@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} } @phdthesis{Damle2023, author = {Damle, Mitali}, title = {Gas distribution around galaxies in cosmological simulations}, doi = {10.25932/publishup-59054}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-590543}, school = {Universit{\"a}t Potsdam}, pages = {ii, xii, 146}, year = {2023}, abstract = {The evolution of a galaxy is pivotally governed by its pattern of star formation over a given period of time. The star formation rate at any given time is strongly dependent on the amount of cold gas available in the galaxy. Accretion of pristine gas from the Intergalactic medium (IGM) is thought to be one of the primary sources for star-forming gas. This gas first passes through the virial regions of the galaxy before reaching the Interstellar medium (ISM), the hub of star formation. On the other hand, owing to the evolutionary course of young and massive stars, energetic winds are ejected from the ISM to the virial regions of the galaxy. A bunch of interlinked, complex astrophysical processes, arising from the concurrent presence of both infalling as well as outbound gas, play out over a range of timescales in the halo region or the Circumgalactic medium (CGM) of a galaxy. It would not be incorrect to say that the CGM has a stronghold over the gas reserves of a galaxy and thus, plays a backhand, yet, rather pivotal role in shaping many galactic properties, some of which are also readily observable. Observing the multi-phase CGM (via spectral-line ion measurements), however, remains a non-trivial effort even today. Low particle densities as well as the CGM's vast spatial extent, coupled with likely deviations from a spherical distribution, marr the possibility of obtaining complete, unbiased, high-quality spectral information tracing the full extent of the gaseous halo. This often incomplete information leads to multiple inferences about the CGM properties that give rise to multiple contradicting models. In this regard, computer simulations offer a neat solution towards testing and, subsequently, falsifying many of these existing CGM models. Thanks to their controlled environments, simulations are able to not only effortlessly transcend several orders of magnitude in time and space, but also get around many of the observational limitations and provide some unique views on many CGM properties. In this thesis, I focus on effectively using different computer simulations to understand the role of CGM in various astrophysical contexts, namely, the effect of Local Group (LG) environment, major merger events and satellite galaxies. In Chapter 2, I discuss the approach used for modeling various phases of the simulated z = 0 LG CGM in Hestia constrained simulations. Each of the three realizations contain a Milky Way (MW)-Andromeda (M31) galaxy pair, along with their corresponding sets of satellite galaxies, all embedded within the larger cosmological context. For characterizing the different temperature-density phases within the CGM, I model five tracer ions with cloudy ionization modeling. The cold and cool-ionized CGM (H i and Si iii respectively) in Hestia is very clumpy and distributed close to the galactic centers, while the warm-hot and hot CGM (O vi, O vii and O viii) is tenuous and volume-filling. On comparing the H i and Si iii column densities for the simulated M31 with observational measurements from Project AMIGA survey and other low-z galaxies, I found that Hestia galaxies produced less gas in the outer CGM, unlike observations. My carefully designed observational bias model subsequently revealed the possibility that some MW gas clouds might be incorrectly associated with the M31 CGM in observations, and hence, may be partly responsible for giving rise to the detected mismatch between simulated data and observations. In Chapter 3, I present results from four zoom-in, major merger, gas-rich simulations and the subsequent role of the gas, originally situated in the CGM, in influencing some of the galactic observables. The progenitor parameters are selected such that the post-merger remnants are MW-mass galaxies. We generally see a very clear gas bridge joining the merging galaxies in case of multiple passage mergers while such a bridge is mostly absent when a direct collision occurs. On the basis of particle-to-galaxy distance computations and tracer particle analysis, I found that about 33-48 percent of the cold gas contributing to the merger-induced star formation in the bridge originated from the CGM regions. In Chapter 4, I used a sample of 234 MW-mass, L* galaxies from the TNG50 cosmological simulations, with an aim of characterizing the impact of their global satellite populations on the extended cold CGM properties of their host L* halos. On the basis of halo mass and number of satellite galaxies (N_sats ), I categorized the sample into low and high mass bins, and subsequently into bottom, inter and top quartiles respectively. After confirming that satellites indeed influence the extended cold halo gas density profiles of the host galaxies, I investigated the effects of different satellite population parameters on the host halo cold CGMs. My analysis showed that there is hardly any cold gas associated with the satellite population of the lowest mass halos. The stellar mass of the most massive satellite (M_*mms ) impacted the cold gas in low mass bin halos the most, while N_sats (followed by M_*mms ) was the most influential factor for the high mass halos. In any case, how easily cold gas was stripped off the most massive satellite did not play much role. The number of massive (Stellar mass, M* > 10^8 M_solar) satellites as well as the M_*mms associated with a galaxy are two of the most crucial parameters determining how much cold gas ultimately finds its way from the satellites to the host halo. Low mass galaxies are found rather lacking on both these fronts unlike their high mass counterparts. This work highlights some aspects of the complex gas physics that constitute the basic essence of a low-z CGM. My analysis proved the importance of a cosmological environment, local surroundings and merger history in defining some key observable properties of a galactic CGM. Furthermore, I found that different satellite properties were responsible for affecting the cold-dense CGM of the low and high-mass parent galaxies. Finally, the LG emerged as an exciting prospect for testing and pinning down several intricate details about the CGM.}, language = {en} }