Hierarchical Clustering in ${Lambda}$CDM Cosmologies via Persistence Energy. (arXiv:2401.01988v1 [astro-ph.CO])
<a href="http://arxiv.org/find/astro-ph/1/au:+Huffel_M/0/1/0/all/0/1">Michael Etienne Van Huffel</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Barberi_L/0/1/0/all/0/1">Leonardo Aldo Alejandro Barberi</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Sagis_T/0/1/0/all/0/1">Tobias Sagis</a>
In this research, we investigate the structural evolution of the cosmic web,
employing advanced methodologies from Topological Data Analysis. Our approach
involves leveraging $Persistence$ $Signals$, an innovative method from recent
literature that facilitates the embedding of persistence diagrams into vector
spaces by re-conceptualizing them as signals in $mathbb R^2_+$. Utilizing this
methodology, we analyze three quintessential cosmic structures: clusters,
filaments, and voids. A central discovery is the correlation between
$Persistence$ $Energy$ and redshift values, linking persistent homology with
cosmic evolution and providing insights into the dynamics of cosmic structures.
In this research, we investigate the structural evolution of the cosmic web,
employing advanced methodologies from Topological Data Analysis. Our approach
involves leveraging $Persistence$ $Signals$, an innovative method from recent
literature that facilitates the embedding of persistence diagrams into vector
spaces by re-conceptualizing them as signals in $mathbb R^2_+$. Utilizing this
methodology, we analyze three quintessential cosmic structures: clusters,
filaments, and voids. A central discovery is the correlation between
$Persistence$ $Energy$ and redshift values, linking persistent homology with
cosmic evolution and providing insights into the dynamics of cosmic structures.
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