We present PHANGS–ALMA, the first survey to map CO J = 2 → 1 line emission at ∼1″ ∼100 pc spatial resolution from a representative sample of 90 nearby (d ≲ 20 Mpc) galaxies that lie on or near the z = 0 “main sequence” of star-forming galaxies. CO line emission traces the bulk distribution of molecular gas, which is the cold, star-forming phase of the interstellar medium. At the resolution achieved by PHANGS–ALMA, each beam reaches the size of a typical individual giant molecular cloud, so that these data can be used to measure the demographics, life cycle, and physical state of molecular clouds across the population of galaxies where the majority of stars form at z = 0. This paper describes the scientific motivation and background for the survey, sample selection, global properties of the targets, Atacama Large Millimeter/submillimeter Array (ALMA) observations, and characteristics of the delivered data and derived data products. As the ALMA sample serves as the parent sample for parallel surveys with MUSE on the Very Large Telescope, the Hubble Space Telescope, AstroSat, the Very Large Array, and other facilities, we include a detailed discussion of the sample selection. We detail the estimation of galaxy mass, size, star formation rate, CO luminosity, and other properties, compare estimates using different systems and provide best-estimate integrated measurements for each target. We also report the design and execution of the ALMA observations, which combine a Cycle 5 Large Program, a series of smaller programs, and archival observations. Finally, we present the first 1″ resolution atlas of CO emission from nearby galaxies and describe the properties and contents of the first PHANGS–ALMA public data release.

We measure the velocity dispersion, σ, and surface density, Σ, of the molecular gas in nearby galaxies from CO spectral line cubes with spatial resolution 45–120 pc, matched to the size of individual giant molecular clouds. Combining 11 galaxies from the PHANGS-ALMA survey with four targets from the literature, we characterize ∼30,000 independent sightlines where CO is detected at good significance. Σ and σ show a strong positive correlation, with the best-fit power-law slope close to the expected value for resolved, self-gravitating clouds. This indicates only a weak variation in the virial parameter α _vir ∝ σ ²/Σ, which is ∼1.5–3.0 for most galaxies. We do, however, observe enormous variation in the internal turbulent pressure P _turb ∝ Σσ ², which spans ∼5 dex across our sample. We find Σ, σ, and P _turb to be systematically larger in more massive galaxies. The same quantities appear enhanced in the central kiloparsec of strongly barred galaxies relative to their disks. Based on sensitive maps of M31 and M33, the slope of the σ–Σ relation flattens at Σ ≲ 10 M _⊙ pc⁻², leading to high σ for a given Σ and high apparent α _vir. This echoes results found in the Milky Way and likely originates from a combination of lower beam-filling factors and a stronger influence of local environment on the dynamical state of molecular gas in the low-density regime.

We describe the processing of the PHANGS–ALMA survey and present the PHANGS–ALMA pipeline, a public software package that processes calibrated interferometric and total power data into science-ready data products. PHANGS–ALMA is a large, high-resolution survey of CO(2–1) emission from nearby galaxies. The observations combine ALMA’s main 12 m array, the 7 m array, and total power observations, and use mosaics of dozens to hundreds of individual pointings. We describe the processing of the u − v data, imaging and deconvolution, linear mosaicking, combining interferometer and total power data, noise estimation, masking, data product creation, and quality assurance. Our pipeline has a general design and can also be applied to Very Large Array and ALMA observations of other spectral lines and continuum emission. We highlight our recipe for deconvolution of complex spectral line observations, which combines multiscale clean, single-scale clean, and automatic mask generation in a way that appears robust and effective. We also emphasize our two-track approach to masking and data product creation. We construct one set of “broadly masked” data products, which have high completeness but significant contamination by noise, and another set of “strictly masked” data products, which have high confidence but exclude faint, low signal-to-noise emission. Our quality assurance tests, supported by simulations, demonstrate that 12 m+7 m deconvolved data recover a total flux that is significantly closer to the total power flux than the 7 m deconvolved data alone. In the appendices, we measure the stability of the ALMA total power calibration in PHANGS–ALMA and test the performance of popular short-spacing correction algorithms.