Export citation

Export citation

Choose format for download:

Download Citation
  • Letter

Topological classification of intrinsic three-dimensional superconductors using anomalous surface construction

Zhongyi Zhang1,2,*, Jie Ren1,2,*, Yang Qi3,4, and Chen Fang1,5,6,†

  • 1Beijing National Laboratory for Condensed Matter Physics and Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
  • 3Center for Field Theory and Particle Physics, Department of Physics, Fudan University, Shanghai 200433, China
  • 4State Key Laboratory of Surface Physics, Fudan University, Shanghai 200433, China
  • 5Songshan Lake Materials Laboratory, Dongguan, Guangdong 523808, China
  • 6Kavli Institute for Theoretical Sciences, Chinese Academy of Sciences, Beijing 100190, China

  • *These authors contributed equally to this study.
  • †cfang@iphy.ac.cn

Phys. Rev. B 106, L121108 – Published 20 September, 2022

DOI: https://doi.org/10.1103/PhysRevB.106.L121108

Abstract

Intrinsic topological superconductors have protected gapless Majorana modes, bound and/or propagating, at the natural boundaries of the sample, without requiring field, defect, or heterostructure. We establish the complete classification/construction of intrinsic topological superconductors jointly protected by point-group and time-reversal symmetries in three dimensions. This is obtained from enumerating distinct ways for stacking nth-order irreducible building blocks, minimal anomalous surface states of nth-order topological superconductors. Particularly, our method provides a unified description of possible surface anomalies away from high-symmetry points/lines in terms of the homotopy group of the surface mass field.

Physics Subject Headings (PhySH)

Authorization Required

We need you to provide your credentials before accessing this content.

Supplemental Material (Subscription Required)

References (Subscription Required)

Outline

Information

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation