The Atacama Cosmology Telescope: DR6 Sunyaev-Zel'dovich Selected Galaxy Clusters Catalog

We present the results of a search for galaxy clusters in the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) microwave sky maps covering 16293 square degrees in three frequency bands, using data obtained over the lifetime of the project (2008-2022). We report redshifts and mass estimates for 10040 clusters detected via their Sunyaev-Zel’dovich (SZ) effect with signal-to-noise greater than 4 at a 2.4 arcminute filter scale. The catalog includes 1180 clusters at redshifts greater than 1, and 124 clusters at redshifts greater than 1.5. Using a relation between cluster SZ signal and mass that is consistent with recent weak-lensing measurements, we estimate that clusters detected with signal-to-noise greater than 5 form a sample which is 90% complete for clusters with masses greater than $5 \times 10^{14}$ MSun (measured within a spherical volume with mean density 500 times the critical density). El Gordo, a cluster found in an initial ACT survey of 755 square degrees, remains the most extreme cluster in mass and redshift; we find no cluster with a mass and redshift combination high enough to falsify the standard LCDM cosmology with Gaussian initial perturbations. We make public a variety of data products, including the full cluster candidate list, noise maps, and sky masks, along with our software for cluster detection and instructions for reproducing our cluster catalogs from the public ACT maps.

💡 Research Summary

The paper presents the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) Sunyaev‑Zel’dovich (SZ) selected galaxy‑cluster catalog, the largest SZ‑selected sample to date. Using the full set of observations from 2008‑2022 across three frequency bands (90, 150, 220 GHz) with angular resolutions of 2.1′, 1.4′, 1.0′, the authors co‑added maps covering 16 293 deg². Cluster detection was performed with the open‑source Nemo pipeline, employing a multi‑frequency matched filter that incorporates the non‑relativistic SZ spectrum, the Universal Pressure Profile (UPP) convolved with the ACT beams, and a noise covariance estimated directly from the maps. A new multi‑pass strategy first identifies and masks bright point sources (S/N > 50), then fainter sources (S/N > 5), before applying the SZ filter; this reduces bias in the noise estimate and improves completeness.

The search area was tiled into 25° × 2° regions to mitigate projection effects at high declination, and the filter was evaluated over 16 angular scales corresponding to a grid of masses (1‑8 × 10¹⁴ M⊙) and redshifts (0.2‑1.2). Candidates were assigned an optimal signal‑to‑noise (q) and a reference‑scale S/N (˜q) measured at a 2.4′ filter scale; the final catalog requires ˜q > 4. Redshifts were obtained by cross‑matching with DES, HSC, KiDS, and eROSITA optical/IR surveys, supplemented by photometric red‑sequence estimates where spectroscopic data were unavailable.

Masses were derived from the central Compton‑y parameter (˜y₀) using a calibrated Y–M relation anchored to recent weak‑lensing measurements, differing slightly from previous ACT releases. Completeness simulations show that the subsample with ˜q > 5 (the “Legacy” sample of 3 747 clusters over 10 317 deg²) is >90 % complete for M₅₀₀c > 5 × 10¹⁴ M⊙. The full catalog contains 10 040 confirmed clusters, including 1 180 at z > 1 and 124 at z > 1.5, and a total of 21 558 candidates (including unconfirmed objects).

The catalog is released publicly with extensive ancillary products: noise maps, sky masks, flagged regions, random catalogs, and the Nemo detection software, enabling reproducibility. Comparison with earlier ACT DR5, Planck, and SPT catalogs shows a 1.5‑fold increase in cluster numbers and a substantial boost in high‑z detections. The most massive object remains El Gordo; no other cluster in the sample violates ΛCDM predictions with Gaussian initial conditions, confirming the consistency of the SZ‑selected sample with the standard cosmological model. The authors discuss future work involving joint analyses with eROSITA and deeper weak‑lensing data to refine mass calibration and systematic uncertainties.