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The Dark Energy Camera All Data Everywhere cosmic shear project V: Constraints on cosmology and astrophysics from 270 million galaxies across 13,000 deg $^2$ of the sky

This paper presents the largest cosmic shear analysis to date using 270 million galaxies across 13,000 deg² from the DECADE and DES Year 3 datasets, deriving robust constraints on $\Lambda$ CDM cosmology and dynamical dark energy while demonstrating that current scale-cut methods introduce a residual bias in $S_8$ and $\Omega_{\rm m}$ that can only be fully mitigated by external baryon model calibrations.

Original authors: D. Anbajagane, C. Chang, A. Drlica-Wagner, C. Y. Tan, M. Adamow, R. A. Gruendl, L. F. Secco, Z. Zhang, M. R. Becker, P. S. Ferguson, N. Chicoine, K. Herron, A. Alarcon, R. Teixeira, D. Suson, A. J. Sh

Published 2026-07-16

📖 4 min read☕ Coffee break read

CC BY 4.0

Original authors: D. Anbajagane, C. Chang, A. Drlica-Wagner, C. Y. Tan, M. Adamow, R. A. Gruendl, L. F. Secco, Z. Zhang, M. R. Becker, P. S. Ferguson, N. Chicoine, K. Herron, A. Alarcon, R. Teixeira, D. Suson, A. J. Shajib, J. A. Frieman, A. N. Alsina, A. Amon, F. Andrade-Oliveira, J. Blazek, C. R. Bom, H. Camacho, J. A. Carballo-Bello, A. Carnero Rosell, R. Cawthon, W. Cerny, A. Choi, Y. Choi, S. Dodelson, C. Doux, K. Eckert, J. Elvin-Poole, J. Esteves, M. Gatti, G. Giannini, D. Gruen, W. G. Hartley, K. Herner, E. M. Huff, B. Jain, D. J. James, M. Jarvis, E. Krause, N. Kuropatkin, C. E. Martínez-Vázquez, P. Massana, S. Mau, J. McCullough, G. E. Medina, B. Mutlu-Pakdil, J. Myles, M. Navabi, N. E. D. Noël, A. B. Pace, S. Pandey, A. Porredon, J. Prat, M. Raveri, A. H. Riley, E. S. Rykoff, J. D. Sakowska, S. Samuroff, D. Sanchez-Cid, D. J. Sand, L. Santana-Silva, I. Sevilla-Noarbe, T. Shin, M. Soares-Santos, G. S. Stringfellow, C. To, E. J. Tollerud, A. Tong, M. A. Troxel, A. K. Vivas, M. Yamamoto, B. Yanny, B. Yin, A. Zenteno, Y. Zhang, J. Zuntz

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, invisible ocean. We can't see the water itself, but we can see how it ripples and bends the light from distant stars, much like how a funhouse mirror distorts your reflection. This bending of light is called weak lensing. It happens because massive things—like clusters of galaxies and invisible "dark matter"—act as gravity lenses, warping the fabric of space and time. By measuring these tiny distortions in the shapes of billions of galaxies, astronomers can map out the invisible skeleton of the cosmos. This isn't just about drawing a pretty picture; it's about figuring out the rules of the game. Is the universe expanding at a steady pace, or is some mysterious "dark energy" pushing it apart faster and faster? How much stuff is actually in the universe? These questions are the holy grail of modern cosmology, and the answers could rewrite our understanding of reality.

Now, enter the Dark Energy Camera All Data Everywhere (DECADE) project. Think of this team as the ultimate cosmic detectives who decided to stop looking at just a few clues and instead scan the entire crime scene. In this new paper, they have combined data from three massive surveys to create the largest weak lensing dataset ever assembled: a staggering 270 million galaxies spread across 13,000 square degrees of the sky (which is about one-third of the entire sky you can see from Earth).

The team used this massive dataset to test the standard model of the universe, known as $\Lambda$ CDM. Their main finding is a set of precise measurements for two key numbers: the amount of matter in the universe ( $\Omega_m$ ) and how clumpy that matter is ( $S_8$ ). They found that the universe is about 26.2% matter and that the "clumpiness" parameter is 0.805. These numbers are very close to what the Planck satellite found by looking at the baby picture of the universe (the Cosmic Microwave Background), differing by less than 1.9 standard deviations. This suggests that our current understanding of the universe is holding up well, even when we look at it in a completely different way.

However, the detectives didn't just stop at the standard model. They also looked for signs of "dynamic dark energy"—a theory that the force pushing the universe apart might change over time, like a car that speeds up or slows down. When they combined their galaxy data with other measurements (like supernovae and the "baryon acoustic oscillations," which are like sound waves frozen in the early universe), they found a slight hint that dark energy might be evolving. The data suggests a tension with the standard model at about 3.2 to 3.5 standard deviations, which is intriguing but not yet a slam-dunk proof. It's a whisper of a new physics, not a shout.

One of the most playful parts of the paper deals with baryons (normal matter like stars and gas). The authors treated the universe like a giant soufflé. When you bake a soufflé, the heat makes it rise, but if you mess with the ingredients, it might collapse or change shape. Similarly, the gas and stars in the universe push against gravity, changing how matter clumps together on small scales. The team tested several different "recipes" (models) for how this baryon soup affects the cosmic map. They found that while the recipes look different on paper, they all lead to the same result: the matter power spectrum is suppressed by about 25%.

Crucially, the paper argues that simply looking at more data (using all scales, even the tiny, messy ones) doesn't automatically solve the mystery of dark matter and dark energy. It turns out that the small scales are so dominated by the "baryon noise" that the extra data mostly just helps them tune their "baryon recipe" rather than revealing new cosmic secrets. To get the full power of these measurements, they need help from other types of observations to calibrate the baryon models.

In short, this paper is a massive success story of data collection. It confirms that the standard model of cosmology is robust, even with the biggest lensing dataset ever created. It suggests that while there might be a tiny crack in the wall of our current theories regarding dark energy, we need to be very careful before knocking the wall down. The universe is still a bit of a puzzle, but thanks to 270 million galaxies, we have a much clearer picture of the pieces we do have.

Technical Summary: The Dark Energy Camera All Data Everywhere (DECADE) Cosmic Shear Project V

Problem and Motivation
Weak lensing (WL) is a primary probe for constraining cosmological parameters and testing models of structure growth and dark energy. However, WL measurements are sensitive to systematic uncertainties, particularly those arising from baryonic feedback on small scales and intrinsic alignments (IA) of galaxies. While previous analyses, such as the Dark Energy Survey (DES) Year 3 (Y3) and the initial DECADE Northern Galactic Cap (NGC) results, provided significant constraints, they were limited in sky coverage. The DECADE project aims to assemble, validate, and analyze the largest weak lensing dataset to date to test cosmological models and assess the impact of astrophysical systematics. This paper (Paper V) extends the analysis to include the Southern Galactic Cap (SGC) and combines it with DES Y3 data, creating a unified dataset of 270 million galaxies across 13,000 deg². The primary challenges addressed include quantifying the tension between WL and Cosmic Microwave Background (CMB) constraints, evaluating dynamical dark energy models, and determining the efficacy of scale cuts versus explicit baryon modeling in mitigating astrophysical biases.

Methodology
The analysis utilizes three distinct cosmic shear data vectors: DECADE NGC, DECADE SGC, and DES Y3.

Data Assembly: The DECADE SGC region adds 3,356 deg² of sky surrounding the DES footprint, containing 63 million galaxies. The total combined dataset ("DECam 13k") covers 13,000 deg². The analysis follows the DES Y3 pipeline closely, employing the HMCode model for the nonlinear matter power spectrum and the Tidally Aligned Tidally Torqued (TATT) model for intrinsic alignments.
Inference Framework: The study employs a Markov Chain Monte Carlo (MCMC) approach using the Polychord sampler within the CosmoSIS package. The likelihood function assumes a Gaussian distribution of the angular two-point correlation functions ( $\xi_{\pm}$ ). Covariance matrices are computed using CosmoCov, incorporating Gaussian terms, connected four-point terms for nonlinear structure, super-sample covariance, and mask corrections.
Baryon Modeling: To address baryonic suppression of the matter power spectrum, the authors utilize a unified pipeline based on the BaryonForge codebase. This allows for the emulation of three distinct phenomenological models: BCEmu, Bacco, and HMx. The study compares constraints derived from:
1. Standard scale cuts (excluding small scales).
2. Using all scales with explicit baryon modeling.
3. Using all scales without baryon modeling.
External Probes: The analysis is extended by combining WL data with Baryon Acoustic Oscillation (BAO) data from DESI DR2 and Supernova (SNe) data from DES Y5 and historical samples to constrain dynamical dark energy models ( $w_0w_a$ and $w_\phi$ ).

Key Contributions

Largest Weak Lensing Dataset: This work presents the largest weak lensing analysis to date, combining 270 million galaxies over 13,000 deg². The dataset serves as a testing ground for upcoming Stage IV surveys like LSST.
Unified Baryon Modeling: The paper introduces a consistent framework (BaryonForge) to compare different baryon suppression models (BCEmu, Bacco, HMx) on the same dataset, demonstrating that concordance in cosmological constraints can be achieved if astrophysical priors are sufficiently wide.
Systematic Bias Quantification: The study quantifies the residual bias introduced by baryonic effects when using standard scale cuts, finding a shift of approximately $0.3\sigma$ in the $S_8-\Omega_m$ plane.
Dynamical Dark Energy Constraints: The paper provides updated constraints on dynamical dark energy models, assessing the marginal improvement lensing offers over BAO and SNe data alone.

Results

$\Lambda$ CDM Constraints: The fiducial analysis yields $S_8 = 0.805 \pm 0.019$ and $\Omega_m = 0.262^{+0.023}_{-0.036}$ . These results are consistent with Planck 2018 constraints within $1.9\sigma$ . The Figure of Merit (FoM) for the DECam 13k dataset improves by a factor of three compared to DES Y3 alone.
Dynamical Dark Energy: When combined with BAO and SNe data, the constraints on dynamical dark energy models show deviations from $\Lambda$ CDM at the $3.2\sigma$ ( $w_0w_a$ ) and $3.5\sigma$ ( $w_\phi$ ) levels. The addition of weak lensing data provides noticeable but minor improvements to these constraints, primarily in directions orthogonal to the best-constrained axes of the BAO/SNe data.
Baryon Modeling and Scale Cuts:
- Different baryon models (BCEmu, Bacco, HMx) yield consistent constraints on the suppression of the matter power spectrum (approximately 25%) and cosmology, provided that astrophysical priors are widened (e.g., for Bacco and HMx).
- Using all scales with explicit baryon modeling improves the FoM by only 7% compared to the fiducial analysis using scale cuts. The additional information from small scales is primarily used to self-calibrate the baryon model rather than to tighten cosmological constraints.
- Current scale-cut approaches result in a residual bias of $\approx 0.3\sigma$ in the $S_8-\Omega_m$ posterior.
Intrinsic Alignments: The SGC data alone shows no significant detection of intrinsic alignments ( $a_1=0, a_2=0$ ), consistent with the NGC and DES Y3 results.

Significance and Claims
The paper claims that the DECam 13k dataset represents the most comprehensive weak lensing analysis available, offering a robust testing ground for the analysis strategies of future surveys. The authors emphasize that while the dataset has tripled the sky coverage of precision WL data, the statistical power of lensing measurements on small scales is currently limited by the inability to "self-calibrate" baryon suppression models solely from lensing data. The study concludes that to fully exploit the statistical power of small-scale lensing data, external probes (such as the thermal and kinetic Sunyaev-Zeldovich effects) or dedicated calibrations of the baryon model are required. The work also highlights that the current precision is limited primarily by baryon suppression uncertainties and intrinsic alignment signals, rather than redshift calibration. The authors make the DECADE shear catalogs, data vectors, and likelihoods publicly available to facilitate further cross-correlation analyses and science exploitation by the broader community.

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