We present the analysis of the full Mapping Nearby Galaxies at APO (MaNGA) DR17 sample to characterize its population of compact galaxies. We focus on galaxies that fill the stellar mass (M⋆) gap between compact elliptical galaxies (cEs; 8 ≲ log (M⋆/M⊙) ≲ 10) and compact massive galaxies (CMGs; 10 ≲ log (M⋆/M⊙)). We study their stellar populations and kinematics to reveal how their properties depend on stellar mass. We select compact galaxies in the MaNGA DR17 sample according to their effective radius (Re) and stellar mass. 37 galaxies fulfill our selection criteria in the bridging region between cEs and CMGs. We derive their kinematics and stellar population parameters from the stacked spectra at 1 Re using a full spectral fitting routine. We then classify the selected compact galaxies in three main groups based on their stellar population properties. One of the groups shows characteristics compatible with relic galaxies, i.e. galaxies that have remained mostly unchanged since their early formation epoch (z ∼ 2). Another group shows more extended and continuous star formation histories (SFHs). The third group shows a low star-forming rate at initial times, which increases at around ∼4 Gyr. We compare the derived properties of the selected galaxies with those of previously studied compact galaxies at different mass ranges. The selected galaxies successfully fill the mass gap between cEs and CMGs. Their properties are compatible with the assumption that the scaling relations of compact galaxies at different mass ranges are related, although galaxies in the first group are clear outliers in the fundamental plane, suggesting different formation mechanisms for this relic population.

Part of this work was performed during a Junta para la Ampliación de Estudios (JAE) fellowship JAEICU-21-ICE-3. A. Ferré-Mateu acknowledges support from grant CEX2019-000920-S and from RYC2021-031099-I and PID2021-123313NA-I00 of MCIN/AEI/10.13039/501100011033/ FEDER, UE, NextGenerationEU/PRT. H. Domínguez-Sánchez acknowledges support by the PID2020-115098RJ-I00 grant from MCIN/AEI/10.13039/501100011033 and from the Spanish Ministry of Science and Innovation and the European Union–NextGenerationEU through the Recovery and Resilience Facility project ICTS-MRR-2021-03-CEFCA.

With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2019-000920-S).

Peer reviewed