Matter properties ALFALFA galaxies with TNG100 code

This paper aims to investigate the galaxy-halo connection using a large sample of individual galaxies with HI-integrated spectra. We determined their dark matter content by applying a dynamical method based on HI line widths measured with the curve-of-growth technique, together with inclination corrections inferred from optical images. We built a sample of 2453 gas-rich, predominantly late-type galaxies spanning a stellar mass range of 10^8.7^M_{sun} to 10^11.4^M{sun} by matching them one-to-one with their counterparts from the ALFALFA survey and the TNG100 simulation, ensuring a direct match of stellar mass and HI radius. We generated mock images and mock HI-integrated spectra for TNG100 galaxies, and applied the same dynamical method to both ALFALFA and TNG100 mock galaxies to infer their dark matter masses. Across all stellar mass bins, ALFALFA galaxies exhibit lower median dark matter masses than the mock TNG100 simulation results. In each bin, this offset is driven by a tail of galaxies with comparatively low dark matter content, which becomes more prominent toward higher stellar masses. In the highest mass bin (M*>10^11^M{sun}), late-type ALFALFA galaxies show a median dark matter mass that is 23% lower than that of their counterparts in the TNG100 dark-matter-only simulation, with 32% of ALFALFA galaxies having M_DM(

Identifier
Source https://dc.g-vo.org/rr/q/lp/custom/CDS.VizieR/J/A+A/706/A64
Related Identifier https://cdsarc.cds.unistra.fr/viz-bin/cat/J/A+A/706/A64
Related Identifier https://vizier.cds.unistra.fr/viz-bin/VizieR-2?-source=J/A+A/706/A64
Metadata Access http://dc.g-vo.org/rr/q/pmh/pubreg.xml?verb=GetRecord&metadataPrefix=oai_b2find&identifier=ivo://CDS.VizieR/J/A+A/706/A64
Provenance
Creator Yang M.; Zhu L.; Yu N.; Lei Y.; Cai R.; Wang J.; Zheng Z.
Publisher CDS
Publication Year 2026
Rights https://cds.unistra.fr/vizier-org/licences_vizier.html
OpenAccess true
Contact CDS support team <cds-question(at)unistra.fr>
Representation
Resource Type Dataset; AstroObjects
Discipline Astrophysics and Astronomy; Cosmology; Galactic and extragalactic Astronomy; Interdisciplinary Astronomy; Interstellar medium; Natural Sciences; Observational Astronomy; Physics; Stellar Astronomy