  Despite NISQ devices being severely constrained, hardware- and
algorithm-aware quantum circuit mapping techniques have been developed to
enable successful algorithm executions. Not so much attention has been paid to
mapping and compilation implementations for spin-qubit quantum processors due
to the scarce availability of experimental devices and their small sizes.
However, based on their high scalability potential and their rapid progress it
is timely to start exploring solutions on such devices. In this work, we
discuss the unique mapping challenges of a scalable crossbar architecture with
shared control and introduce SpinQ, the first native compilation framework for
scalable spin-qubit architectures. At the core of SpinQ is the Integrated
Strategy that addresses the unique operational constraints of the crossbar
while considering compilation scalability and obtaining a O(n) computational
complexity. To evaluate the performance of 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
techniques that could increase algorithm success rates on this architecture and
potentially inspire further research on quantum circuit mapping for other
scalable spin-qubit architectures.
