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Nonlocal Spin Correlation as a Signature of Ising Anyons Trapped in Vacancies of the Kitaev Spin Liquid.
Takahashi, Masahiro O; Yamada, Masahiko G; Udagawa, Masafumi; Mizushima, Takeshi; Fujimoto, Satoshi.
Afiliação
  • Takahashi MO; Department of Materials Engineering Science, Osaka University, Toyonaka 560-8531, Japan.
  • Yamada MG; Department of Materials Engineering Science, Osaka University, Toyonaka 560-8531, Japan.
  • Udagawa M; Department of Physics, The University of Tokyo, Tokyo 113-0033, Japan.
  • Mizushima T; Department of Physics, Gakushuin University, Mejiro, Toshima-ku 171-8588, Japan.
  • Fujimoto S; Department of Physics, Gakushuin University, Mejiro, Toshima-ku 171-8588, Japan.
Phys Rev Lett ; 131(23): 236701, 2023 Dec 08.
Article em En | MEDLINE | ID: mdl-38134764
ABSTRACT
In the Kitaev chiral spin liquid, Ising anyons are realized as Z_{2} fluxes binding Majorana zero modes, which, however, are thermal excitations with finite decay rates. On the other hand, a lattice vacancy traps a Z_{2} flux even in the ground state, resulting in the stable realization of a Majorana zero mode in a vacancy. We demonstrate that spin-spin correlation functions between two vacancy sites exhibit long-range correlation arising from the fractionalized character of Majorana zero modes, in spite of the strong decay of bulk spin correlations. Remarkably, this nonlocal spin correlation does not decrease as the distance between two vacancy sites increases, signaling Majorana teleportation. Furthermore, we clarify that the nonlocal correlation can be detected electrically via the measurement of nonlocal conductance between two vacancy sites, which is straightforwardly utilized for the readout of Majorana qubits. These findings pave the way to the measurement-based quantum computation with Ising anyons trapped in vacancies of the Kitaev spin liquid.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article