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Researchers at the Indian Institute of Science have introduced a noise-aware framework that analytically determines optimal quantum circuit partitioning, reducing required measurement shots by 58% and lowering total error rates by up to 73%. This advancement directly addresses near-term hardware limitations by minimizing resource overhead without relying on speculative future technologies.

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Mandal Indian Institute of Science: Researchers Halve Quantum Algorithm Shots and Cut Energy Use by 62%

Quantum ZeitgeistJuly 29, 20264 min read

How Many Shots Does It Take? A Noise-Aware Quantum Resource Allocation Framework A 58% reduction in the shots needed for reliable quantum computation is now achievable, alongside a 73% decrease in total error compared to conventional methods. This advance directly addresses a core limitation of near-term quantum hardware, optimising resource use for more complex algorithms.

Until now, executing algorithms on quantum computers has required a costly and often excessive number of repeated calculations, known as shots, to ensure reliable results. The Indian Institute of Science (IISc) team of Prateek Kulkarni and Sumit Mandal have, for the first time, developed an analytical expression to determine the optimal number of shots, approximately 8000 in their tests, needed for reliable quantum algorithm execution. The team has devised a new way to…

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