Galaxy surveys

  Cosmology

  Large Scale Structure

  Statistics

  Cosmic Microwave Background

   Constraining the distribution of galaxies and bias via higher order statistics

I have been studying higher order statistics
in galaxy catalogs, such as the Sloan Digital Sky Survey (SDSS).
Statistical properties of large scale structure are represented
primarily through the distribution of galaxies, but
the underlying dark matter, which appears to dominate the
matter content of the universe, might have an entirely different
distribution. This phenomenon, ``bias'', has central
role in modern cosmology. Its understanding potentially
constrains the nature and distribution of dark matter,
one of the most interesting issues of 21st century physics.
Yet, at present, it constitutes the weakest link in our theories of
structure formation. Higher order statistics
sheds new light on these phenomena, and new measurements
will translate into tight constraints on the nature and
distribution of the dark matter, on Gaussianity of the initial conditions,
and on the physics of galaxy formation.

Click herefor preliminary results on angular clustering in the SDSS,
and  here for the latest on higher order clustering in the SDSS.

  Analysis of large astronomical data sets

Istvan Szapudi has been developing a suite of new methods and
algorithms for spatial statistical
analyses of future large astronomical data bases, such as
galaxy catalogs (SDSS),  megapixel CMB maps (e.g., MAP and Planck).
Contemporary data analysis tools
are inadequate for future large data sets, even with the most powerful
supercomputers existing or projected. As an example,
standard analysis of megapixel
CMB maps from Planck would take a million years on hypothetical computers
equipped with TeraBytes of memory. The new analysis suite
created by Szapudi and collaborators, SpICE (Spatially Inhomogeneous
Correlation Estimator) brings an order of billion fold improvement,
enabling the analysis of MAP and Planck in less then 5 and 40 minutes,
respectively. In addition to megapixel CMB maps,
the novel methods developed in this research will
be immensely useful  for joint analysis of
future surveys across several wavelengths, as
envisioned in the planned National Virtual Observatory (NVO) framework.

For the latest on our fast CMB  code here.