Beecroft Institute for Particle Astrophysics and Cosmology

Abstract:

Recent observations reveal galaxies in the early universe (2 < z < 6.4) with large reservoirs of molecular gas and extreme star formation rates. For a very large range of sources, a tight relationship exists between star formation rate and the luminosity of the HCN 7 = 1-0 spectral line, but sources at redshifts of z ∼ 2 and beyond do not follow this trend. The deficit in HCN is conventionally explained by an excess of infrared radiation due to active galactic nuclei (AGNs). We show in this Letter not only that the presence of AGNs cannot account for the excess of IR over molecular luminosity, but also that the observed abundance of HCN is in fact consistent with a population of stars forming from near-primordial gas. © 2006. The American Astronomical Society. All rights reserved.

Abstract:

There is evidence that Newton and Einstein's theories of gravity cannot explain the dynamics of a universe made up solely of baryons and radiation. To be able to understand the properties of galaxies, clusters of galaxies and the universe on the whole it has become commonplace to invoke the presence of dark matter. An alternative approach is to modify the gravitational field equations to accommodate observations. We propose a new class of gravitational theories in which we add a new degree of freedom, the Aether, in the form of a vector field that is coupled covariantly, but non-minimally, with the space-time metric. We explore the Newtonian and non-Newtonian limits, discuss the conditions for these theories to be consistent and explore their effect on cosmology.

Abstract:

The next generation of weak gravitational lensing surveys is capable of generating good measurements of cosmological parameters, provided that, amongst other requirements, adequate redshift information is available for the background galaxies that are measured. It is frequently assumed that photometric redshift techniques provide the means to achieve this. Here we compare Bayesian and frequentist approaches to photometric redshift estimation, particularly at faint magnitudes. We identify and discuss the biases that are inherent in the various methods, and describe an optimum Bayesian method for extracting redshift distributions from photometric data.