Tomas Löfwander

Department of Microtechnology and Nanoscience – MC2
Applied Quantum Physics Laboratory

Phone: +46 31 772 8031
Office: MC2, foom C521
Research focus:
Quantum transport theory of charge, spin, and heat in nanoscale heterostructures, graphene, and unconventional superconductors. One recent focus within graphene research has been modeling and simulation of the half-integer quantum Hall effect, motivated by the development of a quantum Hall resistance standard. Another focus has been on the non-linear response and ballistic transport of electrons in graphene under time-dependent potentials, motivated by applications in high-frequency electronics, for instance THz sensing and frequency multiplication.
Theoretical methods: 
We utilize either analytic approaches based on Landauer-Büttiker scattering theory, including Floquet theory for time-dependent problems, or a recursive Green’s function method based on tight-binding models for simulations. We have developed a non-equilibrium Green’s function based quantum transport solver (knitting algorithm, running on CPUs with MPI) applicable to both graphene and superconducting nanostructures; we supervise the development of a solver of the quasiclassical Green’s function theory for layered unconventional superconductors running on GPUs.

Focus of future research:
  • Quantum Hall effect in graphene on SiC
  • Quantum transport theory for graphene, other 2D materials, and van der Waals heterostructures of these

Highlights of previous research:
Prediction of nonlinearities in ballistic transport in graphene:

Y. Korniyenko, O. Shevtsov, and T. Löfwander
“Nonlinear response of a ballistic graphene transistor with an ac-driven gate: High harmonic generation and terahertz detection”
Phys. Rev. B 94, 125445 (2016)

Prediction of breakdown of the quantum Hall effect in graphene with bilayer stripe defects:

T. Löfwander, P. San-José, E. Prada,
" Quantum Hall effect in graphene with twisted bilayer stripe defects",
Phys. Rev. B 87, 205429 (2013)

Published: Fri 24 Nov 2017.