PHANGS–ALMA Data Processing and Pipeline

Leroy, Adam K.; Hughes, Annie; Liu, Daizhong; Pety, J.; Rosolowsky, Erik; Saito, Toshiki; Schinnerer, E.; Schruba, Andreas; Usero, A.; Faesi, Christopher M.; Herrera, Cinthya N.; Chevance, Mélanie; Hygate, Alexander P. S.; Kepley, Amanda A.; Koch, Eric W.; Querejeta, Miguel; Sliwa, Kazimierz; Will, D.; Wilson, C. D.; Anand, Gagandeep S.; Barnes, Ashley T.; Belfiore, Francesco; Bešlić, Ivana; Bigiel, Frank; Blanc, Guillermo A.; Bolatto, Alberto D.; Boquien, M.; Cao, Yixian; Chandar, Rupali; Chastenet, Jérémy; Chiang, I-Da; Congiu, Enrico; Dale, Daniel A.; Deger, Sinan; Brok, Jakob S. den; Eibensteiner, Cosima; Emsellem, Éric; García-Rodríguez, Axel; Glover, Simon C. O.; Grasha, Kathryn; Groves, Brent; Henshaw, Jonathan D.; Jiménez-Donaire, María J.; Kim, Jaeyeon; Klessen, Ralf S.; Kreckel, Kathryn; Kruijssen, J. M. Diederik; Larson, Kirsten L.; Chen, Ness Mayker; McElroy, Rebecca; Meidt, Sharon E.; Mok, Angus; Pan, Hsi-An; Puschnig, Johannes; Razza, Alessandro; Sánchez‐Blázquez, P.; Sandström, Karin; Santoro, Francesco; Sardone, Amy; Scheuermann, Fabian; Sun, Jiayi; Thilker, David A.; Turner, Jordan A.; Úbeda, Leonardo; Utomo, Dyas; Watkins, Elizabeth J.; Williams, Thomas G.

doi:10.3847/1538-4365/abec80

Cited by 105 publications

(96 citation statements)

References 44 publications

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“…In one early set of observations targeting NGC 0628, also illustrated in Figure 19, we targeted CS(5-4) instead of C 18 O(2-1). The main practical difference is that this places the main CO(2−1) line in the lower sideband instead of the upper sideband, which affects the spectral variation of the noise (see Leroy et al 2021b).…”

Section: Observing Strategymentioning

confidence: 99%

“…The C43-2 main configuration recovers emission only from scales of 10″. Thus short-and zero-spacing information is important to accurately reconstruct the intensity distribution (e.g., see the case of M51; Koda et al 2009;Pety et al 2013; and see details for PHANGS-ALMA data processing in Leroy et al 2021b). Therefore, we observed all targets with both components of the Morita Atacama Compact Array (ACA), the compact array of 7 m dishes and the 12 m single-dish telescopes used for "total power.…”

Section: Target Angular Resolution and Inclusion Of Short-spacing Observationsmentioning

confidence: 99%

“…By including the CO(1−0) and CO(3−2) lines and relaxing the areal coverage requirements, many more archival observations of molecular line emission in nearby galaxies could be included. The PHANGS-ALMA data processing pipeline (Leroy et al 2021b) can straightforwardly handle these data, and we intend to return to this in future work.…”

Section: Notes On Archival Observationsmentioning

confidence: 99%

“…In Section 5, we describe the ALMA observations. A full description of our data processing pipeline is presented in a companion paper (Leroy et al 2021b), and we summarize our approach in Section 6. In Section 7, we describe the properties of the science-ready data products.…”

Section: Introductionmentioning

confidence: 99%

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PHANGS–ALMA: Arcsecond CO(2–1) Imaging of Nearby Star-forming Galaxies

Leroy

Schinnerer

Hughes

et al. 2021

ApJS

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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.

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Section: Observing Strategymentioning

confidence: 99%

Section: Target Angular Resolution and Inclusion Of Short-spacing Observationsmentioning

confidence: 99%

Section: Notes On Archival Observationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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PHANGS–ALMA: Arcsecond CO(2–1) Imaging of Nearby Star-forming Galaxies

Leroy

Schinnerer

Hughes

et al. 2021

ApJS

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222

262

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“…We thus developed a new automated approach to star cluster classifications using neural networks (Wei et al 2020) as part of the Physics at High Angular Resolution in Nearby Galaxies with the Hubble Space Telescope project (PHANGS-HST); PI: J. C. Lee, GO-15654) (J. C. Lee et al, in preparation). 1 PHANGS-HST is a Cycle 26 Treasury program obtaining 5-band UV-optical, F275W (NUV), F336W (U), F438W (B), F555W (V), F814W (I), WFC3 (or ACS in some cases with existing data) imaging for 38 nearby spiral galaxies with previous CO(2-1) observations from the PHANGS-ALMA large program (Leroy et al 2021). 2 An early attempt to classify clusters using quantitative morphological parameters is described in Whitmore et al (2014).…”

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confidence: 99%

Star cluster classification in the PHANGS–HST survey: Comparison between human and machine learning approaches

Whitmore

Lee

Chandar

et al. 2021

Monthly Notices of the Royal Astronomical Society

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When completed, the PHANGS–HST project will provide a census of roughly 50 000 compact star clusters and associations, as well as human morphological classifications for roughly 20 000 of those objects. These large numbers motivated the development of a more objective and repeatable method to help perform source classifications. In this paper, we consider the results for five PHANGS–HST galaxies (NGC 628, NGC 1433, NGC 1566, NGC 3351, NGC 3627) using classifications from two convolutional neural network architectures (RESNET and VGG) trained using deep transfer learning techniques. The results are compared to classifications performed by humans. The primary result is that the neural network classifications are comparable in quality to the human classifications with typical agreement around 70 to 80 per cent for Class 1 clusters (symmetric, centrally concentrated) and 40 to 70 per cent for Class 2 clusters (asymmetric, centrally concentrated). If Class 1 and 2 are considered together the agreement is 82 ± 3 per cent. Dependencies on magnitudes, crowding, and background surface brightness are examined. A detailed description of the criteria and methodology used for the human classifications is included along with an examination of systematic differences between PHANGS–HST and LEGUS. The distribution of data points in a colour–colour diagram is used as a ‘figure of merit’ to further test the relative performances of the different methods. The effects on science results (e.g. determinations of mass and age functions) of using different cluster classification methods are examined and found to be minimal.

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Detailed study of a rare hyperluminous rotating disk in an Einstein ring 10 billion years ago

Liu,

Förster Schreiber,

Harrington

et al. 2024

Nat Astron

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Hyperluminous infrared galaxies (HyLIRGs) are the rarest and most extreme starbursts and found only in the distant Universe (z ≳ 1). They have intrinsic infrared (IR) luminosities LIR ≥ 1013 L⊙ and are commonly found to be major mergers. Recently, the Planck All-Sky Survey to Analyze Gravitationally-lensed Extreme Starbursts project (PASSAGES) searched ~104 deg2 of the sky and found ~20 HyLIRGs. We describe a detailed study of PJ0116-24, the brightest (μLIR ≈ 2.6 × 1014 L⊙, magnified with μ ≈ 17) Einstein-ring HyLIRG in the southern sky, at z = 2.125, with observations from the near-IR integral-field spectrograph VLT/ERIS and the submillimetre interferometer ALMA. We detected Hα, Hβ, [N ii] and [S ii] lines and obtained an extreme Balmer decrement (Hα/Hβ ≈ 8.73 ± 1.14). We modelled the molecular-gas and ionized-gas kinematics with CO(3–2) and Hα data at ~100–300 pc and (sub)kiloparsec delensed scales, respectively, finding consistent regular rotation. We found PJ0116-24 to be highly rotationally supported (vrot/σ0, mol. gas ≈ 9.4) with a richer gaseous substructure than other known HyLIRGs. Our results imply that PJ0116-24 is an intrinsically massive (Mbaryon ≈ 1011.3 M⊙) and rare starbursty disk (star-formation rate, SFR = 1,490 M⊙ yr−1) probably undergoing secular evolution. This indicates that the maximal SFR (≳1,000 M⊙ yr−1) predicted by simulations could occur during a galaxy’s secular evolution, away from major mergers.

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PHANGS–ALMA Data Processing and Pipeline

Cited by 105 publications

References 44 publications

PHANGS–ALMA: Arcsecond CO(2–1) Imaging of Nearby Star-forming Galaxies

PHANGS–ALMA: Arcsecond CO(2–1) Imaging of Nearby Star-forming Galaxies

Star cluster classification in the PHANGS–HST survey: Comparison between human and machine learning approaches

Detailed study of a rare hyperluminous rotating disk in an Einstein ring 10 billion years ago

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