Projected 3pt Correlation Function in the Sloan Digital Sky Survey

Details Projected 3pt Correlation Function in the Sloan Digital Sky Survey Projected 3pt Correlation Function in the Sloan Digital Sky Survey

Dec 2006

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006aas...20918001m&link_type=abstract

2007 AAS/AAPT Joint Meeting, American Astronomical Society Meeting 209, #180.01; Bulletin of the American Astronomical Society,

Statistics

Computation

Scientific paper

We present measurements of the projected three-point correlation function (3PCF) from the Sloan Digital Sky Survey's (SDSS) main galaxy sample. The 3PCF provides statistical information on the non-Gaussianity of large scale structure (LSS). This is naively an N-cubed calculation, which makes the runtime intractable for large datasets (such as the SDSS). To address this, we have been developing a parallel framework that leverages a tree-based approach to aid in an efficient computation. Utilizing volume-limited samples constructed from the most recent data release (DR5 consisting of over 600,000 galaxies), we probe the scale and configuration dependence of the projected 3PCF. As a complement to bispectrum and redshift-space analyses, the projected 3PCF sidesteps redshift distortions in the SDSS data by integrating out the effect of peculiar velocities. With proper binning, measurements on both weakly and strongly non-linear scales are consistent with expectations. On large scales (weakly non-linear), the 3PCF configuration dependence exhibits the V-shape from filamentary structure and measurements converge between redshift-space and projected-space. On small scales, the U-shape is prevalent in redshift-space and (properly) absent in the projected 3PCF. Comparisons with mass evolution in Hubble Volume simulations (Virgo Consortium) are used to investigate the bias between galaxy and mass clustering. Because the 3PCF contains higher order information than a two point correlation function, both the linear and quadratic bias terms are constrained.

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