Scaling Relations across Galaxy Classification Schemes: I. Star Formation Rate-Stellar Mass Plane of CALIFA Nearby Galaxies

Abstract

To gain deeper insights into galaxy evolution and the mechanisms driving transitions between different galaxy morphologies, we analyse the connection between star formation rate and stellar mass for 231 galaxies spanning Hubble types E1-Sdm from the Calar Alto Legacy Integral Field Spectroscopy Area survey using three complementary classification schemes. The Hubble classification provides structural information, the circular velocity curve classification$-$based on principal component analysis$-$ traces the total gravitational potential, and the Quenching classification$-$derived from H$_α$ equivalent width maps$-$indicates the spatial extent of quenched regions relative to star-forming areas. We find a clear separation of galaxy populations on the star formation rate-stellar mass plane. Late-type spirals with slow-rising circular velocity curves, represented by star-forming and quiescent-nuclear-ring galaxies, dominate the blue cloud. Early-type spirals with flat or round-peaked circular velocity curves belonging to centrally quiescent or mixed class populate the green valley, representing a transitional stage. Elliptical and lenticular galaxies with round- or sharp-peaked circular velocity curves from nearly retired or fully retired QSs reside on the red sequence. Furthermore, our results indicate that the morphological groups Sc-Scd, Sd-Sdm, and E1-E3 are characterized by a unique set of QSs and circular velocity curves, while galaxies with morphologies such as Sa-Sbc spread over multiple QSs and circular velocity curves. The distribution of the classification classes shows a tight link between galaxy structure, gravitational potential, and suppression of star-formation in the galaxies.

Figures (6)

• Figure 1: A compilation of individual SDSS DR7 (Abazajian2009) multi-color post stamp images of our sample of 231 galaxies, and arranged by Hubble type from elliptical (E1) to late-type spirals (Sdm).
• Figure 2: Sketches of two of the three classification schemes used in this study. Left: PCA--CVC classification Kalinova2017b, defining four galaxy classes with different CVC shapes (SR, FL, RP, and SP). Right: W$_\mathrm{H\alpha}$--quenching classification (Kalinova2021), distinguishing six classes based on characteristic patterns of ionised gas traced by W$_\mathrm{H\alpha}$ maps (SF, QnR, cQ, MX, nR, and fR).
• Figure 3: SFR$-M_\ast$ diagram of the studied sample across galaxy classification schemes. The dashed line represents the model of the star-forming MS by Elbaz2007, while the error bars -- the typical uncertainties of the $M_\ast$ and the SFR, adopted from CidFernandes2014 and Gonzalez-Delgado2017, respectively. Late-type galaxies follow the star-forming MS, while earlier types, with RP-CVCs and SP-CVCs, and advanced QSs occupy progressively lower SFRs. The panels together highlight the consistent link between galaxy structure, dynamics, and the suppression of star formation.
• Figure 4: Distance from the MS of the studied sample across different galaxy classification schemes. Normalised distributions of $\Delta$SFR $\equiv \log(\mathrm{SFR}) - \log(\mathrm{SFR}_{\mathrm{MS}})$ for local SDSS galaxies (grey) and for our sample, separated by morphology (top), CVC class (middle), and QS (bottom). Vertical dotted lines mark the green-valley region ($-1.2 < \Delta$SFR $< -0.6$) following Bluck2016. We use an arbitrary y-axis for our sample since it is far less numerous than the SDSS galaxy population.
• Figure 5: Scatter-grid plot of galaxies by morphology and QS. Each cell shows individual galaxies as points, coloured by CVC class, with the grid layout allowing comparison of distributions across morphology–quenching combinations. A small random shift to the galaxy location is added artificially to avoid large overlaps between the points.