Galaxy formation and evolution

Abstract:

We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r=23.6 vs. r=22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314,000 galaxies. 140,000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars, and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314,000 galaxies. When measured against confident volunteer classifications, the networks are approximately 99% accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve.

Abstract:

We present a novel 2D flux density model for observed H i emission lines combined with a Bayesian stacking technique to measure the baryonic Tully-Fisher relation below the nominal detection threshold. We simulate a galaxy catalogue, which includes H i lines described with either Gaussian or busy function profiles, and H i data cubes with a range of noise and survey areas similar to the MeerKAT International Giga-Hertz Tiered Extragalactic Exploration (MIGHTEE) survey. With prior knowledge of redshifts, stellar masses, and inclinations of spiral galaxies, we find that our model can reconstruct the input baryonic Tully-Fisher parameters (slope and zero-point) most accurately in a relatively broad redshift range from the local Universe to z = 0.3 for all the considered levels of noise and survey areas and up to z = 0.55 for a nominal noise of 90 μJy/channel over 5 deg2. Our model can also determine the MHI - M∗ relation for spiral galaxies beyond the local Universe and account for the detailed shape of the H I emission line, which is crucial for understanding the dynamics of spiral galaxies. Thus, we have developed a Bayesian stacking technique for measuring the baryonic Tully-Fisher relation for galaxies at low stellar and/or H I masses and/or those at high redshift, where the direct detection of H I requires prohibitive exposure times.