npj Quantum Information (Sep 2022)

Experimental unsupervised learning of non-Hermitian knotted phases with solid-state spins

  • Yefei Yu,
  • Li-Wei Yu,
  • Wengang Zhang,
  • Huili Zhang,
  • Xiaolong Ouyang,
  • Yanqing Liu,
  • Dong-Ling Deng,
  • L.-M. Duan

DOI
https://doi.org/10.1038/s41534-022-00629-w
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 9

Abstract

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Abstract Non-Hermiticity has widespread applications in quantum physics. It brings about distinct topological phases without Hermitian counterparts, and gives rise to the fundamental challenge of phase classification. Here, we report an experimental demonstration of unsupervised learning of non-Hermitian topological phases with the nitrogen-vacancy center platform. In particular, we implement the non-Hermitian twister model, which hosts peculiar knotted topological phases, with a solid-state quantum simulator consisting of an electron spin and a nearby 13C nuclear spin in a nitrogen-vacancy center in diamond. By tuning the microwave pulses, we efficiently generate a set of experimental data without phase labels. Furthermore, based on the diffusion map method, we cluster this set of experimental raw data into three different knotted phases in an unsupervised fashion without a priori knowledge of the system, which is in sharp contrast to the previously implemented supervised learning phases of matter. Our results showcase the intriguing potential for autonomous classification of exotic unknown topological phases with experimental raw data.