The Fornax3D project: The environmental impact on gas metallicity gradients in Fornax cluster galaxies
M. A. Lara-Lopez, P. M. Galan-de Anta, M. Sarzi, E. Iodice, T. A., Davis, N. Zabel, E. M. Corsini, P. T. de Zeeuw, K. Fahrion, J., Falcon-Barroso, D. A. Gadotti, R. M. McDermid, F. Pinna, V. Rodriguez-Gomez,, G. van de Ven, L. Zhu, L. Coccato, M. Lyubenova, and I. Martin-Navarro

TL;DR
This study investigates how the environment in the Fornax galaxy cluster affects gas metallicity gradients, revealing environmental influences like ram pressure stripping and galaxy interactions through observations and simulations.
Contribution
It provides the first detailed analysis of gas metallicity gradients in Fornax cluster galaxies, combining MUSE observations with TNG50 simulations to identify environmental effects.
Findings
Fornax galaxies show slightly higher metallicities than control samples.
Most Fornax galaxies have flatter or more positive metallicity gradients.
Environmental factors like ram pressure stripping likely cause gradient flattening.
Abstract
The role played by environment in galaxy evolution is a current debate in astronomy. The degree to which environment can alter, re-shape, or drive galaxy evolution is a topic of discussion in both fronts, observations and simulations. This paper analyses the gas metallicity gradients for a sample of 10 Fornax cluster galaxies observed with MUSE as part of the Fornax3D project. Detailed maps of emission lines allowed a precise determination of gas metallicity and metallicity gradients. The integrated gas metallicity of our Fornax cluster galaxies show slightly higher metallicities (~0.045 dex) in comparison to a control sample. In addition, we find signs of a mass and metallicity segregation from the center to the outskirts of the cluster. By comparing our Fornax cluster metallicity gradients with a control sample we find a general median offset of ~0.04 dex/Re, with 8 of our…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
