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Researchers have demonstrated that variational quantum eigensolvers can utilize embarrassingly parallel workflows to distribute calculations across multiple processors without requiring direct inter-processor links. This approach mitigates errors caused by inconsistent noise profiles on different chips, offering a potential pathway toward scalable quantum computations using existing hardware limitations. By dividing tasks into independent units for classical analysis, this method bypasses current connectivity bottlenecks in linking quantum processors.

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Researchers Achieve Speedup with Parallel Quantum Algorithms

Quantum ZeitgeistAugust 24, 20264 min read

Distributing quantum calculations across multiple processors typically demands direct communication between them. This work demonstrates variational quantum eigensolvers can instead leverage ‘embarrassingly parallel’ workflows, requiring no inter-processor links, to mitigate errors arising from differing noise profiles on each chip. Evaluations using the CUNQA platform suggest potential pathways towards scalable computations without complex hardware interconnectivity.

The team evaluated three distinct strategies for distributing calculations within the Variational Quantum Eigensolver algorithm using the CUNQA platform. The method enables more efficient computation by dividing quantum tasks between multiple processing units with subsequent classical analysis of the results. These workflows address challenges posed by inconsistencies in noise levels found in current quantum hardware. The team investigated how to split up calculations for the Variational Quantum Eigensolver algorithm using multiple processing units without…

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