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Cosmological Parameter Estimation from the Two-Dimensional Genus Topology -- Measuring the Shape of the Matter Power Spectrum

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arxiv 2004.01424 v1 pith:63KSD2YL submitted 2020-04-03 astro-ph.CO

classification astro-ph.CO
keywords powergenusomegaspectrummattershapetwo-dimensionalamplitude
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abstract

We present measurements of the two-dimensional genus of the SDSS-III BOSS catalogs to constrain cosmological parameters governing the shape of the matter power spectrum. The BOSS data are divided into twelve concentric shells over the redshift range $0.2 < z < 0.6$, and we extract the genus from the projected two-dimensional galaxy density fields. We compare the genus amplitudes to their Gaussian expectation values, exploiting the fact that this quantity is relatively insensitive to non-linear gravitational collapse. The genus amplitude provides a measure of the shape of the linear matter power spectrum, and is principally sensitive to $\Omega_{\rm c}h^{2}$ and scalar spectral index $n_{\rm s}$. A strong negative degeneracy between $\Omega_{\rm c}h^{2}$ and $n_{\rm s}$ is observed, as both can increase small scale power by shifting the peak and tilting the power spectrum respectively. We place a constraint on the particular combination $n_{\rm s}^{3/2} \Omega_{\rm c}h^{2}$ -- we find $n_{\rm s}^{3/2} \Omega_{\rm c}h^{2} = 0.1121 \pm 0.0043$ after combining the LOWZ and CMASS data sets, assuming a flat $\Lambda$CDM cosmology. This result is practically insensitive to reasonable variations of the power spectrum amplitude and linear galaxy bias. Our results are consistent with the Planck best fit $n_{\rm s}^{3/2}\Omega_{\rm c}h^{2} = 0.1139 \pm 0.0009$.

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Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. On the statistical nature of Betti numbers and Euler characteristic of smooth random fields

    math.ST 2025-07 reject novelty 5.0 of 10

    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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