies) from the distorted, magnified images produced by gravitational lensing. When light from a distant source passes near a massive object, its path is bent, creating multiple images, arcs, or Einstein rings. Modeling these effects allows astronomers to map dark matter, measure the expansion of the universe, and study galaxies that would otherwise be too faint to detect.
The theoretical framework was developed in the early 20th century, with Einstein's general relativity predicting light deflection. The first strong gravitational lens was discovered in 1979 (the Twin Quasar). Modern modeling techniques evolved in the 1990s with computational advances.
The modeling uses the lens equation, which relates the observed image positions to the source position and the lens's gravitational potential. By fitting observed images to predicted ones, astronomers iteratively adjust the mass distribution model (often parameterized as dark matter halos with elliptical symmetry) and the source's surface brightness profile. Advanced techniques include pixelated source reconstruction and machine learning to speed up the fitting.
Gravitational lensing modeling is used to map dark matter in galaxy clusters, measure the Hubble constant via time delays in lensed quasars, and detect high-redshift galaxies that are magnified for detailed study.
The first gravitational lens discovered, the Twin Quasar, was initially thought to be two separate quasars until their identical spectra revealed they were two images of the same object.

















