Quantum Edge Topology

Project funded by Novo Nordisk Foundation (Projects), grant NNF23OC0086670. Participating organisations named by the source: Aarhus University. Runs n/a to 2028-07-31. Keywords: Physics. Source: OpenAIRE Graph, from the funder's project data (collected by OpenAIRE on 2025-08-01); national funding data, not CORDIS. Abstract given by the source: The purpose of the project is to explain and investigate two newly discovered topological phenomena in quantum physics. Both phenomena relate to Chern insulators, i.e. crystalline materials with current conducting edges and insulating interiors. Furthermore, the edge currents are topological, meaning that they can only run in one direction even in noisy environments. It was recently discovered that certain noncrystalline materials have topological currents not only on the edge, but also in their interior, and the project aims to explain these currents and investigate their nature. The other phenomenon is the observation that Chern insulators simultaneously show two different types of topology when they are made narrow in one direction. The project aims to explain why and when this happens and also to find new versions of this phenomenon. The project will contribute to charting the area of quantum topology with interesting potential applications in quantum engineering and electronics.

Original source.

Source: OpenAIRE Graph: projects of national funders, OpenAIRE, from the project data of Novo Nordisk Foundation. Retrieved 2026-11-02. Licence: Creative Commons Attribution 4.0 (OpenAIRE Graph). Selected metadata, adapted presentation; the publisher's record is authoritative. No endorsement by the source is implied. Licence: Creative Commons Attribution 4.0 (CC BY 4.0).

AI-assisted summary: The Quantum Edge Topology project, funded by the Novo Nordisk Foundation, aims to investigate newly discovered topological phenomena in quantum physics related to Chern insulators. It involves Aarhus University and runs until July 31, 2028. Suggested technology pillar: enabling. Generated by AI from the public source text; it may contain errors and the original source is authoritative.