Making photonics smart - The fast growth in smart technologies evolves our society and economics. At the core of this development lie devices, instruments, and processor hardware controlled by machine learning algorithms and artificial intelligence, allowing them to operates autonomously, to respond to their environment, and even outpace human capabilities in tackling outstanding challenges. Many of those challenges, such as image recognition, big data communications, and remote sensing, can be broken down to process optical data in an ultrafast, energy-efficient, and dynamic way.
The research group Smart Photonics investigates the application potential that comes with the rise of new programmable optical devices in combination with machine learning algorithms and nonlinear photonics. Through exploration and functionalization of novel nonlinear wave dynamics, the research group thrives for the exploration of new imaging and sensing solutions, new nonlinear states of light, and neuromorphic (brain-like) processor hardware. With this development at the interface of fundamental and applied sciences, the research group contributes to a global urge towards a new generation of autonomous microscopes, ultrafast sensors, and energy-saving optical processors for the medical diagnostics and green computing of the future.
Our research blends cutting-edge systems and concepts at the interdisciplinary interface of data science, physics, and biophotonics:
1. Adaptive fiber optics – In order to unlock the optical fiber as resource for fully fiber-integrated dynamically controllable systems, we work on packaged and fiber-connectorized, adaptive photonic devices based on novel waveguide designs and materials. In collaboration with other departments at Leibniz IPHT, we are able to cover the entire workflow, from design over fabrication to benchmarking, and to continuously develop new solutions with application-tailored properties.
2. Neuromorphic optical processors – We investigate new analog computing frameworks based on optical wave propagation and nonlinear wave dynamics with a focus on neuromorphic (brain-inspired) information processing. Our insights may not only extend our common understanding of artificial neural networks, but also contribute to the development of the next generation of eco-friendly, ultrafast neural engines for information processing.
3. Sensing and microscopy beyond human capabilities – As of today, optical diagnostics is a labor-intensive task that drags away time and creative focus of highly qualified medical personnel for repetitive routines. We investigate novel approaches to accelerate diagnostics through new smart sensing and microscopy devices, empowered by all-optical signal processing and learning-based algorithms.
To keep up our mission, we are continuously looking for highly motivated academic personnel (M.Sc., PhD, postdocs) from all disciplines of physics, engineering, computer science, and biochemistry to complement our interdisciplinary team. Do you have a strong sense of innovation, team play, good scientific practice and communication, do not hesitate to apply. We look forward to getting to know you.
Dr. Mario Chemnitz
Head of Department
Illustration of the nonlinear interaction between an incident light pulse and liquid molecules leading to a significant modification of optical solitons
- Adaptive and programmable optical fibers
- Multi-spectral fiber sensing and imaging
- Neuromorphic optical information processing
- Integrated nonlinear optofluidics
- Smart and autonomous control of optical systems
- Hybrid and multi-dimensional solitary waves
Areas of application
• Dynamically tailorable light sources
• Optical material characterization
• Combustion flame and gas-jet spectroscopy
• Semi-autonomous medical diagnostics
• Computer-free optical signal and pattern recognition