PyGEDM pre-computed maps of Galactic electron density models

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Authors: Danny C. Price
Cited by: 0

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