2008/03/20 by Jeongho Bang, Bang, Jeongho, James Lim +5
Computer Science · Physics and Astronomy · #FOS: Physical sciences #Neural Networks and Applications #Quantum Computing Algorithms and Architecture #Quantum Information and Cryptography #Quantum Physics (quant-ph) #quant-ph
paper · pdf · doi:10.48550/arxiv.0803.2976
4 pages, 8 figures; Revisions made to improve the introduction and motivation
openalex publication_date 2008/03/20 · arxiv created 2008/03/31 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
We propose a novel notion of a quantum learning machine for automatically controlling quantum coherence and for developing quantum algorithms. A quantum learning machine can be trained to learn a certain task with no a priori knowledge on its algorithm. As an example, it is demonstrated that the quantum learning machine learns Deutsch's task and finds itself a quantum algorithm, that is different from but equivalent to the original one.