Quantum Computing with Distributed Modules

This thesis describes our work on optimizing quantum control and scaling up quantum computers. We demonstrate the application of automatic differentiation in quantum optimal control, which allows us to specify advanced optimization criteria and incorporate them in the optimization process of quantum control with ease. These criteria enable more intricate control on the evolution path, suppression of departures from the truncated model subspace, as well as minimization of the physical time needed to perform high-fidelity state preparation and unitary gates. We subsequently present our experimental efforts in efficiently scaling up a quantum computer. The innovation of quantum random access memory (qRAM) architecture with multimode circuit QED establishes a promising path towards expanding the information processing power of a quantum device, without introducing control-resources overhead. Using a single Josephson junction transmon circuit serving as the central processor, we demonstrate universal operations on a nine-qubit random access memory. We further present our experimental results in establishing bidirectional and deterministic photonic communication between two remote superconducting multimode processors, connected through a one-meter long coaxial cable. This device demonstrates a prototype of setting up a scalable and distributed quantum computing cluster that could solve a harder computational problem.