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Deakin University research demonstrates that in distributed quantum computing, prioritizing error reduction over minimizing communication costs can significantly lower logical error rates. The study reveals that larger distance encodings, such as 'bivariate-bicycle' codes, enable more complex simultaneous operations despite requiring additional physical resources. This finding is critical for scaling quantum networks, showing that optimal performance depends on balancing code distance with internode connectivity rather than simply reducing qubit counts.

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Quantum Computers Link Qubit Encoding to Lower Errors

Quantum ZeitgeistOctober 2, 20265 min read

A single block encoding requires ninety physical ebits for a non-local transversal CNOT operation, yet an alternative utilising two smaller blocks needs only seventy-two. This apparent reduction of eighteen ebits does not necessarily optimise performance, with larger distance encodings potentially lowering overall logical error rates in distributed quantum systems. Selecting qubit arrangements based solely on minimising communication costs may therefore overlook opportunities to improve computational accuracy.

Deakin University research details optimisation of encodings for distributing quantum computations across multiple nodes. Improving performance during operations like transversal CNOT gates is achieved by prioritising error reduction, revealing that minimising communication resources isn’t always best. Larger distance encodings, even with increased qubit numbers overall, can lower error rates during complex calculations. The team also showed a self-dual encoding enables eight simultaneous logical GCZ operations using one physical gate operation. Minimising connections alone does not guarantee optimal performance when constructing large quantum computers from smaller interconnected components.…

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