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Machine learning & artificial intelligence in the quantum domain : a review of recent progress

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Machine learning & artificial intelligence in the quantum domain : a review of recent progress

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DUNJKO, Vedran, Hans J. BRIEGEL, 2018. Machine learning & artificial intelligence in the quantum domain : a review of recent progress. In: Reports on Progress in Physics. 81(7), 074001. ISSN 0034-4885. eISSN 1361-6633. Available under: doi: 10.1088/1361-6633/aab406

@article{Dunjko2018-07Machi-42865, title={Machine learning & artificial intelligence in the quantum domain : a review of recent progress}, year={2018}, doi={10.1088/1361-6633/aab406}, number={7}, volume={81}, issn={0034-4885}, journal={Reports on Progress in Physics}, author={Dunjko, Vedran and Briegel, Hans J.}, note={Article Number: 074001} }

Briegel, Hans J. Briegel, Hans J. eng Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and progress in a broad spectrum of research investigating ML and AI in the quantum domain. Dunjko, Vedran 2018-07-16T09:53:42Z Dunjko, Vedran 2018-07-16T09:53:42Z Machine learning & artificial intelligence in the quantum domain : a review of recent progress 2018-07

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