adsabs/AstroCLIMB huggingface dataset:
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: 3D UNet architecture. Each cube represents a 3D space-with-feature map, with the grid size and the number of feature channels indicated. The input and output cubes, each containing 5123 voxels and spanning 1564 h−1 Mpc, correspond to the redshift-space galaxy density field and the real-space dark-matter-density or velocity field, respectively. The encoder comprises eight convolutional layers that progressively downsample the input cube to a bottleneck representation, while the decoder uses eight transposed convolutional layers to upsample the bottleneck output to the target cube. The channel configuration (1 + 3) corresponds to the density field, δm, and the velocity components (vx, vy, vz), enabling simultaneous reconstruction of these quantities as an optional feature. The computational steps are represented by distinct symbols, as illustrated in the lower right corner. All convolutional layers utilize 4 × 4 × 4 filters with a stride of 2.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Comparison of P(k) (upper panel) and P(k) (lower panel) ratios. The black solid line and blue dashed line represent the autopower spectra of the true and reconstructed density fields, respectively, while the green dotted–dashed line represents their cross-power spectrum. For reference, the red dotted line shows the autopower spectrum of the redshift-space galaxy field. The bottom panel shows the ratio between the reconstructed and true power spectra, with the error bars indicating the ±σ variance across the five test samples. The black solid error bars are computed using Equation (9).
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Left: grid-to-grid density relationship between the reconstructed density field 1 + δrec and the true field 1 + δtrue, represented by the blue solid line. For comparison, the result for the galaxy density field is also plotted with the red dashed line. The three contours in each case represent thresholds encompassing 67%, 95%, and 99% of the grid cells. The dashed lines indicate the ideal one-to-one correspondence. Right: density distributions for galaxies (red dashed line), the reconstructed field (blue solid line), and the true field (black solid line). The error bars indicate the ±1σ variance among the five test samples.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Upper panels: grid-to-grid velocity relations for the x-, y-, and z-axis velocity components, as shown in the different columns. The blue solid line corresponds to the results from the entire survey region, while the red dashed lines represent the results for the center survey region, defined as a sub-box within 391.0 h−1 Mpc < x, y, z < 1173.0 h−1 Mpc. The contours represent 67%, 95%, and 99% of the grid cells, with the best-fitting linear regressions shown as dashed lines. The slope of the best-fitting relation and the scatter are also indicated in each panel. Lower panels: probability distributions of the velocity differences, vrec − vtrue.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Comparison between the true and reconstructed dark matter velocity fields in a slice of dimensions 1564 × 1564 × 3.05 h−1 Mpc. The left panel shows the true velocity field ﹩{{\boldsymbol{v}}}_{{\rm{true}}}﹩, directly extracted from the original simulation, while the middle panel presents the UNet-reconstructed field ﹩{{\boldsymbol{v}}}_{{\rm{rec}}}﹩. The right panel shows the residuals, ﹩{{\boldsymbol{v}}}_{{\rm{rec}}}-{{\boldsymbol{v}}}_{{\rm{true}}}﹩. In all panels, the arrows represent the velocity vectors, with their lengths proportional to the vector magnitudes. The underlying density field is also presented.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Comparison of the projected density field distributions in a slice of 1564 × 1564 × 9.16 h−1 Mpc. The different panels correspond to the redshift-space galaxy distribution (input), the true dark-matter-density field δtrue (target), the UNet-reconstructed density field δrec (output), and the difference between δrec and δtrue, as labeled at the top of each panel.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: The same as Figure 8 but comparing the densities in the low-redshift (orange) and high-redshift (blue) regions.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: The ratios Rℓ(k) for the quadrupole (blue solid) and hexadecapole (orange dashed) power spectra.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Comparison of the reconstruction performance between the separately trained models (blue lines) and the unified model (orange lines). As indicated in the panel titles, each subplot corresponds to one of the following diagnostic metrics: (1) the autopower spectrum of the dark matter field; (2) the cross-power spectrum between the reconstructed and true dark matter fields; (3) the momentum field power spectrum; (4) the velocity magnitude power spectrum; (5) the velocity divergence power spectrum; and (6) the vorticity power spectrum.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Normalized confusion matrix. Each row corresponds to a predicted class derived from the UNet-reconstructed dark-matter-density field, while each column corresponds to the true class based on the original simulated density field. The matrix entries represent classification probabilities, obtained by normalizing the values within each column such that the total for each true class sums to 1.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Ratios of the auto- (left panel) and cross-power (right panel) spectra between the reconstructed and true density fields, illustrating the impact of the FA effect. The blue lines show results without the FA effect and the red lines include the FA effect. The green lines represent a simple correction using nearest-neighbor galaxies.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Comparison of the velocity field power spectrum. From left to right, the panels correspond to the velocity magnitude, divergence, and the vorticity, respectively. In each panel, the black solid and blue dashed lines represent the power spectra of the true and reconstructed velocity fields, respectively. The green dotted–dashed line shows the cross-correlation power spectrum for the velocity magnitude between the true and reconstructed fields.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Comparison of the classification of the LSS between the true density field (left panel) and the UNet-reconstructed density field (right panel) in a slice of 1564 × 1564 × 3.05 h−1 Mpc. The yellow, yellow–green, green, and black regions show grid cells located at structures classified as clusters, filaments, sheets, and voids, respectively.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Eigenvalues of the reconstructed tidal tensor vs. those obtained from the true mass density field. The contours for each result encompass 95% and 99% of the grid cells.
Paper: DarkAI: Reconstructing the Density, Velocity, and Tidal Fields of Dark Matter from a DESI-like Bright Galaxy Sample
Authors: Feng Shi, Zitong Wang, Xiaohu Yang, Yizhou Gu, Chengliang Wei, Ming Li, Jiaxin Han, Zhejie Ding, Huiyuan Wang, Youcai Zhang, Wensheng Hong, Yirong Wang, Xiao-dong Li
Figure caption: Completeness map of the DESI survey footprint simulated using the four-pass observation strategy.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: The overall structure of the data-augmented hybrid WDCNN+LSTM model.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: Samples of the generated spectra.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: Structure of the LSTM cell.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: The spectrum and characteristic emission lines of LAMOST J101509.39-030832.6, which is to be confirmed as a WN-type star.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: The spectrum and characteristic emission lines of LAMOST J004147.23+410647.4.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: The spectrum and characteristic emission lines of LAMOST J194615.78+281620.7.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: The spectrum and characteristic emission lines of LAMOST J013237.67+304005.4.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: The structure of the WDCNN+LSTM classification model.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: Confusion matrix of the WDCNN+LSTM model for five-class classification.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: Comparative experimental result of the F1 score.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: Comparative experimental result of precision.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: Comparative experimental result of recall.
Paper: Classification of Wolf–Rayet Stars from LAMOST DR10
Authors: Jirui Chang, Wenyu Wang, Meixia Qu, Kun Su, Liangping Tu, Chenyang Lv, Bin Jiang, Yanxia Zhang
Figure caption: Spectrum comparison between a newly identified WR star (LAMOST J101509.39-030832.6) and the PoWR model template.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Schematic diagram illustrating the equivalent global detection scheme. (a) The SRs extracted from the original data (see Figure 1 of Y. Jiang et al. 2025) by FacetClumps. Curves of different colors represent the boundaries of different SRs. (b) The reconstructed SR data cube, corresponding to the red contours in (a). The asterisks denote the centers of the clumps, and the direction of the red straight lines indicates the orientation of the clumps at the untouched edges. Contours in different colors represent the boundaries of the clumps. To avoid confusion, only a subset of the clump boundaries is shown. (c) The reconstructed SR data cube, corresponding to the blue contours in (a). (d) Detection results’ storage data cube. Transfer the detection masks from (b) and (c) to a storage data cube of the same size as the original data. The inset view shows two clumps in detail, and the black circle in the bottom-left corner marks the spatial resolution of MWISP.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Example of automatic HISA identification for the source G18.107+0.409+22.913 (filament Fil 7 from Y. Jiang et al. 2025). Left panel: the black curve shows the signal-point H I spectrum of the target source from the VGPS (J. M. Stil et al. 2006) survey, with the orange vertical line indicating the velocity of the source. Right panel: this is a zoomed-in view of the left panel. Red points mark the local maxima of the H I profile, while blue points mark minima. The velocity range between adjacent extrema is divided into three segments: the red segment (near maximum) corresponds to the far kinematic distance solution, the blue segment (near minimum) corresponds to the near solution, and the green intermediate segment denotes ambiguous cases. The target’s systemic velocity (orange line) falls within the blue segment. The velocity difference between the target and the nearest minimum (1.182 km s−1) is smaller than the tolerance threshold (3 km s−1), leading to its classification as near kinematic distance at this spectrum.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Distribution of clumps across the Galactic longitude–latitude plane. Box plots illustrate the statistical distribution of Galactic latitude within discrete longitude intervals. Each box displays the interquartile range (IQR), with upper and lower boundaries marking the third and first quartiles, respectively, and the horizontal line indicating the median. The colored dashed–dotted lines represent median values for specific populations: red for positive Galactic latitudes (GLat > 0), blue for negative latitudes (GLat < 0), and black for the overall sample. Whiskers extend to the most extreme data points within 1.5 × IQR, revealing the dispersion across different Galactic longitudes. The orange line (right axis) quantifies the source count within each longitude bin.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Distance comparison of paired ATLASGAL and MWISP clumps. Black crosses mark MWISP clumps whose distance classification is based on maser associations, while blue crosses mark MWISP clumps that utilize maser distance measurements. The density distribution of matched clumps is estimated via KDE, where the color scale represents the relative probability density of clump occurrences. The lime contour outlines the region where KDE values exceed 90% of the distribution. Within this contour, the lime dotted line represents the fitted linear relationship to the clump distance pairs, with a slope of 1.04​​​​ ± 0.009. The red dashed line represents the y = x reference line.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Distribution of all clumps in the Galactic longitude–latitude and Galactic longitude–velocity planes. Different colored dashed lines illustrate various spiral arms from the model by M. J. Reid et al. (2019), with their names labeled.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Flow chart showing the KDA solution procedure adopted for the MWISP SRs in the FGQ.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: The coverage of H I data from different surveys utilized in the automatic HISA method. The priority order of H I data is arranged in the sequence of GALFA, VGPS, CGPS, SGPS, and HI4PI. Asterisks denote the positions of SRs.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Scaling relations between physical parameters of MWISP. Panels show (a) M–Req, where light coral dotted lines indicate constant Σ = 1, 10, 40, 100, 1000 M⊙ pc−2 and lime dotted lines indicate constant n(H2) = 10, 100, 1000, 10,000 cm−3; (b) n(H2)–Req; (c) αvir–Req; (d) σv–Req; (e) σv–M; (f) σv–ReqΣ; (g) N(13CO)–Req; (h) αvir–N(13CO); and (i) σv–N(13CO). The distributions are shown for two subsets: MWISP complete clumps (gray points with cyan contours) and MWISP CMDs. Among the CMD subset, CMD-C, indicated by colored points with blue contours, represents clumps in the close vicinity of masers, while CMD-H, marked by red contours, represents clumps that host masers. For each relation, the best-fit power-law index and corresponding P are indicated in the legend.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Scaling relations between physical parameters of different surveys. Panels show (a) M–Req, (b) n(H2)–Req, (c) αvir–Req, (d) σv–Req, (e) σv–M, and (f) σv–ReqΣ. The color scale represents the KDE of MWISP clumps. Colored dashed lines indicate power-law fits to the main distributions outlined by corresponding contours, with derived power-law indices (α0.9 ± uncertainty) and P labeled for each survey.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Relationships between distance-dependent parameters and heliocentric distance. Panels show (a) M − d, (b) Req − d, (c) αvir − d, and (d) n(H2) − d. Scatter points from the MWISP project are color coded according to their KDE values, as indicated by the color bar, reflecting the local data density. MWISP S1 represents a subset of the MWISP survey that covers a similar Galactic sector to CHIMPS. Contour lines, labeled for MWISP (cyan), MWISP S1 (pink), CHIMPS (lime green), and SEDIGISM (orange), highlight regions with KDE values exceeding 90%. The red lines represent the reference lines showing the theoretical parameter–distance relationships. For each survey’s high-density region, α0.9 denotes the fitted power-law slope of the relationship, presented alongside its uncertainty and P.
Paper: Investigations of MWISP Clumps: 13CO Clump Source Catalog and Physical Properties
Authors: Yu Jiang, Qing-Zeng Yan, Ji Yang, Sheng Zheng, Xuepeng Chen, Yang Su, Zhibo Jiang, Zhiwei Chen, Xin Zhou, Yao Huang, Xiaoyu Luo, Haoran Feng, De-Jian Liu
Figure caption: Face-on number density distribution map of clumps in the Galactic plane. The coordinate system centers on the Galactic center (red star) with the Sun positioned at (0, 8.15) kpc (yellow circle). The red dashed–dotted circle represents the 3 kpc ring around the Galactic center, while the blue dashed–dotted circle represents the solar circle. The number density distribution is calculated using KDE, where the color scale represents the density of clumps, with higher-density regions depicted in greater estimated values. Gray dashed lines show Galactic longitude lines (10° intervals). Axes are centered at the Galactic center, with the negative y-axis oriented toward l = 0° and the positive x-axis toward l = 90°. The colored dashed lines depict the spiral arms, with colors matching those in the bottom panel of Figure 2, based on the model by M. J. Reid et al. (2019).