HR-pyPopStar II: high spectral resolution evolutionary synthesis models low metallicity expansion and the properties of the stellar populations of dwarf galaxies

TL;DR

HR-pyPopStar II delivers high-spectral-resolution SSPs at very low metallicities ($Z=0.0001$–0.0004) by integrating Mun05, PoWR, and PHOENIX libraries with Padova isochrones and four IMFs. The updated models reproduce solar-metallicity results with small differences in molecular bands, while enabling robust analyses of old, metal-poor populations through tests on M15 and MaNGA dwarfs. Applications to a high-S/N globular cluster spectrum and a MaNGA dwarf sample demonstrate comparable trends to literature in mass–metallicity and age–metallicity relations, with hints of two distinct stellar-population components. The work enhances age-metallicity disentanglement in low-metallicity systems and provides publicly available, high-resolution SSPs for extragalactic studies and JWST-era metal-poor targets.

Abstract

Low metallicity stellar populations are very abundant in the Universe, either as the remnants of the past history of the Milky Way or similar spiral galaxies, or the young low metallicity stellar populations that are being observed in the local dwarf galaxies or in the high-z objects with low metal content recently found with JWST. Our goal is to develop new high-spectral-resolution models tailored for low-metallicity environments and apply them to analyse stellar population data, particularly in cases where a significant portion of the stellar content exhibits low metallicity. Methods. We used the state-of-the-art stellar population synthesis code HR-pyPopStar with available stellar libraries to create a new set of models focused on low metallicity stellar populations. We have compared the new spectral energy distributions with the previous models of HR-pyPopStar for solar metallicity. Once we verified that the spectra, except for the oldest ages that show some differences in the molecular bands of the TiO and G band, are similar, we reanalysed the high resolution data from the globular cluster M 15 by finding a better estimate of its age and metallicity. Finally, we analysed a subsample of mostly star-forming dwarf galaxies from the MaNGA survey we found similar stellar mass-mean stellar metallicity weighted by light to other studies that studied star forming dwarf galaxies and slightly higher mean stellar metallicity than the other works that analysed all types of dwarf galaxies at the same time, but are within error bars.

Figures (17)

• Figure 1: Comparison of the coverage of the stellar libraries of C14, black squares, and PHOENIX, red triangles, for the low temperature stars, $T_{\rm eff}<4000 \,{\rm K}$. Blue points represent the isochrones for all ages and solar metallicity.
• Figure 2: SEDs obtained with this new version of the code HR-pyPopStar. We show a comparison among SEDs with a) different ages ($\tau$) for the same metallicity $Z = 0.02$ and CHA IMF; b) different metallicities for a given age log $\tau$ = 8.00 and CHA IMF; and c) different IMFs for a given age log $\tau$ = 8.00 and metallicity $Z = 0.02$.
• Figure 3: Comparison between the old version of HR-pyPopStar using the stellar library of C14 (MI21), in blue line, and the present models using MUN05 +PHOENIX stellar library, in red line, for $Z=0.02$ and CHA IMF. The bottom part of every subfigure shows the residuals $\Delta L_{MI21-new}= \frac{L_{MI21}-L_{new}}{L_{MI21}}$.
• Figure 4: Evolution of magnitudes a) U, b) B, c) V, d) R, e) u, f) g, g) r, h) i, and i) z with age: comparison of results between MI21, blue, and this work, red, with residuals in the bottom panel for CHA IMF and $Z=0.02$.
• Figure 5: D4000 and Dn4000 break time evolution comparison for between MI21 in blue line and this work red line for $Z=0.02$.