  Typical address-oriented computer memories cannot recognize incomplete or
noisy information. Associative (content-addressable) memories solve this
problem but suffer from severe capacity shortages. I propose a model of a
quantum memory that solves both problems. The storage capacity is exponential
in the number of qbits and thus optimal. The retrieval mechanism for incomplete
or noisy inputs is probabilistic, with postselection of the measurement result.
The output is determined by a probability distribution on the memory which is
peaked around the stored patterns closest in Hamming distance to the input.
