@phdthesis{Guidi2017,
  author    = {Guidi, Giovanni},
  title     = {Connecting simulations and observations in galaxy formation studies},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-396876},
  school      = {Universit{\"a}t Potsdam},
  pages     = {141},
  year      = {2017},
  abstract  = {Observational and computational extragalactic astrophysics are two fields of research that study a similar subject from different perspectives. Observational extragalactic astrophysics aims, by recovering the spectral energy distribution of galaxies at different wavelengths, to reliably measure their properties at different cosmic times and in a large variety of environments. Analyzing the light collected by the instruments, observers try to disentangle the different processes occurring in galaxies at the scales of galactic physics, as well as the effect of larger scale processes such as mergers and accretion, in order to obtain a consistent picture of galaxy formation and evolution. On the other hand, hydrodynamical simulations of galaxy formation in cosmological context are able to follow the evolution of a galaxy along cosmic time, taking into account both external processes such as mergers, interactions and accretion, and internal mechanisms such as feedback from Supernovae and Active Galactic Nuclei. Due to the great advances in both fields of research, we have nowadays available spectral and photometric information for a large number of galaxies in the Universe at different cosmic times, which has in turn provided important knowledge about the evolution of the Universe; at the same time, we are able to realistically simulate galaxy formation and evolution in large volumes of the Universe, taking into account the most relevant physical processes occurring in galaxies. As these two approaches are intrinsically different in their methodology and in the information they provide, the connection between simulations and observations is still not fully established, although simulations are often used in galaxies' studies to interpret observations and assess the effect of the different processes acting on galaxies on the observable properties, and simulators usually test the physical recipes implemented in their hydrodynamical codes through the comparison with observations. In this dissertation we aim to better connect the observational and computational approaches in the study of galaxy formation and evolution, using the methods and results of one field to test and validate the methods and results of the other. In a first work we study the biases and systematics in the derivation of the galaxy properties in observations. We post-process hydrodynamical cosmological simulations of galaxy formation to calculate the galaxies' Spectral Energy Distributions (SEDs) using different approaches, including radiative transfer techniques. Comparing the direct results of the simulations with the quantities obtained applying observational techniques to these synthetic SEDs, we are able to make an analysis of the biases intrinsic in the observational algorithms, and quantify their accuracy in recovering the galaxies' properties, as well as estimating the uncertainties affecting a comparison between simulations and observations when different approaches to obtain the observables are followed. Our results show that for some quantities such as the stellar ages, metallicities and gas oxygen abundances large differences can appear, depending on the technique applied in the derivation. In a second work we compare a set of fifteen galaxies similar in mass to the Milky Way and with a quiet merger history in the recent past (hence expected to have properties close to spiral galaxies), simulated in a cosmological context, with data from the Sloan Digital Sky Survey (SDSS). We use techniques to obtain the observables as similar as possible to the ones applied in SDSS, with the aim of making an unbiased comparison between our set of hydrodynamical simulations and SDSS observations. We quantify the differences in the physical properties when these are obtained directly from the simulations without post-processing, or mimicking the SDSS observational techniques. We fit linear relations between the values derived directly from the simulations and following SDSS observational procedures, which in most of the cases have relatively high correlation, that can be easily used to more reliably compare simulations with SDSS data. When mimicking SDSS techniques, these simulated galaxies are photometrically similar to galaxies in the SDSS blue sequence/green valley, but have in general older ages, lower SFRs and metallicities compared to the majority of the spirals in the observational dataset. In a third work, we post-process hydrodynamical simulations of galaxies with radiative transfer techniques, to generate synthetic data that mimic the properties of the CALIFA Integral Field Spectroscopy (IFS) survey. We reproduce the main characteristics of the CALIFA observations in terms of field of view and spaxel physical size, data format, point spread functions and detector noise. This 3-dimensional dataset is suited to be analyzed by the same algorithms applied to the CALIFA dataset, and can be used as a tool to test the ability of the observational algorithms in recovering the properties of the CALIFA galaxies. To this purpose, we also generate the resolved maps of the simulations' properties, calculated directly from the hydrodynamical snapshots, or from the simulated spectra prior to the addition of the noise. Our work shows that a reliable connection between the models and the data is of crucial importance both to judge the output of galaxy formation codes and to accurately test the observational algorithms used in the analysis of galaxy surveys' data. A correct interpretation of observations will be particularly important in the future, in light of the several ongoing and planned large galaxy surveys that will provide the community with large datasets of properties of galaxies (often spatially-resolved) at different cosmic times, allowing to study galaxy formation physics at a higher level of detail than ever before. We have shown that neglecting the observational biases in the comparison between simulations and an observational dataset may move the simulations to different regions in the planes of the observables, strongly affecting the assessment of the correctness of the sub-resolution physical models implemented in galaxy formation codes, as well as the interpretation of given observational results using simulations.},
  language  = {en}
}