The dataset related to "MaNGA DynPop. VII. A Unified Bulge–Disk–Halo Model for Explaining Diversity in Circular Velocity Curves of 6000 Spiral and Early-type Galaxies"

This data release presents the JAM-derived mass distributions in the MaNGA DynPop project (https://manga-dynpop.github.io). We provide the MGE (Multi-Gaussian Expansion) fits and a Python script to calculate various mass distributions (e.g. surface density maps, mass density profiles, kinematics maps). Please cite these two papers (https://ui.adsabs.harvard.edu/abs/2023MNRAS.522.6326Z/abstract, https://ui.adsabs.harvard.edu/abs/2025ApJS..280...55Z/abstract) if you use these mass distributions. Below are the descriptions of the files: JAM_MassDistribution.py, util_dm.py, util_mge.py: The Python scripts to calculate mass distributions. Demo.ipynb: A Jupyter notebook for how to calculate mass distributions. SDSSDR17_MaNGA_MGE.zip: The MGE coefficients in SDSS r-band. It must be unzipped before running the Python script. SDSSDR17_MaNGA_JAM.fits: The catalog that has been provided in MaNGA DynPop I . SDSSDR17_MaNGA_gNFW_cyl_Vcirc_ApJS.txt: The catalog that has been provided in MaNGA DynPop VII . SDSSDR17_MaNGA_JAM_Quality.pdf: (Optional) A PDF file containing images, the MGEs, observed and JAM-derived (mass-follows-light model) stellar kinematics (e.g. the root-mean-square velocity Vrms and line-of-sight velocity) for each galaxy. The quality (keyword: Qual) of JAM fits are based on the comparisons between the observed and modelled kinematics.