TY  - JOUR
PB  - SciPost Foundation
DO  - 10.21468/SciPostPhysCore.6.4.087
TI  - Identifying Chern numbers of superconductors from local measurements
PY  - 2023/12/15
UR  - https://www.scipost.org/SciPostPhysCore.6.4.087
JF  - SciPost Physics Core
JA  - SciPost Phys. Core
VL  - 6
IS  - 4
SP  - 087
A1  - Baireuther, Paul
AU  - Płodzień, Marcin
AU  - Ojanen, Teemu
AU  - Tworzydlo, Jakub
AU  - Hyart, Timo
AB  - Fascination in topological materials originates from their remarkable response properties and exotic quasiparticles which can be utilized in quantum technologies. In particular, large-scale efforts are currently focused on realizing topological superconductors and their Majorana excitations. However, determining the topological nature of superconductors with current experimental probes is an outstanding challenge. This shortcoming has become increasingly pressing due to rapidly developing designer platforms which are theorized to display very rich topology and are better accessed by local probes rather than transport experiments. We introduce a robust machine learning protocol for classifying the topological states of two-dimensional (2D) chiral superconductors and insulators from local density of states (LDOS) data. Since the LDOS can be measured with standard experimental techniques, our protocol contributes to overcoming the almost three decades standing problem of identifying the topological phase of 2D superconductors with broken time-reversal symmetry.
ER  -

@Article{10.21468/SciPostPhysCore.6.4.087,
	title={{Identifying Chern numbers of superconductors from local measurements}},
	author={Paul Baireuther and Marcin Płodzień and Teemu Ojanen and Jakub Tworzydło and Timo Hyart},
	journal={SciPost Phys. Core},
	volume={6},
	pages={087},
	year={2023},
	publisher={SciPost},
	doi={10.21468/SciPostPhysCore.6.4.087},
	url={https://scipost.org/10.21468/SciPostPhysCore.6.4.087},
}