TOM 1 - Silicon Photonics and Guided-Wave Optics
TOM 2 - Computational, Adaptive and Freeform Optics
TOM 3 - Optical System Design, Tolerancing and Manufacturing
TOM 4 - Bio-Medical Optics
TOM 5 - Resonant Nanophotonics
TOM 6 - Optical Materials: crystals, thin films, organic molecules & polymers, syntheses, characterization and applications
TOM 7 - Thermal radiation and energy management
TOM 8 - Non-linear and Quantum Optics
TOM 9 - Opto-electronic Nanotechnologies and Complex Systems
TOM 10 - Frontiers in Optical Metrology
TOM 11 - Tapered optical fibers, from fundamental to applications
TOM 12 - Optofluidics
TOM 13 - Advances and Applications of Optics and Photonics
EU Project Session
Early Stage Researcher Session
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Please note that all times are shown in the time zone of the conference. The current conference time is: 3rd Dec 2022, 04:30:57pm WET
TOM2 S03: Computational, Adaptive and Freeform Optics - focus on Illumination, AR/VR and information driven systems: Applications
4:30pm - 6:00pm
Session Chair: Andrew Robert Harvey, University of Glasgow, United Kingdom
1st floor, 70 seats
4:30pm - 5:00pm Invited ID: 339 / TOM2 S03: 1 TOM 2 Computational, Adaptive and Freeform Optics - focus on Illumination, AR/VR and information driven systems
Fiber endoscope using 3D printed diffractive optical elements for minimally invasive sensing and actuation in biomedicine
Technische Universität Dresden, Germany
Minimally invasive fiber endoscopes are crucial for several applications. The memory effect of coherent fiber bundles is exploited with a diffractive optical element (DOE), printed on the fiber facet by 2-photon polymerization lithography. Results on 3D imaging without mechanical scanning will be presented.
5:00pm - 5:15pm ID: 288 / TOM2 S03: 2 TOM 2 Computational, Adaptive and Freeform Optics - focus on Illumination, AR/VR and information driven systems
Modelling dynamic 3D heat transfer in laser material processing based on physics informed neural networks
Jorrit Voigt, Michael Moeckel
University of Applied Sciences Aschaffenburg, Germany
Machine learning algorithms make predictions by fitting highly parameterized nonlinear functions to massive amounts of data. Yet those models are not necessarily consistent with physical laws and offer limited interpretability. Extending machine learning models by introducing scientific knowledge in the optimization problem is known as physics-based and data-driven modelling. A promising development are physics informed neural networks (PINN) which ensure consistency to both physical laws and measured data. The aim of this research is to model the time-dependent temperature profile in bulk materials following the passage of a moving laser focus by a PINN. The results from the PINN agree essentially with finite element simulations, proving the suitability of the approach. New perspectives for applications in laser material processing arise when PINNs are integrated in monitoring systems or used for model predictive control.
5:15pm - 5:30pm ID: 345 / TOM2 S03: 3 TOM 2 Computational, Adaptive and Freeform Optics - focus on Illumination, AR/VR and information driven systems
Sparse mid-infrared spectra enable real-time and in-vivo applications in tissue discrimination
Felix Fischer, Karsten Frenner, Alois M. Herkommer
Institute of Applied Optics, University of Stuttgart, 70569 Stuttgart, Germany
Differentiation of malign and benign tissue based on spectral information can be done by only using a small fractional amount of the original mid-infrared spectrum. An optimally selected arrangement of a few narrow-band quantum cascade lasers provides proficient signal-to-noise ratios and can drastically reduce the data acquisition time with constant discriminability, such that real-time applications will be possible in short-term and in-vivo diagnostics in the long-term.
5:30pm - 5:45pm ID: 390 / TOM2 S03: 4 TOM 2 Computational, Adaptive and Freeform Optics - focus on Illumination, AR/VR and information driven systems
Synthetic wavelength holography in scattering media
University of Stuttgart, Germany
Coherent detection enables the acquisition of amplitude and phase of optical fields. We use the synthetic wavelength as a computational construct arising from digital processing of two off-axis digital holograms to identify the structure of an object obscured by fog and further increase the imaging range due to the increased sensitivity in coherent detection. Experiments were carried out in a 27 m long fog tube filled with ultrasonically generated fog. Furthermore, we transfer the findings of this work to address the phase distortions in imaging through coherent fiber bundles (CFBs), which could enable distal shape measurement with ultrathin holographic endoscopy.