SEAGLE- Simulating EAGle LEnses:Deciphering the galaxy formation via strong lens simulations

Strong gravitational lensing is a robust tool for studying the mass structure and evolution of early type galaxies (ETGs). In thisthesis, I introduce the SEAGLE (i.e. Simulating EAGLE LEnses) pipeline, that approaches the study of galaxy formation throughstrong gravitational lensing, using a suite of high-resolution hydrodynamic simulations, Evolution, and Assembly of GaLaxies andtheir Environments (EAGLE) project. I showed that the galaxy evolution models with either too weak or too strong stellar and/orAGN feedback fail to explain the distribution of observed mass-density slopes. On the other hand, models with constant stellarfeedback, or AGN feedback with a higher duty cycle but milder temperature increases of their surrounding gas, produce stronglenses with total mass density slopes close to isothermal. For the first time, I discovered a major discrepancy between simulationsand strong lensing observations in their projected dark matter fraction within half of the effective radius. This discrepancy is howeverlifted when a variable bottom heavy stellar initial mass function (IMF) is used in the simulation. This could also indicate a yetunaccounted dependency of the properties of ETGs on stellar and AGN feedback and the assumed stellar IMF. In this thesis, Ihave investigated some of the key but open questions related to galaxy formation via strong lensing and opened up some newthought-provoking questions for future

SEAGLE- Simulating EAGle LEnses:Deciphering the galaxy formation via strong lens simulations

Strong gravitational lensing is a robust tool for studying the mass structure and evolution of early type galaxies (ETGs). In this thesis, I introduce the SEAGLE (i.e. Simulating EAGLE LEnses) pipeline, that approaches the study of galaxy formation through strong gravitational lensing, using a suite of high-resolution hydrodynamic simulations, Evolution, and Assembly of GaLaxies and their Environments (EAGLE) project. I showed that the galaxy evolution models with either too weak or too strong stellar and/or AGN feedback fail to explain the distribution of observed mass-density slopes. On the other hand, models with constant stellar feedback, or AGN feedback with a higher duty cycle but milder temperature increases of their surrounding gas, produce strong lenses with total mass density slopes close to isothermal. For the first time, I discovered a major discrepancy between simulations and strong lensing observations in their projected dark matter fraction within half of the effective radius. This discrepancy is however lifted when a variable bottom heavy stellar initial mass function (IMF) is used in the simulation. This could also indicate a yet unaccounted dependency of the properties of ETGs on stellar and AGN feedback and the assumed stellar IMF. In this thesis, I have investigated some of the key but open questions related to galaxy formation via strong lensing and opened up some new thought-provoking questions for future

A new strategy for matching observed and simulated lensing galaxies

The study of strong-lensing systems conventionally involves constructing a mass distribution that can reproduce the observed multiply imaging properties. Such mass reconstructions are generically non-unique. Here, we present an alternative strategy: instead of modelling the mass distribution, we search cosmological galaxy-formation simulations for plausible matches. In this paper, we test the idea on seven well-studied lenses from the SLACS survey. For each of these, we first pre-select a few hundred galaxies from the EAGLE simulations, using the expected Einstein radius as an initial criterion. Then, for each of these pre-selected galaxies, we fit for the source light distribution, while using MCMC optimization for the placement and orientation of the lensing galaxy, so as to reproduce the multiple images and arcs. The results indicate that the strategy is feasible and can easily reject unphysical galaxy-formation scenarios. It even yields relative posterior probabilities of two different galaxy-formation scenarios, though these are not statistically significant yet. Extensions to other observables, such as kinematics and colours of the stellar population in the lensing galaxy, are straightforward in principle, though we have not attempted it yet. Scaling to arbitrarily large numbers of lenses also appears feasible. This will be especially relevant for upcoming wide-field surveys, through which the number of galaxy lenses will rise possibly a hundredfold, which will overwhelm conventional modelling methods

Lessons from a blind study of simulated lenses: image reconstructions do not always reproduce true convergence

In the coming years, strong gravitational lens discoveries are expected to increase in frequency by two orders of magnitude. Lens-modelling techniques are being developed to prepare for the coming massive influx of new lens data, and blind tests of lens reconstruction with simulated data are needed for validation. In this paper we present a systematic blind study of a sample of 15 simulated strong gravitational lenses from the EAGLE suite of hydrodynamic simulations. We model these lenses with a free-form technique and evaluate reconstructed mass distributions using criteria based on shape, orientation, and lensed image reconstruction. Especially useful is a lensing analogue of the Roche potential in binary star systems, which we call the $\textit{lensing Roche potential}$. This we introduce in order to factor out the well-known problem of steepness or mass-sheet degeneracy. Einstein radii are on average well recovered with a relative error of ${\sim}5\%$ for quads and ${\sim}25\%$ for doubles; the position angle of ellipticity is on average also reproduced well up to $\pm10^{\circ}$, but the reconstructed mass maps tend to be too round and too shallow. It is also easy to reproduce the lensed images, but optimising on this criterion does not guarantee better reconstruction of the mass distribution.Comment: 20 pages, 12 figures. Published in MNRAS. Agrees with published versio