Project description
Novel reconfigurable broadband high-power light source overcomes current barriers
Photonics research is increasingly focused on novel ways to control the spatiotemporal properties of light by leveraging complex non-linear optical processes. Broadband light sources with on-demand characteristics in the spectral, temporal and spatial domains augment the possibilities with their multidimensional complexity. However, the utility of these sources is challenged by their low output power density and limited reconfigurability. With the support of the Marie Skłodowska-Curie Actions programme, the TOGETHER project aims to harness this potential by exploiting complex non-linear dynamics in multimode fibres together with machine learning approaches. Together, they will support development of an on-demand, structured broadband high-power light source overcoming current barriers.
Objective
"Complex nonlinear optical processes have been increasingly used for the smart photonic system to meet demands of advanced light source development for numerous applications. Current flagship techniques are still restricted, lacking flexibility of the light excitation in terms of controlled spatio-temporal properties. For instance, available laser sources have only a few degrees of freedom for versatile pulse shaping and tunable wavelength emission due to narrow bandwidth of a laser gain medium. Conversely, a wide range of applications benefits from broadband light sources with on-demand characteristics in the spectral, temporal, and spatial domains. However, available broadband sources are restricted by low output power density and limited reconfigurability. Therefore, versatile, efficient, and practical light sources are necessary to motivate development of paramount applications including microscopy and metrology techniques.
In this context, the TOGETHER project aims to develop an on-demand structured broadband high-power light source relying on the advantages of complex nonlinear dynamics in multimode fibers along with machine learning approaches to efficiently harness such multidimensional complexity. In particular, rich landscapes of nonlinear dynamics in multimode fibers will be leveraged for ""on-the-fly"" control of nonlinear propagation. In parallel, machine learning based on artificial neural networks will be employed to speed-up typically time-consuming simulations and optimize the process of supercontinuum generation in multimode fibers. Specifically, we aim to optimize broadband sources in terms of power spectral intensity and spatial shapes. The developed sources will be used to enhance the selectivity and signal of multiphoton microscopy via near-infrared excitation, while the extension of supercontinuum generation into the mid-infrared range will also be investigated via non-silica multimode fibers towards applications in molecular spectroscopy."
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologymaterials engineeringfibers
- natural sciencesphysical sciencesopticsmicroscopy
- natural sciencesphysical sciencesopticslaser physics
- natural sciencesphysical sciencesopticsspectroscopy
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Keywords
Programme(s)
- HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA) Main Programme
Funding Scheme
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European FellowshipsCoordinator
33100 Tampere
Finland