0 Datasets
0 Files
Get instant academic access to this publication’s datasets.
Yes. After verification, you can browse and download datasets at no cost. Some premium assets may require author approval.
Files are stored on encrypted storage. Access is restricted to verified users and all downloads are logged.
Yes, message the author after sign-up to request supplementary files or replication code.
Join 50,000+ researchers worldwide. Get instant access to peer-reviewed datasets, advanced analytics, and global collaboration tools.
✓ Immediate verification • ✓ Free institutional access • ✓ Global collaborationJoin our academic network to download verified datasets and collaborate with researchers worldwide.
Get Free AccessGapless helical edge modes are a hallmark of the quantum spin Hall effect. Protected by time-reversal symmetry, each edge contributes a quantized zero-temperature conductance quantum $G_0 \equiv e^2/h$. However, the experimentally observed conductance in WTe$_2$ decreases below $G_0$ per edge already at edge lengths around 100 nm, even in the absence of explicit time-reversal breaking due to an external field or magnetic impurities. In this work, we show how a time-reversal breaking excitonic condensate with a spin-spiral order that can form in WTe$_2$ leads to the breakdown of conductance quantization. We perform Hartree-Fock calculations to compare time-reversal breaking and preserving excitonic insulators. Using these mean-field models we demonstrate via quantum transport simulations that weak non-magnetic disorder reproduces the edge length scaling of resistance observed in the experiments. We complement this by analysis in the Luttinger liquid picture, shedding additional light on the mechanism behind the quantization breakdown.
Yanqi Wang, Michał Papaj, Joel Moore (2023). Breakdown of helical edge state topologically protected conductance in time-reversal-breaking excitonic insulators. , DOI: https://doi.org/10.48550/arxiv.2305.09202.
Datasets shared by verified academics with rich metadata and previews.
Authors choose access levels; downloads are logged for transparency.
Students and faculty get instant access after verification.
Type
Preprint
Year
2023
Authors
3
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.48550/arxiv.2305.09202
Access datasets from 50,000+ researchers worldwide with institutional verification.
Get Free Access