Some statistical and computational challenges, and opportunities in astronomy

The data complexity and volume of astronomical findings have increased in recent decades due to major technological improvements in instrumentation and data collection methods. The contemporary astronomer is flooded with terabytes of raw data that produce enormous multidimensional catalogs of objects (stars, galaxies, quasars, etc.) numbering in the billions, with hundreds of measured numbers for each object. The astronomical community thus faces a key task: to enable efficient and objective scientific exploitation of enormous multifaceted data sets and the complex links between data and astrophysical theory. In recognition of this task, the National Virtual Observatory (NVO) initiative recently emerged to federate numerous large digital sky archives, and to develop tools to explore and understand these vast volumes of data. The effective use of such integrated massive data sets presents a variety of new challenging statistical and algorithmic problems that require methodological advances. An interdisciplinary team of statisticians, astronomers and computer scientists from The Pennsylvania State University, California Institute of Technology and Carnegie Mellon University is developing statistical methodology for the NVO. A brief glimpse into the Virtual Observatory and the work of the Penn State-led team is provided here

A new method for the determination of the growth rate from galaxy redshift surveys

Given a redshift survey of galaxies with measurements of apparent magnitudes, we present a novel method for measuring the growth rate $f(\Omega)$ of cosmological linear perturbations. We use the galaxy distribution within the survey to solve for the peculiar velocity field which depends in linear perturbation theory on $\beta=f(\Omega)/b$, where $b$ is the bias factor of the galaxy distribution. The recovered line-of-sight peculiar velocities are subtracted from the redshifts to derive the distances, which thus allows an estimate of the absolute magnitude of each galaxy. A constraint on $\beta$ is then found by minimizing the spread of the estimated magnitudes from their distribution function. We apply the method to the all sky $K = 11.25$ Two-MASS Redhsift Survey (2MRS) and derive $\beta=0.35\pm 0.1$ at $z\sim 0$, remarkably consistent with our previous estimate from the velocity-velocity comparison. The method could easily be applied to subvolumes extracted from the SDSS survey to derive the growth rate at $z \sim 0.1$. Further, it should also be applicable to ongoing and future spectroscopic redshift surveys to trace the evolution of $f(\Omega)$ to $z\sim1$. Constraints obtained from this method are entirely independent from those obtained from the two-dimensional distortion of $\xi(s)$ and provide an important check on $f(\Omega)$, as alternative gravity models predict observable differences.Comment: 9pages, 1figure Typos corrected. A slight change in the Discussion and Acknowledgemen

Massive Science with VO and Grids

There is a growing need for massive computational resources for the analysis of new astronomical datasets. To tackle this problem, we present here our first steps towards marrying two new and emerging technologies; the Virtual Observatory (e.g, AstroGrid) and the computational grid (e.g. TeraGrid, COSMOS etc.). We discuss the construction of VOTechBroker, which is a modular software tool designed to abstract the tasks of submission and management of a large number of computational jobs to a distributed computer system. The broker will also interact with the AstroGrid workflow and MySpace environments. We discuss our planned usages of the VOTechBroker in computing a huge number of n-point correlation functions from the SDSS data and massive model-fitting of millions of CMBfast models to WMAP data. We also discuss other applications including the determination of the XMM Cluster Survey selection function and the construction of new WMAP maps.Comment: Invited talk at ADASSXV conference published as ASP Conference Series, Vol. XXX, 2005 C. Gabriel, C. Arviset, D. Ponz and E. Solano, eds. 9 page