Abstract
We present a scalable quantum algorithm to solve binary consensus in a system of n crash-prone quantum processes. The algorithm works in \({\mathcal O}(\text{polylog }n)\) time sending \({\mathcal O}(n \text{ polylog } n)\) qubits against the adaptive adversary. The time performance of this algorithm is asymptotically better than a lower bound \(\Omega(\sqrt{n/\log n})\) on time of classical randomized algorithms against adaptive adversaries. Known classical randomized algorithms having each process send \({\mathcal O}(\text{polylog } n)\) messages work only for oblivious adversaries. Our quantum algorithm has a better time performance than deterministic solutions, which have to work in Ω(t) time for t < n failures.
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Chlebus, B.S., Kowalski, D.R., Strojnowski, M. (2010). Scalable Quantum Consensus for Crash Failures. In: Lynch, N.A., Shvartsman, A.A. (eds) Distributed Computing. DISC 2010. Lecture Notes in Computer Science, vol 6343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15763-9_24
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DOI: https://doi.org/10.1007/978-3-642-15763-9_24
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