*Supplemental
materials of***
**

Clustering of High Redshift (z>2.9) Quasars from the Sloan Digital Sky Survey

**high-resolution
paper****
****
astro-ph****
****Press
Release**

*last updated: Feb 2007 by Yue
Shen *

**Tables
and Figures**

**datafile1.txt**
: the entile Table 1 in the paper.

**fb1.eps** : Fig. B1 of the paper; the illustrative
figure for the SDSS tiling geometry.

**Geometry**

The angular geometry description
of the quasar clustering subsamle can be found in Appendix B of the paper. Files
necessary to generate the masks are present here in fits format. You need to
install the*
idlutils*
and* idlspec2d*
products first. Use the READ_FITS_POLYGONS
routine in *idlutils* to read these fits files.

The first two files are
enough for your purpose of generating random catalogs in the same regions as
the clustering subsample with or without bad imaging fields. The other three
files are useful if you want to plot the targeting and tiling geometry as shown
in Fig. B1 of the paper. Note that for the highz_spectro_window.fits file, the
starting plate is 0716, because prior plates were associated with tiling chunks
with targeting version lower than v3_1_0. However, a later plate number doesn't
guarantee the plate is necessarily tiled in a tiling chunk with targeting version
no lower than v3_1_0. In other words, you need to use both tilingChunks.fits
(with targeting version incorporated) and highz_spectro_window.fits
to reject lower target version regions.

full_sectors.fits : the set of balkanized spherical polygons describing
the geometry of the clustering subsample. Note that here "balkanization" is
only done within each tiling chunks (tileRun). Since different tiling chunks
could overlap with each other (see the examples in Fig. B1 of the paper), you
need to do "balkanization" again to get the fully "balknized" sectors, and to
get the total net area covered by these sectors. Such a file is provided as
full_sectors_balkans.fits, where the
tiling chunk and plate info is gone.

bad_fields_balkans.fits : a secondary
mask describing the regions of bad imaging fields.

targetingChunks.fits : the set of polygons
describing the geometry of target chunks.

tilingChunks.fits : the set of polygons describing
the geometry of tiling chunks.

highz_spectro_window.fits : the set
of polygons describing the geometry of spectroscopic plates (tiles) starting
from plate 0716.

**How to determine
whether or not a given point (xyz or RA/DEC) is in regions described by the
set of polygons?**

Use routine **IS_IN_WINDOW**
in *idlutils*.

I also put the original
files describing the boundaries of the targeting chunks and tiling chunks below
(these files can also be obtained from **CAS**
and/or **DR5
site**). There files are necessary if you want to generate the above
fits files by yourself.

**tilingBoundaries**
: table describing the boundaries of tiling chunks; its parent view is **tilingGeometry**.

**targetingChunk** : file describing
the boundaries of targeting chunks (never used in generating **full_sectors.fits**,
but is of general SDSS geometry interests).

**maindr5spectro.par** : file
describing the geometry of spectroscopic plates.

**runQA_DR5.csv** (**46M!!**):
file describing detailed SDSS run quality, used to identify bad imaging fields.
After identifying bad imaging fields, you need to use the **SDSS_RUN2WINDOW**
routine in the SDSS *photoop* product. (Yes, you have to ** install
photoop** product to use sdss_run2window and related routines).

The SDSS tiling geometry
is rather complicated, please refer to the description in Appendix B of the
paper for more information. If you REALLY want to play with spherical polygons
for SDSS, you may want to check the **SDSS
glossary** for some jargons and especially different coordinate systems
that will **ALL** be used in those geometry tables (you will find
even mixed types of coordinate systems!); a description of the *mangle*
product by A. Hamilton can be found **here**.
In the future, the **CAS**
will probably incorporate all the necessary gemoetry information into tables
and provide a user guide to utilize these tables.

**Constraint on
Quasar Lifetime**

We have used the Jing (1998) analytical formula to compute the linear bias. In principle one can use the bias computed from numerical simulation results. However, to interpret our measured correlation function we need a fine redshift grid. Hence using the analytical bias formula is convenient. We have compared the analytical formula with that computed from numerical simulations at two redshifts: z=3 and z=4; and the analytical bias formula is a proper prescription for our integrated correlation function (see Appendix C of the paper for more discussions). Also, we compared the Press-Schechter formula and the Sheth-Tormen formula for the halo mass function with numerical simulation at z=3 and z=4. It is found that the ST formula is a better prescription for the dark matter halo mass function. The numerical simulations we used were kindly provided by Paul Bode & J. P. Ostriker, and the related figures are not included in the paper.

**HMF_compare_z3.eps**
: halo mass function at z=3 (y axis units should be h^4 Mpc^{-3} M_{\odot}^{-1})

**HMF_compare_z4.eps** :
halo mass function at z=4 (y axis units should be h^4 Mpc^{-3} M_{\odot}^{-1})

**comp_halo_mass_CF_Paul_z3_z4.eps**
: comparsion of the DM CF and halo (M>2e12 h^{-1} M_{\odot}) CF with results
computed using analytical CDM power spectrum and linear bias formula.