Reducing the Complexity of Matrix Multiplication by Quantum Computing
A preprint on arXiv presents a quantum algorithm that reduces the computational complexity of matrix multiplication compared to known classical methods. The work is posted under quant-ph and targets the asymptotic cost of matrix multiplication.
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What this could mean
- 0–2 yearsPlausible
If the algorithm's qubit and gate overhead is modest, a simplified version could be benchmarked on existing superconducting or trapped-ion processors for small matrices, validating the theoretical speedup and providing a reusable linear-algebra primitive.
The paper gives a theoretical construction; near-term testability depends on resource requirements. Current quantum platforms already perform small matrix operations, so a reduced-complexity method could plausibly be mapped to limited hardware within two years.
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