Formation et évolution des galaxies

Résumé

L'étude de la formation et de l'évolution des galaxies s'intéresse aux processus ayant abouti à la formation d'un univers hétérogène à partir d'une prémisse homogène, à la formation des premières galaxies (processus appelé galactogenèse), à la façon dont les galaxies changent avec le temps, et aux processus qui ont conduit à la grande variété des structures observées parmi les galaxies proches. C'est l'un des domaines de recherche les plus actifs en astrophysique. Selon les théories de la formation des structures, on présume que la formation des galaxies résulte de légères fluctuations quantiques dans le cadre du Big Bang. Selon une opinion majoritaire l'évolution des galaxies se serait produite en conformité avec le modèle cosmologique Lambda-CDM. C'est-à-dire que le regroupement et la fusion des galaxies constituent leur moyen d'augmenter leur masse, et peut aussi déterminer leur forme et leur structure. Formation des premières galaxies Pendant une certaine durée après

Source officielle

https://fr.wikipedia.org/wiki/Formation_et_%C3%A9volution_des_galaxies

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UNITSIM-Galaxies: data release and clustering of emission-line galaxies

Ginevra Favole

New surveys such as European Space Agencys (ESA's) Euclid mission are planned to map with unprecedented precision the large-scale structure of the Universe by measuring the 3D positions of tens of millions of galaxies. It is necessary to develop theoretically modelled galaxy catalogues to estimate the expected performance and to optimize the analysis strategy of these surveys. We populate two pairs of (1 h(-1) Gpc)(3) volume dark matter-only simulations from the UNIT project with galaxies using the Semi-Analytic Galaxy Evolution semi-analytic model of galaxy formation, coupled to the photoionization model GET.EMLINES to estimate their H alpha emission. These catalogues represent a unique suite that includes galaxy formation physics and - thanks to the fixed-pair technique used - an effective volume of similar to (5 h(-1) Gpc)(3), which is several times larger than the Euclid survey. We present the performance of these data and create five additional emission-line galaxy (ELG) catalogues by applying a dust-attenuation model as well as adjusting the flux threshold as a function of redshift in order to reproduce Euclid-forecast dN/dz values. As a first application, we study the abundance and clustering of those model H alpha ELGs: for scales greater than similar to 5 h(-1) Mpc, we find a scale-independent bias with a value of b similar to 1 at redshift z similar to 0.5, that can increase nearly linearly to b similar to 4 at z similar to 2, depending on the ELG catalogue. Model galaxy properties, including their emission-line fluxes (with and without dust extinction) are publicly available.

OXFORD UNIV PRESS2022

Chargement

Methods for strong gravitational lens detection and analysis using machine learning and high performance computing

Christoph Ernst René Schäfer

The study of strong gravitational lenses is a relatively new scientific field in astronomy with many applications in cosmology. Its unique observables allow astronomers to trace dark matter, determine the expansion of the universe and study galaxy evolution. While strong lenses are relatively rare phenomena, recent and future improvements in observational instrumentation are expected to lead to a sharp increase in the number and quality of their observation. With that increase comes however an observational challenge from the sheer quantity of data the lenses are hidden in. Current classification and modelling techniques are simply not capable of handling the new data in a reasonable timeframe. As a consequence this thesis concerns itself with the development and improvement of numerical methods necessary to find and analyse these newly found lenses, borrowing from deep learning and high performance computing techniques. Deep learning, a field of machine learning, shows significant success in finding lenses in simulations. Performing significantly better than any other classification method, CNN-based lens finders reach almost the required classification efficiency and accuracy for a fully automated Euclid strong lensing pipeline. Its dependency on a varied and complete training set and the difficulty creating it make its immediate application to new surveys however more difficult. Incorporating high performance computing techniques and more concurrent algorithm design into lens analysis results in crucial speed-ups for strong lens analysis. Applied to Lenstool, a popular mass modelling tool for gravitational lenses, the resulting software can be run on modern supercomputers, using Graphics Processing Units (GPU) and CPUs simultaneously. Running it on state-of-the-art hardware makes it possible to reduce computation time to an acceptable level when mass modelling complex cluster lenses.

EPFL2020

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Halo assembly bias is the secondary dependence of the clustering of dark matter haloes on their assembly histories at fixed halo mass. This established dependence is expected to manifest itself on galaxy clustering, a potential effect commonly known as galaxy assembly bias. Using the IllustrisTNG300 magnetohydrodynamical simulation, we analyse the dependence of the properties and clustering of galaxies on the specific mass accretion history of their hosting haloes (sMAH). We first show that several halo and galaxy properties strongly correlate with the slope of the sMAH (beta) at fixed halo mass. Haloes with increasingly steeper beta increment their masses faster early on, and their hosted galaxies present larger stellar-to-halo mass ratios, lose their gas faster, reach the peak of their star formation histories at higher redshift, and become quenched earlier. We also demonstrate that beta provides a more stable link to these key galaxy formation properties than other broadly employed halo proxies, such as formation time. Finally, we measure the secondary dependence of galaxy clustering on beta at fixed halo mass. By tracing back the evolution of individual haloes, we show that the amplitude of the galaxy assembly bias signal for the progenitors of z = 0 galaxies increases with redshift, reaching a factor of 2 at z = 1 for haloes of M-halo = 10(11.)(5) -10(12) h(-1) M-circle dot. The measurement of the evolution of assembly bias along the merger tree provides a new theoretical perspective to the study of secondary bias. Our findings have also important implications for the generation of mock catalogues for upcoming cosmological surveys.

OXFORD UNIV PRESS2021

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Methods for strong gravitational lens detection and analysis using machine learning and high performance computing

Christoph Ernst René Schäfer

EPFL2020