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Title: BINARY QUASARS IN THE SLOAN DIGITAL SKY SURVEY: EVIDENCE FOR EXCESS CLUSTERING ON SMALL SCALES

Journal Article · · The Astronomical Journal
OSTI ID:888613

We present a sample of 218 new quasar pairs with proper transverse separations R{sub prop} < 1 h{sup -1} Mpc over the redshift range 0.5 < z < 3.0, discovered from an extensive follow up campaign to find companions around the Sloan Digital Sky Survey and 2dF Quasar Redshift Survey quasars. This sample includes 26 new binary quasars with separations R{sub prop} < 50 h{sup -1} kpc ({theta} < 10''), more than doubling the number of such systems known. We define a statistical sample of binaries selected with homogeneous criteria and compute its selection function, taking into account sources of incompleteness. The first measurement of the quasar correlation function on scales 10 h{sup -1} kpc < R{sub prop} < 400 h{sup -1} kpc is presented. For R{sub prop} {approx}< 40 h{sup -1} kpc, we detect an order of magnitude excess clustering over the expectation from the large scale (R{sub prop} {approx}> 3 h{sup -1} Mpc) quasar correlation function, extrapolated down as a power law to the separations probed by our binaries. The excess grows to {approx}30 at R{sub prop} {approx} 10 h{sup -1} kpc, and provides compelling evidence that the quasar autocorrelation function gets progressively steeper on sub-Mpc scales. This small scale excess can likely be attributed to dissipative interaction events which trigger quasar activity in rich environments. Recent small scale measurements of galaxy clustering and quasar-galaxy clustering are reviewed and discussed in relation to our measurement of small scale quasar clustering.

Research Organization:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
W-7405-ENG-48
OSTI ID:
888613
Report Number(s):
UCRL-JRNL-218569; ANJOAA; TRN: US200618%%373
Journal Information:
The Astronomical Journal, Vol. 131, Issue 1; ISSN 0004-6256
Country of Publication:
United States
Language:
English