The power spectrum of galaxies from large to small scales: a line-intensity mapping perspective

ABSTRACT We present a model for the power spectrum of the density field of galaxies weighted by their star formation rate. This weighting is relevant in line-intensity mapping (lim) when the observed line luminosity is strongly correlated with star formation, as is the case for the H $\alpha$ line. Our model reproduces the measured power spectrum in the illustris tng simulation to within a few per cent across all scales, with fitting parameters that have clear physical interpretations. On scales of tens of megaparsecs, the model accounts for the weighted non-linear bias of galaxies as well as halo exclusion (two-halo term). On smaller scales, it incorporates the weighted distribution of satellite galaxies within haloes (one-halo term). The random sampling of satellite galaxies introduces a galaxy shot noise term to the power spectrum on small scales, and their confinement to haloes introduces a halo shot noise term on large scales. Omitting satellite galaxies from the analysis results in an underestimation of both the large-scale bias and the mean intensity by $\sim 30$ per cent each at $z \sim 1.5$. Assigning the intensity of satellites to the centre of their respective haloes affects the power spectrum on scales $k \gtrsim 0.3\ {\rm h\, Mpc^{-1}}$. Our fitting function provides a well-motivated parametrization that can be used to interpret data from upcoming lim surveys.

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Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2025-04-18
DOI
https://doi.org/10.1093/mnras/staf647
Citations
4
Primary Topic
Astronomy and Astrophysical Research
Type
article
Field-Weighted Citation Impact
4.77

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article

The power spectrum of galaxies from large to small scales: a line-intensity mapping perspective

Kana Moriwaki, Sownak Bose, Rui Jun, Tom Theuns
4 citations
Monthly Notices of the Royal Astronomical Society
Astronomy and Astrophysical Research
4.77
article

The power spectrum of galaxies from large to small scales: a line-intensity mapping perspective

Kana Moriwaki, Sownak Bose, Rui Jun, Tom Theuns
article en
4 citations

Abstract

ABSTRACT We present a model for the power spectrum of the density field of galaxies weighted by their star formation rate. This weighting is relevant in line-intensity mapping (lim) when the observed line luminosity is strongly correlated with star formation, as is the case for the H $\alpha$ line. Our model reproduces the measured power spectrum in the illustris tng simulation to within a few per cent across all scales, with fitting parameters that have clear physical interpretations. On scales of tens of megaparsecs, the model accounts for the weighted non-linear bias of galaxies as well as halo exclusion (two-halo term). On smaller scales, it incorporates the weighted distribution of satellite galaxies within haloes (one-halo term). The random sampling of satellite galaxies introduces a galaxy shot noise term to the power spectrum on small scales, and their confinement to haloes introduces a halo shot noise term on large scales. Omitting satellite galaxies from the analysis results in an underestimation of both the large-scale bias and the mean intensity by $\sim 30$ per cent each at $z \sim 1.5$. Assigning the intensity of satellites to the centre of their respective haloes affects the power spectrum on scales $k \gtrsim 0.3\ {\rm h\, Mpc^{-1}}$. Our fitting function provides a well-motivated parametrization that can be used to interpret data from upcoming lim surveys.

Monthly Notices of the Royal Astronomical SocietyVol. 540(1)
Durham University (GB), The University of Tokyo (JP)
UK Research and Innovation, University of Tokyo, Science and Technology Facilities Council, Japan Society for the Promotion of Science
Openalex Percentile: Top 6%
Astronomy and Astrophysical Research
4.77
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The power spectrum of galaxies from large to small scales: a line-intensity mapping perspective — Kana Moriwaki, Sownak Bose, et al. · Monthly Notices of the Royal Astronomical Society (2025) | TGRS Research Map | TGRS