The realization of fault-tolerant quantum computing is currently impeded by the stochastic nature of qubit decoherence and the inherent complexity of scaling control systems. This study rigorously evaluates the architectural innovations of Google’s Willow processor, specifically investigating its efficacy in mitigating noise through surface code error correction. The primary objective is to verify the hypothesis of exponential error suppression within a superconducting transmon array, determining if the system can surpass the critical “break-even” point. Methodologically, the research employs a quantitative performance analysis, configuring physical qubits into logical units of varying code distances (d=3 to d=7) and subjecting them to sustained syndrome extraction cycles under millikelvin cryogenic conditions. Results indicate a fundamental departure from previous scaling paradoxes; logical error rates were observed to halve with every increment in code distance, definitively crossing the algorithmic break-even threshold. The data confirms that real-time decoding and optimized tunable coupler designs effectively isolate errors, preventing topological lattice corruption. In conclusion, the Willow chip provides empirical validation that increasing system size now yields higher fidelity, establishing a critical engineering baseline for the development of large-scale, utility-grade quantum computers.