Author:
Tartu Ülikool

Doctoral defence: Moorits Mihkel Muru “Modeling the cosmic web with the Bisous method”

On 10 November at 13:00 Moorits Mihkel Muru defended his Doctoral Thesis in physics „Modeling the cosmic web with the Bisous method“

Supervisor 
Professor Elmo Tempel, University of Tartu 

Opponent 
PhD Weiwuang Cui, Department of Theoretical Physics, Universidad Autónoma de Madrid (Spain) 

Summary

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Moorits Mihkel Muru - Tartu Ülikool

The observations have shown that galaxies and cosmic gas form intricate web-like large-scale structure of the Universe. This cosmic web is sculpted by gravity and cosmic expansion. The filaments that connect the galaxy clusters and surround the huge empty voids are the most remarkable of the cosmic web elements, hold most of the Universe’s mass, and profoundly influence galaxy evolution. This thesis explores the Bisous model, a framework developed to model the filaments using observational data. The Bisous model tackles the challenge of studying the unobservable dark matter structure by connecting galaxies into chains and optimizing the distribution of these chains to form an interconnected cosmic web. To assess the Bisous model’s reliability, we examined its variance when applied to the same data. The results confirmed the model’s convergence and showed its robustness. For flux-limited surveys, the observed galaxy number density depends on the distance due to diminishing light. This presents a challenge for detecting the cosmic web at greater distances. Our analysis revealed and quantified a strong relationship between galaxy number density and the completeness of detected filaments. Despite lower densities, the model rarely produced erroneous filaments, adding to its robustness. As a way to boost the galaxy number densities, we also explored using photometric redshift. Photometric data can be measured in bulk for thousands of galaxies, but the distance estimates have significantly larger uncertainties than for spectroscopic redshift data. Our analysis revealed that mixing photometric and spectroscopic redshift data improved filament detection. This approach proves valuable when spectroscopic data are scarce. The main results of the thesis are the quantitative characterization of the model to help interpret the results and a method to boost filament detection. This will pave the way for a more comprehensive understanding of the cosmic web and galaxy evolution.  

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