Image simulations of highly magnified clumpy galaxies

Strong gravitational lensing is a fundamental tool for studying the high-redshift Universe since the magnification it produces enables it to reach spatial resolutions that would otherwise be unattainable. Background sources placed in proximity to the caustics of a galaxy cluster lead to such a high degree of magnification, that they allow for the observation of regions as small as stellar clusters. This is a crucial process to comprehend the mechanisms responsible for galaxy formation and evolution in the early Universe. In this Thesis, we develop a python-based pipeline aimed at simulating observations of high-redshift clumpy galaxies with three different instruments: HST/ACS, JWST/NIRCAM and Euclid/VIS. These sources are modeled by combining the host galaxy and stellar clumps as multiple luminous components. Each of them is defined using elliptical Sérsic surface brightness profiles. We place these sources near the caustics of five different galaxy clusters in order to generate highly magnified gravitational arcs. This tool is highly flexible, allowing us to change the parameters in order to simulate very diverse sources under different observing conditions. Our simulator, hence, enables us to directly compare the performance of past, present, and future instruments when dealing with sub-kpc substructures. The second part of this work shows two applications of our simulator. Firstly, we focus on the issue of identifying stellar clumps in strongly lensed galaxies. In order to complete this task we rely on the recently developed modeling code GravityFM. We define a procedure to increase the contrast of the visible stellar clumps in images simulated with the abovementioned instruments and we attempt a statistical comparison of the detections. Secondly, we show how the images generated with our pipeline can be combined with other simulators, such as SimCADO image simulator for E-ELT/MICADO, which also includes the support from the Adaptive Optics system MORFEO.