Selection of molecules with desired properties from random pools of biopolymers has become a powerful tool in biotechnology. On designing an evolution experiment, a certain knowledge of the concomitant fitness landscape is clearly helpful to set up the optimal experimental conditions. The correlation function is a useful means of characterizing a given landscape, since it can be efficiently measured if one has a method of separating a pool of random sequences according to their Hamming distance from a moderately small number of test sequences. In this paper we describe a special type of hybridization chromatography, where a mixture of oligomers (partially) complementary to a given test sequence is hybridized to the test sequence, covalently bound to a matrix. DNA oligomers are eluted in an 'effective temperature gradient' using conditions that minimize the differences of effects of GC versus AT pairs on the melting temperatures. This method should be a means to quickly separate error classes and thus be the crucial step in characterizing fitness landscapes of biopolymers through an experimental approach. It would also be a useful tool to design sequence pools with a bias towards desired mutant spectra.