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Betti Functionals as a Probe for Cosmic Topology
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abstract
The question of the global topology of the Universe (cosmic topology) is still open. In the $\Lambda$CDM concordance model it is assumed that the space of the Universe possesses the trivial topology of $\mathbb{R}^3$ and thus that the Universe has an infinite volume. As an alternative, we study in this paper one of the simplest non-trivial topologies given by a cubic 3-torus describing a universe with a finite volume. To probe cosmic topology, we analyse certain structure properties in the cosmic microwave background (CMB) using Betti Functionals and the Euler Characteristic evaluated on excursions sets, which possess a simple geometrical interpretation. Since the CMB temperature fluctuations $\delta T$ are observed on the sphere $\mathbb{S}^2$ surrounding the observer, there are only three Betti functionals $\beta_k(\nu)$, $k=1,2,3$. Here $\nu=\delta T/\sigma_0$ denotes the temperature threshold normalized by the standard deviation $\sigma_0$ of $\delta T$. Analytic approximations of the Gaussian expectations for the Betti functionals and an exact formula for the Euler characteristic are given. It is shown that the amplitudes of $\beta_0(\nu)$ and $\beta_1(\nu)$ decrease with increasing volume $V=L^3$ of the cubic 3-torus universe. Since the computation of the $\beta_k$'s from observational sky maps is hindered due to the presence of masks, we suggest a method yielding lower and upper bounds for them and apply it to four Planck 2018 sky maps. It is found that the $\beta_k$'s of the Planck maps lie between those of the torus universes with side-lengths $L=2.0$ and $L=3.0$ in units of the Hubble length and above the infinite $\Lambda$CDM case. These results give a further hint that the Universe has a non-trivial topology.
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Cited by 1 Pith paper
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On the statistical nature of Betti numbers and Euler characteristic of smooth random fields
Betti numbers, Euler characteristic and their sum for excursion sets are expressed in terms of Binomial coefficients of a topological basis, predicting Gaussian statistics except at high thresholds.
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