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The BINGO project X. Cosmological parameter constraints from HI Intensity Mapping lognormal simulations

Using lognormal simulations to account for key systematics, this study forecasts that the BINGO HI intensity mapping experiment, when combined with Planck CMB data, will significantly tighten cosmological parameter constraints and provide competitive measurements of dark energy evolution.

Original authors: Pablo Motta, Filipe B. Abdalla, Camila P. Novaes, Elcio Abdalla, Jiajun Zhang, Gabriel A. Hoerning, Alessandro Marins, Eduardo J. de Mericia, Luiza O. Ponte, Amilcar R. Queiroz, Thyrso Villela, Bin Wa

Published 2026-03-25

📖 5 min read🧠 Deep dive

CC BY 4.0

Original authors: Pablo Motta, Filipe B. Abdalla, Camila P. Novaes, Elcio Abdalla, Jiajun Zhang, Gabriel A. Hoerning, Alessandro Marins, Eduardo J. de Mericia, Luiza O. Ponte, Amilcar R. Queiroz, Thyrso Villela, Bin Wang, Carlos A. Wuensche, Chang Feng, Edmar C. Gurjão

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

The Big Picture: Listening to the "Hum" of the Universe

Imagine the universe as a giant, quiet library. For decades, astronomers have been trying to understand how this library is organized and how it's expanding. Usually, they do this by looking at individual "books" (galaxies) one by one. But there are so many books, and they are so far away, that counting them one by one is like trying to count every grain of sand on a beach using a magnifying glass. It takes forever and is incredibly expensive.

Enter BINGO (Baryon Acoustic Oscillations from Integrated Neutral Gas Observations). Instead of counting individual grains of sand, BINGO is a new kind of radio telescope designed to listen to the "hum" of the entire beach at once.

This "hum" is made of Neutral Hydrogen (HI), the most common gas in the universe. Even though we can't see this gas with our eyes, it emits a faint radio signal. BINGO's job is to map this signal across a huge chunk of the sky to see how the universe is stretching and growing.

The Problem: The Signal is a Whisper in a Hurricane

There is a catch. The signal from the hydrogen gas is incredibly faint—about 10,000 times weaker than the "noise" coming from our own galaxy and other bright radio sources.

The Analogy: Imagine trying to hear a single person whispering a secret in the middle of a rock concert. The "whisper" is the hydrogen signal; the "rock concert" is the foreground noise (stars, dust, and other radio sources).
The Challenge: To hear the whisper, you have to be incredibly good at filtering out the music without accidentally deleting the whisper along with it.

What This Paper Did: The "Simulation" Test Drive

Since the BINGO telescope hasn't finished collecting all its real data yet, the authors of this paper built a virtual version of the experiment. Think of this as a high-tech flight simulator for cosmologists.

Creating the Fake Universe: They used a computer program to generate 3,000 different "fake universes." In these simulations, they created the hydrogen signal, added the "rock concert" noise (foregrounds), and even added the static hiss of the radio receiver itself (thermal noise).
The Noise-Canceling Headphones: They applied a sophisticated algorithm (called FastICA) to these fake maps. This is like putting on noise-canceling headphones that are smart enough to identify the rock concert and mute it, leaving only the whisper.
The Test: They then tried to measure the properties of the universe using these cleaned-up fake maps to see if their math worked.

The Results: A Super-Team Up

The team compared their BINGO simulation results with data from Planck, a famous satellite that mapped the Cosmic Microwave Background (the "baby picture" of the universe).

The Result: When they combined the "baby picture" (Planck) with the "adult map" (BINGO), the results were amazing.
The Analogy: Imagine you are trying to guess the weight of a mystery box. Planck gives you a very good guess. But when you add BINGO's data, it's like suddenly getting a second, independent scale that confirms the weight. The uncertainty in their guess shrank by about 60%. They went from "It's probably between 10 and 12 pounds" to "It's definitely between 10.8 and 11.2 pounds."

Why This Matters: The Mystery of Dark Energy

The main reason we are doing all this is to understand Dark Energy. This is the mysterious force pushing the universe apart, making it expand faster and faster.

The Mystery: We know Dark Energy exists, but we don't know what it is. Is it a constant force? Does it change over time?
The BINGO Advantage: Planck is great at looking at the early universe, but it's not as good at seeing what's happening right now (in the last few billion years). BINGO is designed to look at that specific "recent" era.
The Finding: By combining BINGO and Planck, the team could put much tighter constraints on Dark Energy. They found that the data is consistent with the idea that Dark Energy is a constant force (the "Cosmological Constant"), but their method is now sensitive enough to detect if that force is changing in the future.

The Bottom Line

This paper is a "dress rehearsal." It proves that the BINGO telescope, once it starts taking real data, will be a powerful tool. Even with the "rock concert" of noise and the "static" of the equipment, the team showed that their methods can successfully filter out the noise and reveal the secrets of the universe's expansion.

In short: They built a virtual universe, taught a computer to filter out the noise, and proved that when BINGO goes live, it will help us finally understand the invisible force driving the universe apart.

1. Problem Statement

The late-time accelerated expansion of the Universe, driven by Dark Energy (DE), remains one of the most significant challenges in modern cosmology. While the standard $\Lambda$ CDM model is supported by various observations (CMB, SNe Ia, galaxy surveys), it faces theoretical issues (cosmological constant and coincidence problems) and observational tensions (e.g., $H_0$ and $\sigma_8$ tensions).

Traditional galaxy redshift surveys are limited by the faintness of galaxies at high redshifts and the high cost of observing large volumes. Neutral Hydrogen (HI) Intensity Mapping (IM) offers a more efficient alternative by measuring the aggregate 21-cm emission from many galaxies within a beam, rather than resolving individual sources. However, HI IM faces significant challenges:

Foreground Contamination: The HI signal ( $\sim 1$ mK) is orders of magnitude weaker than astrophysical foregrounds ( $\sim 10$ K), such as Galactic synchrotron radiation and point sources.
Systematic Effects: Instrumental noise (thermal and $1/f$ ), beam resolution, and imperfect foreground removal can bias cosmological parameter estimation.
Lack of Robust Forecasts: There is a need to quantify how well next-generation experiments like BINGO (Baryon Acoustic Oscillations from Integrated Neutral Gas Observations) can constrain cosmological parameters when realistic systematics and noise are included.

2. Methodology

The authors performed a comprehensive forecast analysis for the BINGO Phase 1 configuration using a Bayesian inference framework.

A. Simulation Framework

Cosmological Signal: Generated 3,000 independent realizations of the 21-cm brightness temperature using the FLASK code. The signal was modeled as a multivariate lognormal distribution to avoid non-physical negative densities and accurately capture non-Gaussian features of the matter distribution.
Foregrounds: Simulated seven foreground components (synchrotron, free-free, thermal dust, anomalous microwave emission, thermal/kinetic Sunyaev-Zel'dovich effects, and unresolved radio point sources) using the Planck Sky Model (PSM).
Instrumental Effects:
- Added thermal (white) noise based on BINGO specifications ( $T_{sys} = 70$ K, 28 horns, 5-year mission).
- Applied a Gaussian beam smoothing ( $\theta_{FWHM} = 40$ arcmin).
- Applied a sky mask to exclude the Galactic plane and define the survey area ( $\sim 5324$ deg $^2$ ).
Foreground Removal: Applied the FastICA (Fast Independent Component Analysis) algorithm to the contaminated maps to perform blind foreground removal, recovering the 21-cm signal and residual noise.

B. Data Analysis Pipeline

Angular Power Spectrum (APS): Calculated the pseudo- $C_\ell$ from the simulated maps using the UCLCl code.
Bias Correction: Implemented a debiasing procedure to correct for:
1. Additive bias: Instrumental noise power.
2. Multiplicative bias: Signal attenuation caused by the component separation pipeline (quantified by a factor $\beta_\ell$ ).
Covariance Matrix: Computed the full covariance matrix from the ensemble of 3,000 simulations to account for cosmic variance and correlations between multipoles.
Likelihood & Sampling:
- Used a Gaussian likelihood function based on the APS and covariance matrix.
- Employed Nested Sampling (via the Pliny code) to explore the parameter space.
- Parameters: Constrained 6 standard $\Lambda$ CDM parameters ( $\Omega_b h^2, \Omega_c h^2, 100\theta_s, n_s, \ln 10^{10}A_s, \tau_r$ ) and 60 HI parameters (bias $b_{HI}$ and density $\Omega_{HI}$ for each of the 30 frequency bins).
- Models: Tested both the standard $\Lambda$ CDM model and the dynamical dark energy $w_0 w_a$ CDM model.
- Combination: Jointly analyzed BINGO simulations with the Planck 2018 CMB likelihood.

3. Key Contributions

Realistic Systematic Modeling: Unlike previous idealized forecasts, this work incorporates a full pipeline including lognormal signal generation, multi-component foreground simulation, FastICA cleaning, and instrumental noise.
Debiasing Technique: Demonstrated a robust method to correct the APS for signal loss induced by foreground removal, ensuring unbiased parameter recovery.
High-Dimensional Parameter Space: Successfully constrained a massive parameter space (66 parameters for $\Lambda$ CDM) simultaneously, including the redshift evolution of HI density and bias across 30 frequency channels.
Validation of Robustness: Verified that the methodology yields consistent results across 3,000 simulation realizations and remains stable even when adding white noise and foreground residuals.

4. Key Results

Improved Cosmological Constraints: Combining BINGO with Planck 2018 data tightens the confidence regions of cosmological parameters to $\sim 40\%$ of the size of Planck-only constraints.
- Specific improvements include a 58% reduction in uncertainty for $\Omega_b h^2$ , 61% for $\Omega_c h^2$ , and 63% for $H_0$ .
- The joint analysis significantly improves constraints on the optical depth to reionization ( $\tau_r$ ) by breaking degeneracies with $A_s$ and $n_s$ .
Dark Energy Constraints:
- Planck alone cannot tightly constrain the dark energy equation of state ( $w_0, w_a$ ).
- The joint BINGO + Planck analysis yields $w_0 = -0.62^{+0.20}_{-0.22}$ and $w_a = 0.0 \pm 1.3$ .
- These results are consistent with the fiducial $\Lambda$ CDM values ( $w_0=-1, w_a=0$ ) at the 1.9 $\sigma$ level, demonstrating BINGO's ability to probe the low-redshift expansion history where dark energy dominates.
HI Parameter Recovery:
- The pipeline successfully recovered the fiducial HI density ( $\Omega_{HI} b_{HI}$ ) and bias ( $b_{HI}$ ) values within 1–2 $\sigma$ confidence intervals across all 30 frequency channels.
- The inclusion of white noise and foreground residuals did not significantly increase parameter uncertainties, attributed to the high signal-to-noise ratio (SNR) in the analyzed multipole range ( $\ell < 165$ ).
Goodness of Fit: The reduced $\chi^2$ values for the fits were close to unity (ranging from 1.13 to 1.32), indicating excellent agreement between the theoretical models and the simulated data.

5. Significance

This paper establishes BINGO as a highly competitive experiment for precision cosmology. The results demonstrate that:

Feasibility: HI Intensity Mapping can effectively constrain cosmological parameters and the nature of Dark Energy when combined with CMB data.
Robustness: The proposed analysis pipeline, including blind foreground removal and debiasing, is robust against realistic observational systematics (noise and foreground residuals).
Complementarity: BINGO fills a critical gap by anchoring the low-redshift expansion history, complementing the high-redshift constraints provided by Planck.
Future Outlook: While the current study uses optimistic assumptions (e.g., Gaussian beams, stationary noise), it provides a validated benchmark. Future work will focus on incorporating more complex systematics (e.g., $1/f$ noise, beam leakage) to transition from forecasting to observational analysis.

In summary, this study validates the scientific potential of the BINGO project to extract significant cosmological information from the HI distribution, offering constraints competitive with current and future major cosmological surveys.