Year: 2023
Type: article
Abstract: Bilayer graphene is a nanomaterial that allows for well-defined, separated quantum states to be defined by electrostatic gating and, therefore, provides an attractive platform to construct tunable quantum dots. When a magnetic field perpendicular to the graphene layers is applied, the graphene valley degeneracy is lifted, and splitting of the energy levels of the dot is observed. Although bilayer graphene quantum dots have recently been realized in experiments, it is critically important to devise robust methods that can identify the observed quantum states from accessible measurement data. Here, we develop an efficient algorithm for extracting the model parameters needed to characterize the states of a bilayer graphene quantum dot. Specifically, we put forward a Hamiltonian-guided random search method and demonstrate robust identification of quantum states on both simulated and experimental data.
Source: Physical Review Applied
Institutions: University of Zurich, ETH Zurich, Institute for Theoretical Physics, University of Basel, MIT Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Laboratory for Solid State Physics, Comenius University Bratislava, Delft University of Technology
Language: English
Subfield: Atomic and Molecular Physics, and Optics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: bronze
Funders: National Science Foundation, European Commission, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Agentúra na Podporu Výskumu a Vývoja, Vedecká Grantová Agentúra MŠVVaŠ SR a SAV, European Research Council, National Center of Competence in Research Quantum Science and Technology, H2020 European Research Council, H2020 Marie Skłodowska-Curie Actions
Awards: Slovak Academic and Scientific PROgramme for experienced researchers, G3878479425, G4246281229, G434337789, Slovak Academic and Scientific PROgramme for experienced researchers, Modelovanie nových fáz a fázových prechodov v kondenzovaných látkach, G528290496, Využitie metód strojového učenia vo fyzike kondenzovaných látok, G8608589759, Topological Mechanical Metamaterials
OpenAlex ID: W4319311879