SpinQ: Compilation strategies for scalable spin-qubit architectures
In most qubit realizations, prototype devices are available and are already utilized in both industry and academic research. Despite being severely constrained, hardware- and algorithm-aware quantum circuit mapping techniques have been developed for enabling successful algorithm executions during the NISQ era, targeting mostly technologies with high qubit counts. Not so much attention has been paid to the implementation of compilation methods for quantum processors based on spin-qubits due to the scarce availability of current experimental devices and their small sizes. However, based on their high scalability potential and their rapid progress it is timely to start exploring quantum circuit mapping solutions for these spin-qubit devices. In this work, we discuss the unique mapping challenges of a scalable spin-qubit crossbar architecture with shared control [arXiv:1711.03807] and introduce $\textit{SpinQ}$, the first native compilation framework for scalable spin-qubit architectures that maps quantum algorithms on this crossbar architecture. At the core of $\textit{SpinQ}$ is the $\textit{Integrated Strategy}$ that addresses the unique operational constraints of the crossbar while considering compilation (execution time) scalability, having a $O(n)$ computational complexity. To evaluate the performance of $\textit{SpinQ}$ on this novel architecture, we compiled a broad set of well-defined quantum circuits and performed an in-depth analysis based on multiple metrics such as gate overhead, depth overhead, and estimated success probability, which in turn allowed us to create unique mapping and architectural insights. Finally, we propose novel mapping technique improvements for the crossbar architecture that could increase algorithm success rates and potentially inspire further research on quantum circuit mapping techniques for other scalable spin-qubit architectures.