Milky Way Imaging Scroll Painting (MWISP)

Updated 10 November 2025

MWISP is a comprehensive survey that maps the Milky Way's molecular gas using simultaneous CO isotopologue observations to capture cloud structure and kinematics.
Its innovative methodology, using cryogenically-cooled SIS receivers and digital FFT spectrometers, produces high-fidelity PPV cubes enabling precise analyses of filamentary and hierarchical substructures.
The survey's advanced data products and robust distance determination techniques facilitate refined mapping of Galactic structure and deeper insights into star formation and feedback processes.

The Milky Way Imaging Scroll Painting (MWISP) is an extensive, multi–line CO mapping survey of the northern Galactic plane conducted with the Purple Mountain Observatory 13.7 m telescope at Delingha, China. MWISP provides a high–fidelity, velocity–resolved census of molecular gas structure, kinematics, and substructure, using simultaneous observations of ^12CO, ^13CO, and C^18O J=1→0 transitions. The survey's uniform angular (∼52″–55″) and velocity (∼0.16–0.17 km s^–1) resolution, sub–Kelvin sensitivity, and large sky coverage (9.75° ≤ ℓ ≤ 230.25°, |b| ≤ 5.25°) deliver an unprecedented dataset for quantitative analysis of cloud and filament populations, hierarchical structure, and Galactic-scale phenomena.

1. Survey Design, Instrumentation, and Data Products

MWISP utilizes a cryogenically–cooled 3×3–beam SIS receiver, instantaneously sampling ^12CO(1–0), ^13CO(1–0), and C^18O(1–0) spectral lines. The typical beam size (HPBW) is ∼52″–55″, with 30″ spatial grid sampling and velocity channels of width ∼0.16–0.17 km s^–1, corresponding to a spectral resolution of ∼61 kHz. System temperatures are T_sys ≈ 250–350 K for single sideband operation; the main–beam efficiency is η_MB ≈ 0.5. The survey employs frequency–switching with rapid cycles for baseline correction, combined with digital FFT spectrometers (BW ≈ 1000 MHz per IF). Raw spectra are calibrated to the antenna temperature scale, followed by polynomial baseline subtraction and conversion to main–beam brightness temperature:

$T_{\rm MB} = T_A^* / \eta_{\rm MB}$

Final data cubes are constructed with 30″ × 30″ × 0.17 km s^–1 pixels using an optimal convolution kernel, ensuring precise alignment between isotopologue channels.

Coverage spans >200° in longitude; the Phase I footprint is 9.75° ≤ ℓ ≤ 230.25°, |b| ≤ 5.25°; Phase II is extending the latitude range. Per–channel rms noise after baseline removal is ≲0.5 K for ^12CO and ≲0.3 K for ^13CO, C^18O. Data products include calibrated position–position–velocity (PPV) cubes, integrated intensity maps, moment maps, catalogs, and ancillary diagnostics (peak temperature, velocity dispersion).

2. Molecular Cloud Census and Substructure Characterization

MWISP's full–sampling and sensitivity allow rigorous identification of molecular cloud populations using clustering algorithms such as DBSCAN (Density-Based Spatial Clustering of Applications with Noise) directly in PPV space (Yan et al., 2022). Standard DBSCAN parameters (ε=1 voxel, MinPts=4) and stringent post-selection filters (≥16 voxels, peak ≥5σ, ≥2×2 spatial pixels, ≥3 velocity channels) yield catalogs in which cloud number, boundaries, and substructure statistics respond strongly to angular resolution and sensitivity. MWISP data demonstrate power-law distributions in physical area and mass, e.g., $dN/dA \propto A^{-2.20}$ , $dN/dM \propto M^{-1.96}$ , robust against algorithmic variation (Yan et al., 2020).

Giant Molecular Clouds (GMCs) are resolved into aggregates of tens to hundreds of DBSCAN-identified sub-clouds, leading to a reinterpretation of GMCs as clusters of molecular clouds rather than monolithic entities. Completeness tests indicate MWISP recovers >80% of local-arm CO flux at fiducial cutoffs, while legacy surveys miss extended and faint components (Sun et al., 2021).

3. Filament and Hierarchical Structure Analysis

MWISP enables identification and analysis of filamentary structures. The DPConCFil algorithm suite (Jiang, 2 Dec 2024) includes a consistency-based method using positional and directional consistency of clumps and axes to delineate filaments in the PPV cube. Graph–based skeletonization extracts intensity ridges, while graph–based substructuring decomposes complex filaments into sub-units.

Statistical investigations using Hessian matrix and Rayleigh statistics (Soler et al., 2021) in smoothed MWISP cubes reveal that most ^12CO and ^13CO filaments display no global orientation preference; only localized regions show alignment parallel or perpendicular to the Galactic plane, decoupled from atomic (HI) filament morphologies. This indicates that molecular filament structure is shaped by local physics—stellar feedback, magnetic fields, spiral shocks—rather than inherited from atomic precursors.

Hierarchical decomposition (modified dendrograms) applied to MWISP ^13CO cubes reveals self-similar structure spectra ( $dN/dR \propto R^{-2.6}$ , $dN/dM \propto M^{-1.64}$ ) and scaling relations ( $\sigma_v \propto R^{0.55}$ , $M \propto R^{2.27}$ ) consistent across non-hierarchical and hierarchical identification schemes (Shen et al., 30 May 2024). Virial parameter analyses distinguish regions dominated by turbulence/external pressure (quiescent regions) from those where gravity dominates (star-forming cores), mapping the transition from unbound to bound structure as a function of physical scale.

4. Quantitative Physical Properties and Scaling Relations

MWISP cloud and clump catalogs provide a foundation for statistical tests of scaling relations. Large samples (e.g., 71,661 ^13CO clumps (Jiang et al., 2 Sep 2025)) exhibit universal power laws:

Mass–Radius: $M \propto R^{2.23}$
Size–Density: $n_{\rm H_2} \propto R^{-0.96}$
Virial–Radius: $\alpha_{\rm vir} \propto R^{-0.73}$
Linewidth–Size: $\sigma_v \propto R^{0.40}$
Linewidth–Mass: $\sigma_v \propto M^{0.17}$

A steeper mass–radius slope (γ>2) implies increasing surface density for larger clumps. The sub-virial σ_v–(R Σ) relation and lower α_vir values in maser-associated clumps indicate modified gas motion, stronger binding, and density structure in regions of active star formation. The measured mass spectrum is $dN/dM \propto M^{-1.83}$ (Sun et al., 2021), with most molecular mass residing in the largest clouds.

Column density PDFs (N-PDFs) are characterized for large samples: ∼72% of clouds are log-normal (turbulence-dominated), while ∼18% develop power-law high-density tails (indicative of self-gravitating, star-forming regions). N-PDF width scales as $\sigma_s \propto N_{H_2}^{0.44}$ , correlated with Sonic Mach number but independent of cloud mass (Ma et al., 2022).

5. Galactic Structure: Spiral Arms, Disk Thickness, Warp, and Flaring

MWISP data reveal spiral arm loci, molecular disk thickness, warp, and flaring as a function of Galactic radius. Arm tracing uses aggregated cloud positions in l–v–b, with robust assignments via kinematic distances, maser matches, and Bayesian PDF methods (Zhou et al., 20 Aug 2025). Analysis shows

Molecular disk thickness: FWHM ≈ 220 pc in the inner Galaxy, increasing, and correlated linearly with warp amplitude.
Outer arm structure: MWISP maps recover distant molecular clouds (e.g., 457 Outer arm clouds (Du et al., 2016)), yielding spiral arm pitch angle ψ ≈ 13.1°.
Inter–arm spurs and bridges are prominent, indicating a complex topology beyond simple arm/inter-arm models.

Disk vertical structure studies indicate scale heights, warping, and thickness from Gaussian fits to column-density slices (Du et al., 2016, Zhou et al., 20 Aug 2025). Mist curtains—large, kinematically cold, sheet-like structures—are detected close to the Sun, expanding the taxonomy of molecular structures.

6. Distance Determination and Statistical Census

Robust distance measurements use the background-eliminated extinction-parallax (BEEP) method and its enhancement, BEEP-II, tying MWISP CO on-cloud samples to Gaia DR2 and AV catalogs (Yan et al., 2019, Yan et al., 2021). BEEP-II utilizes a global circular parameter grid, piecewise integration, DBSCAN+k-means clustering, and MCMC refinement, achieving:

Reliable distances for 97.94% of clump samples; mean statistical uncertainty ∼7.3%
Capability to resolve distance ambiguities for large/complex clouds
Empirical calibration for local clouds: $D = 0.033\,V_{\rm LSR} + 0.18$ (Yan et al., 2020)

This strategy yields a thorough spatial catalog, enabling direct mapping of Galactic structure, analysis of spiral arm/interarm distributions, and refinement of the baryonic mass budget—the latter increased by ≥40% over pre-MWISP estimates (Sun et al., 2021).

7. Applications to Star Formation, Feedback, and Evolution

MWISP's multi-line strategy, high resolution, and sampling density support extensive studies of star formation and feedback. Dense gas tracers (C^18O, 1.1 mm dust) and clump catalogs clarify the link between excitation temperature, opacity, column density, and star-forming activity (Gong et al., 2016). Star-forming gas systematically exhibits higher temperature, opacity, and density.

Fragmentation analyses of filaments combine turbulent and gravitational models, demonstrating large-scale fragmentation controlled by turbulence and small-scale gravitational collapse triggering YSO formation. Star formation efficiency and rate in MWISP clouds exceed traditional Kennicutt-Schmidt predictions, directly connecting detailed molecular properties to Galactic star formation laws.

The exponential flux–intensity relation for molecular clouds, established in MWISP cubes, segments cloud structure statistics and outlines hierarchical structures (from envelopes to filaments to dense cores), acting as a silhouette operator. The nearly universal shape and segment flux fractions across thousands of clouds provide a powerful tool for cloud population and evolutionary studies (Yan et al., 13 May 2024).

MWISP establishes an unparalleled molecular-gas database for Milky Way studies, underpinning advances in hierarchical structure analysis, distance anchoring, filament and clump population statistics, mapping of spiral structure, and understanding star formation dynamics and feedback. The open availability of value-added catalogs and analysis suites (e.g., DPConCFil, FacetClumps) accelerate community-wide exploitation of these resources for the next generation of Galactic ISM research.