Configurable sublinear circuits for quantum state preparation

The theory of quantum algorithms promises unprecedented benefits harnessing the laws mechanics for solving certain computational problems. A prerequisite applying to a wide range real-world problems is loading classical data state. Several circuit-based methods have been proposed encoding as probability amplitudes However, in these methods, either circuit depth or width must grow linearly with size, nullifying advantage representing exponentially many In this paper, we present configurable bidirectional procedure that addresses problem by tailoring resource trade-off between and depth. particular, show configuration encodes an N-dimensional using whose both sublinearly N. We demonstrate proof-of-principle implementations on five computers accessed through IBM IonQ cloud services.