Cosmology

Abstract:

We describe the scientific motivations, the mission concept and the instrumentation of SPACE, a class-M mission proposed for concept study at the first call of the ESA Cosmic-Vision 2015-2025 planning cycle. SPACE aims to produce the largest three-dimensional evolutionary map of the Universe over the past 10 billion years by taking near-IR spectra and measuring redshifts for more than half a billion galaxies at 0∈<∈z∈<∈2 down to AB~23 over 3π sr of the sky. In addition, SPACE will also target a smaller sky field, performing a deep spectroscopic survey of millions of galaxies to AB~26 and at 2∈<∈z∈<∈10∈+. These goals are unreachable with ground-based observations due to the ≈500 times higher sky background (see e.g. Aldering, LBNL report number LBNL-51157, 2001). To achieve the main science objectives, SPACE will use a 1.5 m diameter Ritchey-Chretien telescope equipped with a set of arrays of Digital Micro-mirror Devices covering a total field of view of 0.4 deg2, and will perform large-multiplexing multi-object spectroscopy (e.g. ≈6000 targets per pointing) at a spectral resolution of R~400 as well as diffraction-limited imaging with continuous coverage from 0.8 to 1.8 μm. Owing to the depth, redshift range, volume coverage and quality of its spectra, SPACE will reveal with unique sensitivity most of the fundamental cosmological signatures, including the power spectrum of density fluctuations and its turnover. SPACE will also place high accuracy constraints on the dark energy equation of state parameter and its evolution by measuring the baryonic acoustic oscillations imprinted when matter and radiation decoupled, the distance-luminosity relation of cosmological supernovae, the evolution of the cosmic expansion rate, the growth rate of cosmic large-scale structure, and high-z galaxy clusters. The datasets from the SPACE mission will represent a long lasting legacy for the whole astronomical community whose data will be mined for many years to come. © 2008 Springer Science+Business Media B.V.

Abstract:

X-ray spectroscopy offers an opportunity to study the complex mixture of emitting and absorbing components in the circumnuclear regions of active galactic nuclei (AGN), and to learn about the accretion process that fuels AGN and the feedback of material to their host galaxies. We describe the spectral signatures that may be studied and review the X-ray spectra and spectral variability of active galaxies, concentrating on progress from recent Chandra, XMM-Newton and Suzaku data for local type 1 AGN. We describe the evidence for absorption covering a wide range of column densities, ionization and dynamics, and discuss the growing evidence for partial-covering absorption from data at energies ≳ 10 keV. Such absorption can also explain the observed X-ray spectral curvature and variability in AGN at lower energies and is likely an important factor in shaping the observed properties of this class of source. Consideration of self-consistent models for local AGN indicates that X-ray spectra likely comprise a combination of absorption and reflection effects from material originating within a few light days of the black hole as well as on larger scales. It is likely that AGN X-ray spectra may be strongly affected by the presence of disk-wind outflows that are expected in systems with high accretion rates, and we describe models that attempt to predict the effects of radiative transfer through such winds, and discuss the prospects for new data to test and address these ideas. © 2009 Springer-Verlag.

Abstract:

Although a fair amount of work has been devoted to growing Monte-Carlo merger trees which resemble those built from an N-body simulation, comparatively little effort has been invested in quantifying the caveats one necessarily encounters when one extracts trees directly from such a simulation. To somewhat revert the tide, this paper seeks to provide its reader with a comprehensive study of the problems one faces when following this route. The first step to building merger histories of dark matter haloes and their subhaloes is to identify these structures in each of the time outputs (snapshots) produced by the simulation. Even though we discuss a particular implementation of such an algorithm (called AdaptaHOP) in this paper, we believe that our results do not depend on the exact details of the implementation but extend to most if not all (sub)structure finders. We then highlight different ways to build merger histories from AdaptaHOP haloes and subhaloes, contrasting their various advantages and drawbacks. We find that the best approach to (sub)halo merging histories is through an analysis that goes back and forth between identification and tree building rather than one which conducts a straightforward sequential treatment of these two steps. This is rooted in the complexity of the merging trees which have to depict an inherently dynamical process from the partial temporal information contained in the collection of instantaneous snapshots available from the N-body simulation.