Papers › Building models of the Universe with hydrodynamic simulations
Building models of the Universe with hydrodynamic simulations
Edoardo Altamura
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Hydrodynamic simulations have become irreplaceable in modern cosmology for exploring complex systems and making predictions to steer future observations. In Chapter 1, we begin with a philosophical discussion on the role of simulations in science. We argue that simulations can bridge the gap between empirical and fundamental knowledge. The validation of simulations stresses the importance of achieving a balance between trustworthiness and scepticism. Next, Chapter 2 introduces the formation of structures and comparisons between synthetic and observational data. Chapter 3 describes the production pipeline of zoom-in simulations used to model individual objects and novel methods to mitigate known shortcomings. Then, we assessed the weak scaling of the SWIFT code and found it to be one of the hydrodynamic codes with the highest parallel efficiency. In Chapter 4, we study the rotational kinetic Sunyaev-Zeldovich (rkSZ) effect for high-mass galaxy clusters from the MACSIS simulations. We find a maximum signal greater than 100 μK, 30 times stronger than early predictions from self-similar models, opening prospects for future detection. In Chapter 5, we address a tension between the distribution of entropy measured from observations and predicted by simulations of groups and clusters of galaxies. We find that most recent hydrodynamic simulations systematically over-predict the entropy profiles by up to one order of magnitude, leading to profiles that are shallower and higher than the power-law-like entropy profiles that have been observed. We discuss the dependence on different hydrodynamic and sub-grid parameters using variations of the EAGLE model. Chapter 6 explores the evolution of the profiles as a function of cosmic time. We report power-law-like entropy profiles at high redshift for both objects. However, at late times, an entropy plateau develops and alters the shape of the profile.
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