We show that the first 10 eigencomponents of the Karhunen-Loève expansion or Principal Component Analysis ( PCA ) provide a robust classification scheme for the identification of stars , galaxies and quasi-stellar objects from multi-band photometry .
To quantify the efficiency of the method , realistic simulations are performed which match the planned Large Zenith Telescope survey .
This survey is expected to provide spectral energy distributions with a resolution R \simeq 40 for \sim 10 ^ { 6 } galaxies to R \leq 23 ( z \sim 1 ) , \sim 10 ^ { 4 } QSOs , and \sim 10 ^ { 5 } stars .

We calculate that for a median signal-to-noise ratio of 6 , 98 % of stars , 100 % of galaxies and 93 % of QSOs are correctly classified .
These values increase to 100 % of stars , 100 % of galaxies and 100 % of QSOs at a median signal-to-noise ratio of 10 .
The 10-component PCA also allows measurement of redshifts with an accuracy of \sigma _ { \mathrm { Res . } } \la 0.05 for galaxies with z \la 0.7 , and to \sigma _ { \mathrm { Res . } } \la 0.2 for QSOs with z \ga 2 , at a median signal-to-noise ratio of 6 .
At a median signal-to-noise ratio 20 , \sigma _ { \mathrm { Res . } } \la 0.02 for galaxies with z \la 1 and for QSOs with z \ga 2.5 ( note that for a median S / N ratio of 20 , the bluest/reddest objects will have a signal-to-noise ratio of \la 2 in their reddest/bluest filters ) .
This redshift accuracy is inherent to the R \simeq 40 resolution provided by the set of medium-band filters used by the Large Zenith Telescope survey .
It provides an accuracy improvement of nearly an order of magnitude over the photometric redshifts obtained from broad-band BVRI photometry .