<![CDATA[Fault-tolerant quantum computing is a fundamental requirement for realizing large-scale, reliable quantum processors, as quantum information is inherently vulnerable to noise, decoherence, and operational imperfections. Among existing quantum error correction schemes, surface codes are widely regarded as the most promising approach due to their high error thresholds and compatibility with realistic hardware constraints. This study aims to investigate how surface codes can be engineered to support scalable fault-tolerant quantum computing under non-ideal noise conditions. The research employs a computational and engineering-oriented methodology based on numerical simulations of surface code architectures with varying code distances, physical error rates, and decoding strategies. Performance is evaluated using logical error rates, threshold behavior, and classical decoding overhead as key indicators. The results demonstrate that surface codes achieve exponential suppression of logical errors in sub-threshold regimes, confirming their robustness for scalable error correction. However, the findings also reveal that classical decoding complexity and correlated noise effects emerge as dominant constraints at larger scales. These results indicate that fault tolerance is not solely determined by quantum error correction theory but arises from the integrated performance of quantum hardware and classical processing systems. In conclusion, the study establishes that scalable fault-tolerant quantum computing requires a co-design approach that simultaneously optimizes surface code architecture, noise mitigation, and decoding efficiency to ensure reliable large-scale quantum computation.]]>
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