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By stacking an ensemble of strong lensing clusters, we demonstrate the feasibility of placing constraints on the dark energy equation of state. This is achieved by using multiple images of sources at two or more distinct redshift planes. The sample of smooth clusters in our simulations is based on observations of massive clusters and the distribution of background galaxies is constructed using the Hubble Deep Field. Our source distribution reproduces the observed redshift distribution of multiply imaged sources in Abell 1689. The cosmology recovery depends on the number of image families with known spectroscopic redshifts and the number of stacked clusters. Our simulations suggest that constraints comparable to those derived from other competing established techniques on a constant dark energy equation of state can be obtained using 10 to 40 clusters with 5 or more families of multiple images. We have also studied the observational errors in the image redshifts and positions. We find that spectroscopic redshifts and high resolution {it Hubble Space Telescope} images are required to eliminate confidence contour relaxation relative to the ideal case in our simulations. This suggests that the dark energy equation of state, and other cosmological parameters, can be constrained with existing {it Hubble Space Telescope} images of lensing clusters coupled with dedicated ground-based arc spectroscopy.
Using a new sub-sample of observed strong gravitational lens systems, for the first time, we present the equation for the angular diameter distance in the $y$-redshift scenario for cosmography and use it to test the cosmographic parameters. In additi
We perform a comprehensive study of the total mass distribution of the galaxy cluster RXCJ2248 ($z=0.348$) with a set of high-precision strong lensing models, which take advantage of extensive spectroscopic information on many multiply lensed systems
We use supernovae measurements, calibrated by the local determination of the Hubble constant $H_0$ by SH0ES, to interpolate the distance-redshift relation using Gaussian process regression. We then predict, independent of the cosmological model, the
Weak gravitational lensing is considered to be one of the most powerful tools to study the mass and the mass distribution of galaxy clusters. However, the mass-sheet degeneracy transformation has limited its success. We present a novel method for a c
In the coming LSST era, we will observe $mathcal{O}(100)$ of lensed supernovae (SNe). In this paper, we investigate possibility for predicting time and sky position of a supernova using strong lensing. We find that it will be possible to predict the