A dynamic learning paradigm for quantum computers

We present a dynamic learning paradigm for ``programming'' a general quantum computer. We first apply the method to a system of two coupled superconducting quantum interference devices (SQUIDs), and demonstrate learning of both XOR and XNOR for a pure quantum state. Theoretical exact solutions confirm our results. The method can be also be used for mixed states. We next apply the method to a system of three SQUIDs and demonstrate learning of the Toffoli and Fredkin gates. Experimental work is in progress.