Research Areas in Theoretical Physics 2
We study dynamical instabilities arising from optical feedback, optical injection or mode coupling in lasers. The carrier dynamics in the gain material (e.g., semiconductor nanostructures) plays a central role. Another research topic concerns the extent to which these optical systems can be used for hardware-based machine learning. We use numerical methods to solve coupled differential equations as well as analytical methods of nonlinear dynamics for bifurcation analysis.
Reservoir computing is a machine learning method that can be easily implemented in hardware and is being intensively investigated in the research group. In the project NeurosensEar Neuromorphic Acoustic Sensor Technology for High-Performance Hearing Aids of Tomorrow, funded by the Carl Zeiss Foundation, we are investigating micro-mechanical resonators as InSensor Reservoir Computers.
DFG Projekt (2020-2023) "Hybrid photonic computing in delay-coupled non-linear systems with memory"
Teilprojekt im Sonderforschungsbereich SFB910 (2019-2022) "Collective phenomena in laser networks with nonidentical units"
- realize all optical reservoir computing schemes (evaluation via benchmark tasks: Chaotic time series prediction, Memory capacity, Channel equalization etc.)
- develop numerical framework for simulating highly connected delay-coupled networks with memory,
- analyze impact of network topology on computing performance.
- explore correlations of performance and bifurcation structure