🔭 astrophysics

Cosmology with HI Intensity Mapping

This chapter outlines the Square Kilometre Array Observatory's (SKAO) strategy for conducting neutral hydrogen (HI) intensity mapping surveys across redshifts 0 to 6 using both SKA-Mid and SKA-Low, detailing the methodologies, observational challenges, and cosmological forecasts for constraining the LambdaCDM model through power spectrum and other statistical analyses.

Original authors: Laura Wolz, Gabriele Autieri, José Luis Bernal, Maria Berti, Philip Bull, Stefano Camera, Isabella P. Carucci, Zhaoting Chen, Steven Cunnington, José Fonseca, Keith Grainge, Jiakang Han, Wenkai Hu, Di

Published 2026-07-07

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Laura Wolz, Gabriele Autieri, José Luis Bernal, Maria Berti, Philip Bull, Stefano Camera, Isabella P. Carucci, Zhaoting Chen, Steven Cunnington, José Fonseca, Keith Grainge, Jiakang Han, Wenkai Hu, Dionysios Karagiannis, Mario G. Santos, Marta Spinelli, Liantsoa F. Randrianjanahary, Cora Uhlemann, Matteo Viel, Bernhard Vos-Ginés, Jingying Wang

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine the universe as a giant, three-dimensional city built over billions of years. For a long time, astronomers have tried to map this city by looking at the "lights" of individual houses (galaxies). But this is like trying to understand the layout of a massive metropolis by counting streetlights one by one; it takes forever, and you miss the big picture of the neighborhoods and the highways connecting them.

This paper introduces a new way to map the universe using the Square Kilometre Array (SKA), a massive radio telescope project. Instead of counting individual houses, the SKA will listen to the "hum" of the entire city at once.

Here is a breakdown of the paper's key ideas using simple analogies:

1. The "Hum" of the Universe (Hi Intensity Mapping)

The universe is filled with neutral hydrogen gas (Hi), which is the raw material for making stars. This gas emits a faint radio signal (a "hum") at a specific wavelength (21 cm).

The Old Way: Trying to detect this hum from a single galaxy is like trying to hear a whisper in a hurricane. You can only do it for very close, bright galaxies.
The New Way (Intensity Mapping): The SKA will listen to the combined hum of millions of galaxies in a single patch of sky. It doesn't care about individual houses; it measures the total volume of the "neighborhood." This allows them to map huge volumes of the universe very quickly, creating a 3D "heat map" of where matter is concentrated.

2. The Two Main Surveys: The Wide Scan and the Deep Dive

The paper outlines two specific ways the SKA will use this technique, depending on which part of the telescope is used:

SKA-Mid (The Wide Scan): Think of this as a security camera scanning a huge parking lot. It will sweep over a massive area (20,000 square degrees) to map the universe from the present day back to when the universe was about 11 billion years old ( $z < 3$ ). It moves fast, covering ground quickly.
SKA-Low (The Deep Dive): This is like using a powerful microscope to look at a tiny, ancient fossil. It will focus on a smaller area but look much deeper into the past, capturing the universe when it was very young (between 12 and 13 billion years old, $3 < z < 6$ ).

3. The Big Challenge: Tuning Out the Static

The "hum" of the hydrogen is incredibly faint. The main problem is that the universe is full of "static" (noise) that is thousands of times louder.

The Analogy: Imagine trying to hear a single violin in a stadium full of people cheering, with a nearby construction site, and a radio station broadcasting nearby.
The Solution: The paper explains that the "static" (from our own galaxy and other sources) has a smooth, predictable pattern, while the hydrogen signal changes rapidly. Astronomers use mathematical tricks to subtract the smooth static, leaving behind the rapid changes of the hydrogen signal. However, this is tricky because the telescope itself can sometimes distort the signal, creating "ghosts" in the data that need to be cleaned up.

4. What They Hope to Learn (The "Why")

By mapping this hydrogen hum, the scientists want to answer three major questions about the universe:

The Cosmic Ruler (BAO): The paper discusses "Baryon Acoustic Oscillations." Imagine the early universe was a giant drum that was hit once. The sound waves from that hit created ripples in the distribution of matter. These ripples left a specific "fingerprint" or standard ruler in the hydrogen map. By measuring the size of these ripples at different times, scientists can measure how fast the universe is expanding and figure out the nature of Dark Energy (the mysterious force pushing the universe apart).
The Cosmic Scale (Turnover): There is a specific size in the universe where the "clumping" of matter stops getting bigger. This is like the horizon line on a foggy day. Measuring this "turnover" point gives scientists another way to measure the universe's expansion and the Hubble constant (how fast the universe is growing), independent of other methods.
The Ghost Particles (Neutrinos): The paper predicts that this method will help weigh neutrinos (tiny, ghost-like particles that zip through everything). By seeing how the hydrogen gas clumps together, they can put a limit on how heavy these particles are.

5. Teamwork Makes the Dream Work

The paper emphasizes that this method works best when combined with other surveys.

The Analogy: If you are trying to solve a puzzle, looking at it from just one angle might be confusing. But if you look at it from the front (optical telescopes) and the side (radio telescopes), the picture becomes clear.
The Result: By combining the SKA's hydrogen map with data from optical telescopes (like the DESI or Euclid missions), they can cancel out errors and get a much more precise measurement of the universe's properties than any single telescope could achieve alone.

Summary

In short, this paper is a blueprint for using the SKA to listen to the "background noise" of the universe's most common gas. By turning this noise into a 3D map, astronomers hope to measure the universe's expansion, understand the mysterious forces driving it, and weigh the invisible particles that fill the cosmos. It's a shift from counting individual stars to listening to the song of the entire cosmos.

Technical Summary: Cosmology with Hi Intensity Mapping

Problem Statement
The primary challenge addressed in this chapter is the need for efficient, large-volume tracers of the large-scale structure (LSS) to constrain cosmological parameters, particularly those related to dark energy, dark matter, and the growth of structure. While optical and near-infrared spectroscopic surveys (e.g., DESI, Euclid, LSST) have achieved precision cosmology, they face limitations in survey speed and volume coverage. Neutral hydrogen (Hi) gas, ubiquitous throughout cosmic history, offers a complementary tracer. However, the 21 cm emission line from Hi is faint, and at high redshifts, individual galaxies are too dim to be resolved individually. Traditional resolved galaxy surveys are restricted to low redshifts ( $z < 0.4$ for the full SKA baseline). The problem is how to detect the collective Hi signal across vast cosmological volumes ( $0 < z < 6$ ) to measure the matter power spectrum and Baryon Acoustic Oscillations (BAO) without being overwhelmed by instrumental noise and foreground contamination that is orders of magnitude brighter than the target signal.

Methodology
The authors outline the Hi Intensity Mapping (IM) strategy for the Square Kilometre Array Observatory (SKAO), utilizing two distinct instrumental configurations:

SKA-Mid (Band 1 & 2): Operated in a fast-scanning single-dish mode to cover a wide area ( $20,000 \text{ deg}^2$ ) over the redshift range $0.35 < z < 3$ . This approach averages emission from unresolved galaxies within large voxels.
SKA-Low: Focused on deep observations in the $3 < z < 6$ range, commensal with Epoch of Reionization (EoR) surveys.

The methodology relies on modeling the Hi auto-power spectrum, $P_{\text{Hi}}(k, \mu, z)$ , which acts as a tracer for the matter power spectrum $P_m(k, z)$ . The theoretical framework includes:

Signal Modeling: The power spectrum is modeled as a function of the Hi bias ( $b_{\text{Hi}}$ ), the mean brightness temperature ( $T_{\text{Hi}}$ ), and the growth factor ( $f$ ), incorporating redshift-space distortions and the Alcock-Paczynski effect.
Noise and Systematics: The analysis accounts for instrument noise (system temperature, beam convolution) and foreground separation challenges. Foreground removal techniques discussed include "foreground avoidance" (excising contaminated Fourier modes) and data-driven blind removal (e.g., Principal Component Analysis), noting the necessity of correcting for signal loss via transfer functions.
Forecasting: The authors employ Fisher matrix forecasts and Bayesian analyses using synthetic data sets. They compare "pessimistic" scenarios (varying all nuisance parameters with wide priors) against "optimistic" scenarios (incorporating prior knowledge on bias and brightness temperature).
Synergies: The methodology extends to cross-correlations with other probes, specifically the Dark Energy Survey (DES) and Planck CMB data, to break degeneracies between cosmological and astrophysical parameters.

Key Contributions

Survey Definitions: The chapter establishes baseline survey parameters for SKAO Hi IM, defining the "Wide Band 1 Survey" (SKA-Mid) and the "Deep SKA1-LOW Survey," including integration times and sky coverage.
Systematic Characterization: It provides a detailed review of observational challenges specific to SKAO, including "zebra stripes" caused by gain non-linearities in MeerKAT precursors, primary beam chromaticity, and mutual coupling artifacts in SKA-Low.
Cosmological Forecasts: The paper presents updated forecasts for constraining $\Lambda$ CDM parameters, specifically $H_0$ , $\Omega_c h^2$ , and the sum of neutrino masses ( $\Sigma m_\nu$ ), using Hi power spectrum multipoles.
Large-Scale Features: The authors detail the potential for detecting the BAO scale and the matter-radiation equality turnover scale ( $k_0$ ) in the Hi power spectrum, the latter being a standard ruler independent of the sound horizon.
Multi-Tracer Analysis: The chapter demonstrates the statistical power of combining Hi IM with spectroscopic galaxy surveys (e.g., DES) to constrain bias parameters and redshift scatter, reducing sensitivity to systematics.

Results

Cosmological Constraints:
- $H_0$ : In a pessimistic scenario using SKAO Hi data alone, $H_0$ is constrained to $67.39 \pm 0.44 \text{ km s}^{-1} \text{Mpc}^{-1}$ , comparable to Planck alone ( $67.36 \pm 0.54$ ). In an optimistic scenario, the error reduces to $0.29$. When combined with Planck CMB data, the error on $H_0$ drops to $0.17$, a reduction of more than three times compared to Planck alone.
- Neutrino Mass: Hi data alone provides upper limits on $\Sigma m_\nu$ comparable to single-instrument CMB observations ( $\Sigma m_\nu < 0.287 \text{ eV}$ optimistic; $< 0.425 \text{ eV}$ pessimistic). Combining Hi with Planck significantly tightens these constraints to $< 0.105 \text{ eV}$ (optimistic) and $< 0.126 \text{ eV}$ (pessimistic).
- BAO and Turnover: The SKA-Mid wide survey is forecast to provide competitive constraints on the Hubble parameter and comoving angular diameter distance ( $\alpha_\parallel$ and $\alpha_\perp$ ) relative to DESI. The turnover feature is predicted to be detected with high statistical significance ( $13.1\sigma$ ), offering a $H_0$ constraint of $\sim 2\%$ independent of the sound horizon.
Synergy: Cross-correlation with DES is shown to effectively constrain tracer bias and photometric redshift scatter, breaking degeneracies that limit single-probe analyses.

Significance
The authors position Hi Intensity Mapping with the SKAO as a "new, competitive cosmological probe" that is complementary to CMB and optical surveys. The significance of this work lies in demonstrating that Hi IM can achieve statistical precision on key cosmological parameters (particularly $H_0$ and neutrino mass) that rivals or exceeds current state-of-the-art observations, especially when combined with other datasets. The chapter emphasizes that while observational systematics (foregrounds, calibration) remain significant challenges, the unique ability of Hi IM to map enormous cosmic volumes rapidly makes it pivotal for resolving tensions in cosmology and understanding the nature of dark energy. The work serves as a foundational overview for the SKAO's Hi IM capabilities, updating previous science cases with refined methodologies and forecasts for the $0 < z < 6$ epoch.