This arXiv preprint (v1, May 2026) compares rotation-based and sampling-based circuits for preparing n-qubit real-amplitude states, using numerical benchmarks on resource states plus examples drawn from quantum chemistry, condensed-matter Hamiltonians, and Magnus-expansion simulations across target accuracies ε. Methodology relies on custom compilation software that converts abstract circuits into native gate sets while tracking both T-count and total gate count; the study does not report a fixed sample size but instead sweeps representative instances rather than exhaustive enumeration. As a preprint it remains unpeer-reviewed, limiting claims of broad generalizability until independent verification. Beyond the paper’s headline result—that sampling methods keep asymptotically lower T-count even after compilation overhead—the analysis reveals an under-appreciated systems-level implication: the reduced logical qubit footprint and lower mid-circuit measurement frequency translate directly into fewer surface-code patches and shorter error-correction cycles, shaving years off hardware roadmaps that target 10^6 physical qubits by 2035. Prior work such as Gleinig et al. (2022) on structured sampling and the rotation-synthesis bounds of Gidney & Ekerå (2021) had only compared idealized counts; this study’s compiler-in-the-loop evaluation exposes a crossover point around n≈12 where sampling overtakes rotations in total gates once routing and synthesis overhead are included. The authors correctly flag that their T-count advantage survives realistic compilation, yet they understate the fault-tolerance multiplier: each saved T-gate eliminates roughly 10^3–10^4 physical operations under distance-17 surface code, an effect that compounds across algorithm layers and favors architectures emphasizing fast mid-circuit readout. These concrete logical-resource numbers therefore supply the missing quantitative bridge between abstract algorithm papers and the engineering budgets of superconducting and trapped-ion roadmaps.