Excitation of warm HD and H2

Version 1: Unrefereed data products. Published at the same time that the paper was submitted to ApJ in case the referee needs access to it. It will be replaced by Version 2, if necessary, after the paper has been reviewed. Data files behind "Excitation of warm HD and H2 and implications for the interstellar deuterium abundance" by David A. Neufeld (ApJ 2026, submitted) HD/H2 Zenodo data products -------------------------- h2_population_grids.fits: Non-LTE para-H2 and ortho-H2 rotational population grids. The population image extensions store log10(f_J/g_J) in NumPy order [temperature, density, level]. hd_population_grids.fits: Non-LTE HD rotational population grid. hd_lamda.dat: LAMDA-style HD molecular file with separate para-H2 and ortho-H2 de-excitation rates. High-J rates are extrapolated, as stated in the file. posterior_isobaric.csv and posterior_isochoric.csv: Least-squares best-fit values, posterior medians, and central 68% credible intervals for all fitted parameters and all observed positions for which line fluxes were measured by Francis et al. (2025, A&A, 694, A174) FITS population convention--------------------------The stored quantity is LOGPOP = log10(f_J/g_J), where f_J is the fractional population and g_J is the statistical weight. Recover f_J with f_J = g_J * 10**LOGPOP. H2 spin-isomer populations are normalized separately. FITS image axes are reversed relative to the documented NumPy array order. NaN values in LOGPOP preserve numerically unresolved, negligible high-level populations from the source calculations; NANCOUNT records their number. The python test script test_fitsread.py reads in the FITS files and creates numpy arrays containing all relevant quantities. It then plots the data for comparison with Neufeld (2026) Figure 1.