The Fornax Deep Survey with the VST

Context. Low surface brightness (LSB) dwarf galaxies in galaxy clusters are an interesting group of objects as their contribution to the luminosity function and evolutionary paths not yet clear. Increasing completeness our catalogs is crucial for understanding these galaxies, which have effective brightnesses below 23 mag arcsec −2 (in optical). Progress continuously being made via performance deep observations, but detection depth quantification can also be improved application novel approaches object detection. For example, Fornax Deep Survey (FDS) has revealed many faint that visually detected from images down a level 27 , whereas traditional methods, such using Source Extractor (SE), fail find them. Aims. In this work we use max-tree based algorithm (Max-Tree Objects, MTO) on FDS data order detect previously undetected LSB galaxies. After extending existing with sample, goal understand evolution dwarfs cluster. We study newly end function. Methods. test parameter extraction accuracy MTO simulated real images. then apply identify candidates. The identified fitted 2D Sérsic models GALFIT classified imaging artifacts, likely cluster members, or background morphological appearance, colors, structure. Results. With MTO, able increase earlier catalog (FDSDC) 0.5–1 deeper terms total magnitude brightness. Due increased measuring sizes objects, add small were excluded outer parts had been missed 265 new cluster, increases number known 821. Using whole population, show faint-end slope α = −1.38 ± 0.02. compare obtained different environments studied do any significant differences. On other hand, Fornax-like IllustrisTNG cosmological simulation shallower slopes than found observational data. several trends structure, morphology support idea higher center due tidal forces age dimming stellar populations. same result holds subgroup large so-called ultra-diffuse