The miniJPAS survey: Dissecting galaxy properties across environments with spatially resolved photometry

Abstract

The Javalambre-Physics of the Accelerating Universe Astrophysical Survey (J-PAS) is an ongoing survey mapping thousands of square degrees in the Northern Hemisphere using 56 narrow-band filters, delivering IFU-like photometric data well suited for studying galaxy properties and evolution. As a precursor, the miniJPAS survey observed a 1 deg$^2$ field with the same filter system, providing an ideal testbed for the study of spatially resolved galaxies. In this work, we investigate the resolved stellar population and emission-line properties of 51 miniJPAS galaxies, classified by spectral type (red or blue) and environment (group or field), and assess the role of environment in galaxy evolution. We use the Py2DJPAS pipeline to process the data, homogenise the images to a common PSF, define galactic regions, and extract photo-spectra. Radial profiles are analysed using elliptical annuli spaced by 0.7 R_EFF, combined with an inside-out segmentation to study star formation histories. Stellar population parameters are derived with the Bayesian SED-fitting code BaySeAGal, while artificial neural networks are used to estimate the equivalent widths of the H$α$, H$β$, [NII], and [OIII] emission lines. We find clear trends in a mass density-colour diagram: denser, redder regions are older, more metal-rich, and have lower specific star formation rates, while bluer, less dense regions show stronger emission lines and higher sSFRs. Red and blue galaxies are well separated in these relations, whereas environmental classification shows no clear distinction. Radial profiles support an inside-out formation scenario, with significant differences between red and blue galaxies but no strong environmental dependence. We suggest that the weak environmental effects may be due to the relatively low stellar masses of the galaxy groups in our sample.