Galaxy formation and evolution

Abstract:

© 2016. The American Astronomical Society. All rights reserved.. The dynamical formation of stellar-mass black hole-black hole binaries has long been a promising source of gravitational waves for the Laser Interferometer Gravitational-Wave Observatory (LIGO). Mass segregation, gravitational focusing, and multibody dynamical interactions naturally increase the interaction rate between the most massive black holes in dense stellar systems, eventually leading them to merge. We find that dynamical interactions, particularly three-body binary formation, enhance the merger rate of black hole binaries with total mass M tot roughly as ∝Mtotβ, with β ≳ 4. We find that this relation holds mostly independently of the initial mass function, but the exact value depends on the degree of mass segregation. The detection rate of such massive black hole binaries is only further enhanced by LIGO's greater sensitivity to massive black hole binaries with M tot ≲ 80 . We find that for power-law BH mass functions dN/dM ∝ M -α with α ≤ 2, LIGO is most likely to detect black hole binaries with a mass twice that of the maximum initial black hole mass and a mass ratio near one. Repeated mergers of black holes inside the cluster result in about ∼5% of mergers being observed between two and three times the maximum initial black hole mass. Using these relations, one may be able to invert the observed distribution to the initial mass function with multiple detections of merging black hole binaries.

Abstract:

The next generation of cosmology experiments will be required to use photometric redshifts rather than spectroscopic redshifts. Obtaining accurate and well-characterized photometric redshift distributions is therefore critical for Euclid, the Large Synoptic Survey Telescope and the Square Kilometre Array. However, determining accurate variance predictions alongside single point estimates is crucial, as they can be used to optimize the sample of galaxies for the specific experiment (e.g. weak lensing, baryon acoustic oscillations, supernovae), trading off between completeness and reliability in the galaxy sample. The various sources of uncertainty in measurements of the photometry and redshifts put a lower bound on the accuracy that any model can hope to achieve. The intrinsic uncertainty associated with estimates is often non-uniform and input-dependent, commonly known in statistics as heteroscedastic noise. However, existing approaches are susceptible to outliers and do not take into account variance induced by non-uniform data density and in most cases require manual tuning of many parameters. In this paper, we present a Bayesian machine learning approach that jointly optimizes the model with respect to both the predictive mean and variance we refer to as Gaussian processes for photometric redshifts (GPz). The predictive variance of the model takes into account both the variance due to data density and photometric noise. Using the SDSS DR12 data, we show that our approach substantially outperforms other machine learning methods for photo-z estimation and their associated variance, such as tpz and annz2. We provide a matlab and python implementations that are available to download at https://github.com/OxfordML/GPz.

Abstract:

We present the stellar mass (M*) and Wide-Field Infrared Survey Explorer (WISE) absolute Band 1 magnitude (MW1) Tully-Fisher relations (TFRs) of subsets of galaxies from the CO Legacy Database for the Galex Arecibo SDSS Survey (COLD GASS). We examine the benefits and drawbacks of several commonly used fitting functions in the context of measuring CO(1-0) line widths (and thus rotation velocities), favouring the Gaussian Double Peak function. We find the MW1 and M* TFR, for a carefully selected sub-sample, to be MW1 = (-7.1 ± 0.6) [log(W50/sin i / km s^-1) - 23.83 ± 0.09 and log (M*/M⊙) = (3.3 ± 0.3) [log(W50/sin i / km s^-1) -2.58] + 10:51 ± 0.04, respectively, where W50 is the width of a galaxy's CO(1-0) integrated profile at 50% of its maximum and the inclination i is derived from the galaxy axial ratio measured on the SDSS r-band image. We find no evidence for any significant offset between the TFRs of COLD GASS galaxies and those of comparison samples of similar redshifts and morphologies. The slope of the COLD GASS M* TFR agrees with the relation of Pizagno et al. (2005). However, we measure a comparitively shallower slope for the COLD GASS MW1 TFR as compared to the relation of Tully and Pierce (2000). We attribute this to the fact that the COLD GASS sample comprises galaxies of various (late-type) morphologies. Nevertheless, our work provides a robust reference point with which to compare future CO TFR studies.

Abstract:

The dark matter (DM) haloes around spiral galaxies appear to conspire with their baryonic content: empirically, significant amounts of DM are inferred only below a universal characteristic acceleration scale. Moreover, the discrepancy between the baryonic and dynamical mass, which is usually interpreted as the presence of DM, follows a very tight mass discrepancy acceleration (MDA) relation. Its universality, and its tightness in spiral galaxies, poses a challenge for the DM interpretation and was used to argue in favour of MOdified Newtonian Dynamics (MOND). Here, we test whether or not this applies to early-type galaxies. We use the dynamical models of fast-rotator early-type galaxies by Cappellari et al. based on ATLAS 3D and SAGES Legacy Unifying Globulars and GalaxieS (SLUGGS) data, which was the first homogenous study of this kind, reaching ∼4Re, where DM begins to dominate the total mass budget. We find the early-type galaxies to follow an MDA relation similar to spiral galaxies, but systematically offset. Also, while the slopes of the mass density profiles inferred from galaxy dynamics show consistency with those expected from their stellar content assuming MOND, some profiles of individual galaxies show discrepancies.