  Baryonic Acoustic Oscillations (BAO) and their effects on the matter power
spectrum can be studied by using the Lyman-alpha absorption signature of the
matter density field along quasar (QSO) lines of sight. A measurement
sufficiently accurate to provide useful cosmological constraints requires the
observation of ~100000 quasars in the redshift range 2.2<z<3.5 over ~8000 deg2.
Such a survey is planned by the Baryon Oscillation Spectroscopic Survey (BOSS)
project of the Sloan Digital Sky Survey (SDSS-III).In practice, one needs a
stellar rejection of more than two orders of magnitude with a selection
efficiency for quasars better than 50% up to magnitudes as large as g ~ 22. To
obtain an appropriate target list and estimate quasar redshifts, we have
developed an Artificial Neural Networks (NN) with a multilayer perceptron
architecture. The input variables are photometric measurements, i.e. the object
magnitudes and their errors in the five bands (ugriz) of the SDSS photometry.
For target selection, we achieve a non-quasar point-like object rejection of
99.6% and 98.5% for a quasar efficiency of, respectively, 50% and 85%. The
photometric redshift precision is of the order of 0.1 over the region relevant
for BAO studies.
