Experimental quantum kernel trick with nuclear spins in a solid

@article{Kusumoto2021ExperimentalQK,
  title={Experimental quantum kernel trick with nuclear spins in a solid},
  author={Takeru Kusumoto and Kosuke Mitarai and Keisuke Fujii and Masahiro Kitagawa and Makoto Negoro},
  journal={npj Quantum Information},
  year={2021},
  volume={7},
  pages={1-7}
}
The kernel trick allows us to employ high-dimensional feature space for a machine learning task without explicitly storing features. Recently, the idea of utilizing quantum systems for computing kernel functions using interference has been demonstrated experimentally. However, the dimension of feature spaces in those experiments have been smaller than the number of data, which makes them lose their computational advantage over explicit method. Here we show the first experimental demonstration… 

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