PyGEDM pre-computed maps of Galactic electron density models
Abstract
Pre-computed HDF5 data cubes for PyGEDM web app, updated to include NE2025. Data are all-sky maps of integrated electron density (i.e. dispersion measure, DM) as a function of distance in kiloparsecs. Dimension scales distance (kpc), DM (pc/cm3), galactic latitude and galactic longitude (deg). gl = np.linspace(-180, 180, 360*2+1) gb = np.linspace(-90, 90, 180*2+1) dist = np.array((0.1, 0.2, 0.5, 1, 2, 5, 8.5, 10, 20, 50)) Data in hickle file: 'dist': numpy array of distances in kpc (len 10), 'gl': galactic longitude in deg (len 721), 'gb': galactic latitude in deg (len 361), 'ne2001': NE2001 data, numpy array with shape (10, 361, 721), float32 dtype, 'ymw16': YMW16 data, numpy array with shape (10, 361, 721), float32 dtype, 'ne2025': NE2025 data, numpy array with shape (110, 361, 721), float32 dtype}
Fields of Study & Subjects
Astronomy and Astrophysical Research
Stellar
planetary
and galactic studies
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 26 February 2026
- Language
- EN
- Document type
- Dataset