PHANGS Sample: Multiwavelength Galaxy Data

• PHANGS sample is a carefully curated set of nearby star-forming galaxies selected for low inclination, proximity, high star formation, and robust molecular content.
• Using instruments like ALMA, HST, MUSE, AstroSat, and Spitzer, the project delivers high-resolution, homogeneous data from a few parsecs to kiloparsecs for detailed ISM and stellar analyses.
• The well-defined selection criteria and cross-phase analyses provide actionable insights into star formation efficiency, molecular cloud lifecycles, and local galaxy evolution.

The PHANGS sample refers to a set of nearby galaxies and their substructures systematically targeted by the “Physics at High Angular resolution in Nearby GalaxieS” (PHANGS) collaboration using a suite of matched, multi-wavelength observational campaigns (ALMA, HST, MUSE, AstroSat, Spitzer) optimized for high physical resolution and homogeneity across large portions of the $z=0$ star-forming main sequence. PHANGS defines foundational samples for cloud, cluster, and star formation regulation studies, providing well-calibrated demographic, spatial, and physical property catalogs for interstellar medium (ISM) and stellar populations on scales from a few parsecs (with HST) to kiloparsecs (with ALMA and MUSE). The precise definition of the “PHANGS sample” varies by dataset, but the core design principles unify all branches: low inclination, proximity, high star formation, robust molecular content, and main-sequence disk morphology.

1. Hierarchical Structure of the PHANGS Samples

The PHANGS project targets samples tailored to the capabilities and goals of each facility. The organizational hierarchy is:

• Parent sample: 118 galaxies, spanning D ≈ 0.8–21 Mpc, selected for overall star-forming disk character and ALMA, HST, or ancillary survey visibility (Anand et al., 2020).
• PHANGS–ALMA: 90 galaxies, with a “main” sample of 75 restricted by $i < 75^\circ$, $d \lesssim 17$ Mpc, $\log_{10} M_\star/\mathrm{M}_\odot > 9.75$, and high specific SFR (Leroy et al., 2021).
• PHANGS–HST: 38 spiral galaxies, $D \lesssim 20$ Mpc, $i < 60^\circ$, moderate–high SFR, observed in 5 UV-optical bands for resolved stellar clusters and associations (Larson et al., 2022).
• PHANGS–MUSE: ∼19 galaxies, optimized for IFU mapping of nebular lines, stellar population synthesis, and ISM diagnostics at ∼100 pc scales; matched to ALMA coverage for molecular gas context (Pessa et al., 2023, Brazzini et al., 30 Sep 2024, Barnes et al., 13 Oct 2025).
• PHANGS–AstroSat: 31 galaxies imaged in FUV/NUV, with D < 22 Mpc, selected from the ALMA parent sample to optimize UVIT visibility and coverage (Hassani et al., 2023).
• Multiwavelength enriched subsamples: Subsets with overlapping ALMA, HST, and MUSE footprints for cross-phase and cross-scale analyses (e.g., GMC–cluster pairing, nebula–association mapping) (Turner et al., 2022, Barnes et al., 13 Oct 2025).

Sample boundaries and selection are always explicitly stated so that derived demographic/statistical inferences are rigorously controlled for completeness and biases.

2. Galaxy-Level Selection Criteria and Demographics

PHANGS samples galaxies to maximize the spatial resolving power for critical substructure (GMCs, HII regions, clusters) while ensuring robust representation of global galaxy properties. The main selection criteria for the core samples are:

• Distance: $D \lesssim 17$–22 Mpc (facility-dependent), yielding ∼50–150 pc at 1″.
• Inclination: $i < 60$–75°, minimizing projection/dust effects.
• Stellar mass: $\log_{10}M_\star/\mathrm{M}_\odot > 9.75$; main-sequence and massive star-forming spirals (Sa–Sd), with a few S0 extensions (Leroy et al., 2021, Querejeta et al., 2021).
• Star formation activity: $sSFR > 10^{-11}$ yr⁻¹ prevents inclusion of quenched early-type disks.
• Coverage: Preference for uniform, deep mapping of disks to $R_{25}$ or beyond; mosaics are constructed to encompass CO emission and the main star formation zone.
• Environment: Includes both field and group galaxies; environmental context (e.g., presence of bars, central AGN, rings) is a critical secondary axis.

A summary of physical properties for the representative ALMA sample:

Property	Median	16–84th percentile
Distance (Mpc)	14	5.0–17
log($M_\star$/M$_\odot$)	10.35	9.25–11.25
log(SFR/M$_\odot$ yr⁻¹)	0.15	–0.8–1.2
Inclination (deg)	31	0–75

(Querejeta et al., 2021, Leroy et al., 2021)

3. Substructure and Environmental Classification

PHANGS samples are designed to resolve and catalogue ISM and stellar substructures:

• Molecular clouds (GMCs): Identified in ALMA CO(2–1) at 1″ (∼100 pc median), using algorithms such as CPROPS (Turner et al., 2022).
• Star clusters and associations: HST imaging at 0.05″ (∼2–8 pc), with watershed and neural network approaches for cluster, association, and hierarchical structure identification in 38 galaxies (Larson et al., 2022, Maschmann et al., 7 Mar 2024).
• HII regions and nebulae: From MUSE spectroscopy and HST H$\alpha$ imaging (down to 10 pc physical PSF), robustly separated into star-forming, planetary nebula, and SNR classes. Sizes, densities, and complexity scores are measured (Barnes et al., 13 Oct 2025, Santoro et al., 2021).
• Morpho-kinematic environments: Using near-IR and optical imaging to define centres, bars, spiral arms, interarms, and disks (“morphological masks”), which are the basis for environmental trends (gas content, depletion time, clustering) (Querejeta et al., 2021).

These structural catalogues link star formation outcomes (cluster populations, HII region sizes) to ISM context, enabling studies of feedback and efficiency as a function of local conditions.

4. Measurements, Completeness, and Selection Effects

Measurement strategies and completeness assessments underpin PHANGS’s ability to yield reliable demographic statistics:

• CO mapping: ALMA cubes (12m+7m+TP) typically reach surface-brightness sensitivity $\Sigma_\mathrm{mol} < 2$ M$_\odot$ pc⁻² in 5 km s$^{-1}$ bins (Leroy et al., 2021); completeness scales as $$M_\mathrm{min} \sim 7 \times 10^4 (D/10\,\mathrm{Mpc})^2$$ M$_\odot$ for GMCs (Zakardjian et al., 2023).
• Star clusters/associations: HST detection at $M_V \leq -2.8$ (D=10 Mpc) or $M_V \leq -4.2$ (D=18 Mpc), completeness varies with crowding and local surface brightness; neural network classification boosts sample size beyond human-inspected cluster catalogs (Maschmann et al., 7 Mar 2024).
• HII regions: MUSE and HST H$\alpha$ imaging reaches $$\sigma_\mathrm{final,10pc} \sim 6.25 \times 10^{-16}$$ erg s$^{-1}$ cm$^{-2}$ arcsec$^{-2}$, enabling measurement down to sub-parsec scales after homogenization (Barnes et al., 13 Oct 2025).
• Distance scale: Uniform distances (TRGB, Cepheid, SBF) are critical for size and luminosity normalization; the PHANGS compilation specifies hierarchy and uncertainty per object (Anand et al., 2020).
• Bias control: Completeness and selection biases (e.g., in distance, SFR) are explicitly modeled; e.g., survey depth, inclination limits, morphology cuts, and overlap of multiwavelength footprints.

5. Cross-Phase Analysis, Environmental Trends, and Scientific Impact

PHANGS samples serve as the basis for cross-phase and environmental analyses:

• Star formation efficiency and scaling relations: The molecular Kennicutt–Schmidt relation, $\Sigma_\mathrm{SFR} = A\,\Sigma_\mathrm{mol}^N$, holds near-unity slope across all environments, but environmental contrasts exist: bars and arms accumulate gas and star formation but only subtly affect depletion times (Querejeta et al., 2021).
• ISM–cluster coupling and feedback timescales: Multiwavelength matching yields constraints on cloud association lifetimes (feedback clears clusters from GMCs after 4–6 Myr) and the dissolution of hierarchical clustering over tens of Myr (Turner et al., 2022).
• Resolved metallicity and abundance gradients: MUSE/ALMA samples reveal shallow, universal negative oxygen gradients (mean $\sim -0.02$ dex $R_e^{-1}$), with mixing and breaks associated with bars or rings (Brazzini et al., 30 Sep 2024).
• ISM structure and clumping: UV–CO imaging shows bars and spiral arms as the loci of strongest emission clumping; Gini coefficients and clumping statistics track environment-dependent gas structuring (Hassani et al., 2023).
• Stellar population gradients and assembly histories: MUSE-derived gradients firmly establish inside-out disk formation, bar-driven mixing, and relationships between kinematics and assembly timescales at $\sim$100 pc resolution (Pessa et al., 2023).
• Dynamical resonances and secular evolution: Bar corotation and Lindblad resonance catalogues are provided for 74 galaxies, allowing spatial mapping of gas flows and morphological features versus dynamical theory (Ruiz-García et al., 17 Oct 2024).

6. Role in Multi-Survey Synergy and the Broader Context

PHANGS was designed as a platform for multiwavelength, multi-phase synergy:

• Uniform analysis across ISM, stars, and star formation tracers: Matched spatial coverage and resolution permit direct tests of ISM lifecycle, star formation triggering, feedback impact, and secular evolution.
• Public catalogues and machine-readable data: All core sample products (clouds, clusters, HII regions, metallicity, morphologies, kinematics) are released for community analysis and cross-comparison (Barnes et al., 13 Oct 2025).
• Benchmark for future extragalactic surveys: PHANGS methodology sets a precedent for sample selection, environmental dissection, and bias-aware population synthesis for ALMA, JWST, and new IFU surveys.
• Representative baseline for local star-forming disk physics: The statistical scale and homogeneity of PHANGS renders it the reference sample for ISM, star formation, and evolution studies of $z=0$ disks.

The PHANGS sample framework, with its precisely characterized, multi-phase, and environment-tagged galaxy set, underpins most contemporary extragalactic studies seeking demographic, spatial, and evolutionary trends in the lifecycle of molecular clouds, star clusters, and nebulae.