2,310 research outputs found
Artificial Intelligence and Machine Learning for Quantum Technologies
In recent years, the dramatic progress in machine learning has begun to impact many areas of science and technology significantly. In the present perspective article, we explore how quantum technologies are benefiting from this revolution. We showcase in illustrative examples how scientists in the past few years have started to use machine learning and more broadly methods of artificial intelligence to analyze quantum measurements, estimate the parameters of quantum devices, discover new quantum experimental setups, protocols, and feedback strategies, and generally improve aspects of quantum computing, quantum communication, and quantum simulation. We highlight open challenges and future possibilities and conclude with some speculative visions for the next decade
Quantum machine learning and quantum biomimetics: A perspective
Quantum machine learning has emerged as an exciting and promising paradigm
inside quantum technologies. It may permit, on the one hand, to carry out more
efficient machine learning calculations by means of quantum devices, while, on
the other hand, to employ machine learning techniques to better control quantum
systems. Inside quantum machine learning, quantum reinforcement learning aims
at developing "intelligent" quantum agents that may interact with the outer
world and adapt to it, with the strategy of achieving some final goal. Another
paradigm inside quantum machine learning is that of quantum autoencoders, which
may allow one for employing fewer resources in a quantum device via a training
process. Moreover, the field of quantum biomimetics aims at establishing
analogies between biological and quantum systems, to look for previously
inadvertent connections that may enable useful applications. Two recent
examples are the concepts of quantum artificial life, as well as of quantum
memristors. In this Perspective, we give an overview of these topics,
describing the related research carried out by the scientific community.Comment: Invited Perspective article for Machine Learning: Science and
Technology, 17 pages, 6 figures, 110 reference
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