As a theoretical condensed matter physicist, I like systems that combine fundamental physics with experimental relevance and potential real-world applications: Why do the charge carriers behave the way they do? What might be an experimental signature of that effect? Could we think of an application using this fascinating property?
In my team, we work on the following connected research topics:
Quantum Confinement and Transport
Electrostatically confined quantum wires and quantum dots in bilayer graphene.
We study confined states, quantum transport, and electron optics in two-dimensional materials, with a particular focus on electrostatically defined structures in bilayer graphene. Quantum dots, channels, point contacts, and cavities provide versatile settings in which geometry, material properties, and external perturbations (such as fields and proximitizing materials) can be used to shape electronic states and transport. Close exchange with experimental groups allows theory to interpret measurements and predict new regimes for future devices.
Non-equilibrium Driven Dynamics
Light-driven charge-carrier dynamics in different two-dimensional materials.
Ultra-fast subcycle dynamics of charge carriers driven by intense laser pulses enables the investigation of fundamental properties of quantum states on their shortest length and time scales while also holding great potential for light-driven quantum electronics applications. This combination of fundamental non-equilibrium physics and potential technological applications motivates us to theoretically investigate driven electron dynamics at ultra-short time scales in low-dimensional materials.
Electronic, Mechanical, and Topological Properties
Van-der-Waals hetero structures of different atomic lattices
Our work explores how 2D material combination, strain, stacking, and electrostatic control affect the electronic, mechanical, and topological properties of layered materials. This includes different types of heterostructures and moiré materials. Being able to control a material’s electronic, mechanical, and topological properties is essential for its use in any functional device.
Computational Quantum Design
Inverse optimization of control protocols for quantum-state transfer.
We develop computational approaches for modeling and controlling complex quantum systems. These range from numerical diagonalization, wave-packet dynamics, and device and transport simulations to machine-learning-based inverse optimization. Scalable implementations on CPU and GPU architectures enable high-throughput calculations and connect theoretical condensed-matter physics with computational science.
Methods and Collaboration
Our research combines analytical models with large-scale numerical simulations and machine learning techniques. Collaboration with experimental partners is an integral part of this program: calculations are used both to explain observed phenomena and to guide the exploration of new material systems, device geometries, and control protocols.
