User's guide to extracting cosmological information from line-intensity maps

User’s guide to extracting cosmological information from line-intensity maps

José Luis Bernal, Patrick C. Breysse, Héctor Gil-Marín, and Ely D. Kovetz

Phys. Rev. D 100, 123522 – Published 16 December 2019

Abstract

Line-intensity mapping (LIM) provides a promising way to probe cosmology, reionization and galaxy evolution. However, its sensitivity to cosmology and astrophysics at the same time is also a nuisance. Here we develop a comprehensive framework for modeling the LIM power spectrum, which includes redshift space distortions and the Alcock-Paczynski effect. We then identify and isolate degeneracies with astrophysics so that they can be marginalized over. We study the gains of using the multipole expansion of the anisotropic power spectrum, providing an accurate analytic expression for their covariance, and find a 10%–75% increase in the precision of the baryon acoustic oscillation scale measurements when including the hexadecapole in the analysis. We discuss different observational strategies when targeting other cosmological parameters, such as the sum of neutrino masses or primordial non-Gaussianity, finding that fewer and wider redshift bins are typically optimal. Overall, our formalism facilitates an optimal extraction of cosmological constraints robust to astrophysics.

Received 9 August 2019

DOI:https://doi.org/10.1103/PhysRevD.100.123522

Physics Subject Headings (PhySH)

Cosmology Dark energy Evolution of the Universe Large scale structure of the Universe

Gravitation, Cosmology & Astrophysics

Authors & Affiliations

José Luis Bernal ^1,2,3, Patrick C. Breysse ⁴, Héctor Gil-Marín ^1,3, and Ely D. Kovetz⁵

¹ICC, University of Barcelona, IEEC-UB, Martí i Franquès 1, E08028 Barcelona, Spain
²Dept. de Física Quàntica i Astrofísica, Universitat de Barcelona, Martí i Franquès 1, E08028 Barcelona, Spain
³Institut d’Estudis Espacials de Catalunya (IEEC), E08034 Barcelona, Spain
⁴Canadian Institute for Theoretical Astrophysics, University of Toronto, 60 Street George Street, Toronto, Ontario M5S 3H8, Canada
⁵Department of Physics, Ben-Gurion University, Be’er Sheva 84105, Israel

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Issue

Vol. 100, Iss. 12 — 15 December 2019

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Images

Figure 1
Comparison of the LIM power spectrum multipoles at $z = 2.73$ for the fiducial set of parameters (blue) and the cases where each of the parameters of Eq. (9) is increased by 5% (except for $\vec{ς}$ ). The top panels show the true power spectrum, while the bottom panels show the smoothed power spectrum as measured by the generalized experiment considered. From left to right, each column corresponds to the monopole, quadrupole and hexadecapole, respectively. The lower part of each panel shows the ratio or difference (when the multipoles cross 0) between the fiducial power spectrum and the ones with the varied parameters. Dashed lines denote negative values. Note the effect of the window function on all multipoles, especially the quadrupole and hexadecapole: both the fiducial power spectra and their parameter dependence are considerably affected by the smoothing of the map.
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Figure 2
Signal-to-noise ratio per $k$ bin of the measured LIM power spectrum for each redshift bin of the generic experiment considered in this work (color coded) including only the monopole (dotted lines), the monopole and the quadrupole (dashed lines) and adding also the hexadecapole (solid lines).
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Figure 3
Correlation matrices of the parameters $α_{⊥}$ , $α_{∥}$ and $⟨ T ⟩ f σ_{8}$ , marginalized over the nuisance parameters, for each redshift bin, calculated for our generalized experiment. The correlations in the lower triangular matrix correspond to the case where the monopole and quadrupole are included. In the upper triangular matrix the hexadecapole is included as well.
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Figure 4
Forecasted 68% confidence-level marginalized two-dimensional constraints for the pair combinations $α_{⊥}$ , $α_{∥}$ and $⟨ T ⟩ f σ_{8}$ , and their corresponding marginalized one-dimensional distributions. We show results using the monopole and quadrupole (blue), and when including the hexadecapole as well (orange).
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Figure 5
Forecasted 68% confidence-level marginalized constraints on $f_{NL}$ (top panels) and on $\sum m_{ν}$ (bottom panels) for our general experiment using the monopole, quadrupole and hexadecapole, as function of $Ω_{field}$ and $N_{pol} N_{feeds} N_{ant} t_{obs} / T_{sys}^{2}$ , a combination of instrumental parameters which determines the measurement sensitivity. We compare results using a single redshift bin (left panels) or five bins (right panels). Note the change of scale in the color bars.
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Figure 6
Monopole of the LIM power spectrum (solid lines) and square root of its covariance (dashed lines) at $z = 2.73$ for the generic experiment described in Sec. 4a. Different colors denote different modeling of the LIM power spectrum and covariance: the observed one, $\tilde{P}$ (blue), the true one as in Eq. (b1), $P$ (orange), and the true one with the weight scheme discussed in this appendix, $\hat{P}$ (green). For illustration purposes, here we only consider $W_{res}$ and ignore $W_{vol}$ .
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