No abstract

The pressure of fundamental limits on classical computation and the promise of exponential speedups from quantum effects have recently brought quantum circuits [10] to the attention of the Electronic Design Automation community [18,28,7,27,17]. We discuss efficient quantum logic circuits which perform two tasks: (i) implementing generic quantum computations and (ii) initializing quantum registers. In contrast to conventional computing, the latter task is nontrivial because the state-space of an n-qubit register is not finite and contains exponential superpositions of classical bit strings. Our proposed circuits are asymptotically optimal for respective tasks and improve earlier published results by at least a factor of two.The circuits for generic quantum computation constructed by our algorithms are the most efficient known today in terms of the number of difficult gates (quantum controlled-NOTs). They are based on an analogue of the Shannon decomposition of Boolean functions and a new circuit block, quantum multiplexor, that generalizes several known constructions. A theoretical lower bound implies that our circuits cannot be improved by more than a factor of two. We additionally show how to accommodate the severe architectural limitation of using only nearest-neighbor gates that is representative of current implementation technologies. This increases the number of gates by almost an order of magnitude, but preserves the asymptotic optimality of gate counts.

We give quantum circuits that simulate an arbitrary two-qubit unitary operator up to a global phase. For several quantum gate libraries we prove that gate counts are optimal in the worst and average cases. Our lower and upper bounds compare favorably to previously published results. Temporary storage is not used because it tends to be expensive in physical implementations. For each gate library, the best gate counts can be achieved by a single universal circuit. To compute the gate parameters in universal circuits, we use only closed-form algebraic expressions, and in particular do not rely on matrix exponentials. Our algorithm has been coded in C++.