论文标题
使用两个QUIT量子芯片进行分类
Classification using a two-qubit quantum chip
论文作者
论文摘要
量子计算具有巨大的潜力，可以推进超出经典范围的机器学习算法。即使尚不存在成熟的通用量子计算机，也可以使用模拟器和已经可用的量子硬件显示其机器学习的预期好处。在这项工作中，我们专注于使用实际的早期量子硬件基于距离的分类。我们扩展了较早的工作，并仅使用两个量子位介绍基于距离的分类算法。我们表明结果与理论上预期的结果相似。
Quantum computing has great potential for advancing machine learning algorithms beyond classical reach. Even though full-fledged universal quantum computers do not exist yet, its expected benefits for machine learning can already be shown using simulators and already available quantum hardware. In this work, we focus on distance-based classification using actual early stage quantum hardware. We extend earlier work and present a distance-based classification algorithm using only two qubits. We show that the results are similar to the theoretically expected results.
