Probing cosmic voids with emission-line galaxies

Introduction We aim to provide forecasts for future line intensity mapping (LIM) observations and galaxy redshift surveys, focusing on the physical properties of low-density region of the cosmic web (voids). We study how the measured physical properties depend on the observational methods for void detection and identification. Methods We generate mock intensity maps targeting the far-infrared CO(3–2) emission line by assigning the line luminosities to dark matter halos in cosmological simulations. The popular void-finding algorithm VIDE is applied to identify cosmic voids and quantify their properties. We analyze the voids detected in two different observation modes: (1) three-dimensional galaxy redshift surveys and (2) two-dimensional LIM observations corresponding to a single-frequency bin at 173 GHz. Results We find that the measured void size functions and radial density profiles differ depending on the observational method. These features exhibit characteristic signatures that reflect both the underlying cosmology and the nature of the emission-line galaxies. Discussion LIM-based void detection is a promising avenue for cosmological studies. We discuss the potential of combining LIM and galaxy survey data in a joint analysis to improve constraints on cosmological parameters and to better understand emission-line galaxy populations.

Authors

Institutions

Publication Details

Journal
Frontiers in Astronomy and Space Sciences
Published
2025-06-20
DOI
https://doi.org/10.3389/fspas.2025.1607031
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Probing cosmic voids with emission-line galaxies

Yuka Yamada, Naoki Yoshida
Frontiers in Astronomy and Space Sciences
Galaxies: Formation, Evolution, Phenomena
article

Probing cosmic voids with emission-line galaxies

Yuka Yamada, Naoki Yoshida
article en

Abstract

Introduction We aim to provide forecasts for future line intensity mapping (LIM) observations and galaxy redshift surveys, focusing on the physical properties of low-density region of the cosmic web (voids). We study how the measured physical properties depend on the observational methods for void detection and identification. Methods We generate mock intensity maps targeting the far-infrared CO(3–2) emission line by assigning the line luminosities to dark matter halos in cosmological simulations. The popular void-finding algorithm VIDE is applied to identify cosmic voids and quantify their properties. We analyze the voids detected in two different observation modes: (1) three-dimensional galaxy redshift surveys and (2) two-dimensional LIM observations corresponding to a single-frequency bin at 173 GHz. Results We find that the measured void size functions and radial density profiles differ depending on the observational method. These features exhibit characteristic signatures that reflect both the underlying cosmology and the nature of the emission-line galaxies. Discussion LIM-based void detection is a promising avenue for cosmological studies. We discuss the potential of combining LIM and galaxy survey data in a joint analysis to improve constraints on cosmological parameters and to better understand emission-line galaxy populations.

Frontiers in Astronomy and Space SciencesVol. 12
Bunkyo University (JP), Kavli Institute for the Physics and Mathematics of the Universe (JP), The University of Tokyo (JP)
Ministry of Education, Culture, Sports, Science and Technology, Japan Society for the Promotion of Science
Openalex Percentile: Top 91%
Galaxies: Formation, Evolution, Phenomena
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.