In recent years, quantum computing (QC) research has moved from the realm of theoretical physics and mathematics into real implementations [9]. With many different potential hardware implementations, quantum computer architecture is a rich field with an opportunity to solve interesting new problems and to revisit old ones. This paper presents a QC architecture tailored to physical implementations with highly mobile and persistent quantum bits (qubits). Implementations with qubit coherency times that are much longer than operation times and qubit transportation times that are orders of magnitude faster than operation times lend greater flexibility to the architecture. This is particularly true in the placement and locality of individual qubits. For concreteness, we assume a physical device model based on electron-spin qubits on liquid helium (eSHe) [15].Like many conventional computer architectures, QCs focus on the efficient exposure of parallelism. We present here a QC microarchitecture that enjoys increasing computational parallelism with size and latency scaling only linearly with the number of operations. Although an efficient and high level of parallelism is admirable, quantum hardware is still expensive and difficult to build, so we demonstrate how the software may be optimized to reduce an application's hardware requirements by 25% with no performance loss. Because the majority of a QC's time and resources are devoted to quantum error correction, we also present noise modeling results that evaluate error correction procedures. These results demonstrate that idle qubits in memory need only be refreshed approximately once every one hundred operation cycles.

Quantum computers (QCs) must implement quantum error correcting codes (QECCs) to protect their logical qubits from errors, and modeling the effectiveness of QECCs on QCs is an important problem for evaluating the QC architecture. The previously developed Monte Carlo (MC) error models may take days or weeks of execution to produce an accurate result due to their random sampling approach. We present an alternative analytical error model that generates, over the course of executing the quantum program, a probability tree of the QC's error states. By calculating the fidelity of the quantum program directly, this error model has the potential for enormous speedups over the MC model when applied to small yet useful problem sizes. We observe a speedup on the order of 1,000X when accuracy is required, and we evaluate the scaling properties of this new analytical error model.