Summary
"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."
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."
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| Web resources: | https://cordis.europa.eu/project/id/101154320 |
| Start date: | 18-08-2025 |
| End date: | 17-08-2027 |
| Total budget - Public funding: | - 215 534,00 Euro |
Cordis data
Original description
"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."
Status
SIGNEDCall topic
HORIZON-MSCA-2023-PF-01-01Update Date
21-11-2024
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