Line-intensity mapping: theory review with a focus on star-formation lines

Bernal, José Luís; Kovetz, Ely D.

doi:10.1007/s00159-022-00143-0

Cited by 40 publications

(21 citation statements)

References 237 publications

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“…We here briefly comment on the promising possibilities of line intensity mapping (LIM) [98,99]. Similarly to the anisotropy measurements previously described, rather than identifying galaxies, LIM aims at measuring the integrated emission of spectral lines from both galaxies and the intergalactic medium (IGM) with small low-aperture instruments.…”

Section: Line Intensity Mapping Projected Reachmentioning

confidence: 99%

Probing the Blue Axion with Cosmic Optical Background Anisotropies

Lucente¹,

Vitagliano²

2023

Preprint

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Section: Line Intensity Mapping Projected Reachmentioning

confidence: 99%

Probing the Blue Axion with Cosmic Optical Background Anisotropies

Lucente¹,

Vitagliano²

2023

Preprint

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“…One of the potentially powerful aspects of LIM is that there are now numerous experiments planned or online that probe different lines, trace different gas phases, and at different redshifts (see Bernal & Kovetz 2022, for a recent summary).…”

Section: Introductionmentioning

confidence: 99%

“…In order to do this, it is essential to have a comprehensive modeling framework (see, e.g., Conroy et al 2006;Lagos et al 2012;Yue et al 2015;Ihle et al 2019;Kannan et al 2022;Mas-Ribas et al 2022;Sato-Polito et al 2022, for some related discussions). The most commonly used framework is halobased phenomenological models (see Bernal & Kovetz 2022, for a recent review). In this approach, scaling relations between halo mass and redshift and "intrinsic" physical properties such as stellar mass and star formation rate (SFR) are derived using abundance matching.…”

Section: Introductionmentioning

confidence: 99%

Characterizing the Conditional Galaxy Property Distribution Using Gaussian Mixture Models

Zhang

Pullen

Somerville

et al. 2023

ApJ

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Line-intensity mapping (LIM) is a promising technique to constrain the global distribution of galaxy properties. To combine LIM experiments probing different tracers with traditional galaxy surveys and fully exploit the scientific potential of these observations, it is necessary to have a physically motivated modeling framework. As part of developing such a framework, in this work, we introduce and model the conditional galaxy property distribution (CGPD), i.e., the distribution of galaxy properties conditioned on the host halo mass and redshift. We consider five galaxy properties, including the galaxy stellar mass, molecular gas mass, galaxy radius, gas-phase metallicity, and star formation rate (SFR), which are important for predicting the emission lines of interest. The CGPD represents the full distribution of galaxies in the five-dimensional property space; many important galaxy distribution functions and scaling relations, such as the stellar mass function and SFR main sequence, can be derived from integrating and projecting it. We utilize two different kinds of cosmological galaxy simulations, a semi-analytic model and the IllustrisTNG hydrodynamic simulation, to characterize the CGPD and explore how well it can be represented using a Gaussian mixture model (GMM). We find that with just a few (approximately three) Gaussian components, a GMM can describe the CGPD of the simulated galaxies to high accuracy for both simulations. The CGPD can be mapped to LIM or other observables by constructing the appropriate relationship between galaxy properties and the relevant observable tracers, which will be discussed in future works.

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“…Line intensity mapping (LIM) is another emerging technique to probe the 3D LSS from spectral-intensity maps. By mapping a particular spectral line emission, LIM infers the line-of-sight distance of the emission sources from the frequency-redshift relation (e.g., Kovetz et al 2017;Bernal & Kovetz 2022). However, as LIM only analyzes a single spectral line, the majority of emissions from the full SED have not only been discarded, but also become the continuum (e.g., Yue et al 2015) or interloper line (e.g., Cheng et al 2016Cheng et al , 2020Lidz & Taylor 2016) foregrounds in LIM measurements.…”

Section: Introductionmentioning

confidence: 99%

Data-driven Cosmology from Three-dimensional Light Cones

Cheng

Wandelt

Chang

et al. 2023

ApJ

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We present a data-driven technique to analyze multifrequency images from upcoming cosmological surveys mapping large sky area. Using full information from the data at the two-point level, our method can simultaneously constrain the large-scale structure (LSS), the spectra and redshift distribution of emitting sources, and the noise in the observed data without any prior assumptions beyond the homogeneity and isotropy of cosmological perturbations. In particular, the method does not rely on source detection or photometric or spectroscopic redshift estimates. Here, we present the formalism and demonstrate our technique with a mock observation from nine optical and near-infrared photometric bands. Our method can recover the input signal and noise without bias, and quantify the uncertainty on the constraints. Our technique provides a flexible framework to analyze the LSS observation traced by different types of sources, which has potential for wide application to current or future cosmological data sets such as SPHEREx, Rubin Observatory, Euclid, or the Nancy Grace Roman Space Telescope.

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Line-intensity mapping: theory review with a focus on star-formation lines

Cited by 40 publications

References 237 publications

Probing the Blue Axion with Cosmic Optical Background Anisotropies

Probing the Blue Axion with Cosmic Optical Background Anisotropies

Characterizing the Conditional Galaxy Property Distribution Using Gaussian Mixture Models

Data-driven Cosmology from Three-dimensional Light Cones

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