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Transitioning quantum computing from laboratory physical demonstrations to practical, utility-scale processing requires bridging a multi-order-of-magnitude gap between physical gate fidelities and algorithmic error thresholds. While fault-tolerant quantum computing relies on quantum error correction to span this divide, traditional evaluation metrics focused on isolated physical components fail to reflect real-world execution capacity. In this Perspective, we analyze the physical and microarchitectural bottlenecks governing scalable quantum compute engines: the spatial footprint trade-offs between code encoding efficiency and hardware routing, the temporal latencies of closed-loop decoding under strict cryogenic thermal budgets, and the structural performance asymmetries of modular multi-chip networks. We argue that overcoming these multi-faceted scalability barriers demands moving beyond single-layer hardware optimizations toward a holistic full-stack co-design paradigm—jointly tailoring error-correcting code topologies, control microarchitectures, and interconnect networks to unlock sustainable logical throughput.
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Liu et al. (2026) studied this question.
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