Abstract
Quantum machine learning has seen considerable theoretical and practical developments in recent years and has become a promising area for finding real world applications of quantum computers. In pursuit of this goal, here we combine state-of-the-art algorithms and quantum hardware to provide an experimental demonstration of a quantum machine learning application with provable guarantees for its performance and efficiency. In particular, we design a quantum Nearest Centroid classifier, using techniques for efficiently loading classical data into quantum states and performing distance estimations, and experimentally demonstrate it on a 11-qubit trapped-ion quantum machine, matching the accuracy of classical nearest centroid classifiers for the MNIST handwritten digits dataset and achieving up to 100% accuracy for 8-dimensional synthetic data.
Highlights
Quantum technologies promise to revolutionize the future of information and communication, in the form of quantum computing devices able to communicate and process massive amounts of data both efficiently and securely using quantum resources
We focus on quantum machine learning (QML)
Rd, only pre-processes the classical data OeðdÞ total time, in order to create effia set of parameters θ 1⁄4 ðθ[1]; θ2; 1⁄4 ; θdÀ1Þ 2 RdÀ1, that will be the parameters of the (d − 1) two-qubit gates we will use in our quantum circuit
Summary
Quantum technologies promise to revolutionize the future of information and communication, in the form of quantum computing devices able to communicate and process massive amounts of data both efficiently and securely using quantum resources. Small quantum computers capable of running representative algorithms were first made available in research laboratories, utilizing both trapped ion[1,2] and superconducting qubits[3,4]. Performance comparisons among different quantum computer hardware have been made for running a host of quantum computing tasks[5,6]. A recent report on achieving quantum supremacy, where a task was performed by a quantum computer that cannot be simulated with any available classical computer[7], is an indication that powerful quantum computers will likely be available to researchers in the near future
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