A Rust-accelerated, topology-informed workflow for Kuramoto--XY quantum simulation and NISQ benchmarking

This methods preprint describes the software and experimental workflow behind scpn-quantum-control, an open-source framework for mapping heterogeneous Kuramoto-type oscillator networks to XY spin Hamiltonians, compiling topology-informed variational ansatze, benchmarking simulation paths, and executing reproducible NISQ hardware experiments. The workflow combines Python/Qiskit orchestration with a Rust/PyO3 acceleration layer for hot-path kernels including coupling-matrix construction, Hamiltonian assembly, trajectory features, hybrid digital--analog partitioning, and protected-subspace diagnostics. The manuscript reports artefact-generated timings across local workstation, ML350, Vertex AI CPU, and Vertex AI Tesla T4 contexts, with checksum parity across Python, Rust, and Go kernels. The record includes manuscript source, notes bibliography, and PDF. It is an archival methods record for the repository and its reproducibility artefacts, not an independent claim of broad quantum advantage.