[en] We present to the astronomical community an algorithm for the detection of low surface brightness (LSB) galaxies in images, called MARSIAA (MARkovian Software for Image Analysis in Astronomy), which is based on multi-scale Markovian modeling. MARSIAA can be applied simultaneously to different bands. It segments an image into a user-defined number of classes, according to their surface brightness and surroundings—typically, one or two classes contain the LSB structures. We have developed an algorithm, called DetectLSB, which allows the efficient identification of LSB galaxies from among the candidate sources selected by MARSIAA. The application of the method to two and three bands simultaneously was tested on simulated images. Based on our tests, we are confident that we can detect LSB galaxies down to a central surface brightness level of only 1.5 times the standard deviation from the mean pixel value in the image background. To assess the robustness of our method, the method was applied to a set of 18 B- and I-band images (covering 1.3 deg² in total) of the Virgo Cluster to which Sabatini et al. previously applied a matched-filter dwarf LSB galaxy search algorithm. We have detected all 20 objects from the Sabatini et al. catalog which we could classify by eye as bona fide LSB galaxies. Our method has also detected four additional Virgo Cluster LSB galaxy candidates undetected by Sabatini et al. To further assess the completeness of the results of our method, both MARSIAA, SExtractor, and DetectLSB were applied to search for (1) mock Virgo LSB galaxies inserted into a set of deep Next Generation Virgo Survey (NGVS) gri-band subimages and (2) Virgo LSB galaxies identified by eye in a full set of NGVS square degree gri images. MARSIAA/DetectLSB recovered ∼20% more mock LSB galaxies and ∼40% more LSB galaxies identified by eye than SExtractor/DetectLSB. With a 90% fraction of false positives from an entirely unsupervised pipeline, a completeness of 90% is reached for sources with r_e > 3'' at a mean surface brightness level of μ_g = 27.7 mag arcsec^–2 and a central surface brightness of μ⁰_g = 26.7 mag arcsec^–2. About 10% of the false positives are artifacts, the rest being background galaxies. We have found our proposed Markovian LSB galaxy detection method to be complementary to the application of matched filters and an optimized use of SExtractor, and to have the following advantages: it is scale free, can be applied simultaneously to several bands, and is well adapted for crowded regions on the sky.

[en] A sample of very high resolution cosmological disk galaxy simulations is used to investigate the evolution of galaxy disk sizes back to redshift 1 within the ΛCDM cosmology. Artificial images in the rest-frame B band are generated, allowing for a measurement of disk scale lengths using surface brightness profiles as observations would, and avoiding any assumption that light must follow mass as previous models have assumed. We demonstrate that these simulated disks are an excellent match to the observed magnitude-size relation for both local disks and for disks at z = 1 in the magnitude/mass range of overlap. We disentangle the evolution seen in the population as a whole from the evolution of individual disk galaxies. In agreement with observations, our simulated disks undergo roughly 1.5 mag arcsec^-2 of surface brightness dimming since z = 1. We find evidence that evolution in the magnitude-size plane varies by mass, such that galaxies with M_* ≥ 10⁹ M_sun undergo more evolution in size than luminosity, while dwarf galaxies tend to evolve potentially more in luminosity. The disks grow in such a way as to stay on roughly the same stellar-mass-size relation with time. Finally, due to an evolving stellar-mass-star-formation-rate (SFR) relation, a galaxy at a given stellar mass (or size) at z = 1 will reside in a more massive halo and have a higher SFR, and thus a higher luminosity, than a counterpart of the same stellar mass at z = 0.