Nonlinear Photonics
Within this line of research, we explore complex phenomena in photonics,filling the gap between Modern Photonic Sources and Functional Complex Systems. Our Nonlinear Photonics Lab, working alongside a strong theoretical team, aims to gain an in-depth understanding of complex phenomena and to provide novel solutions from communication to information processing, transferring knowledge to the Information and Communication Technologies (ICT) domain.
We study nonlinear and spatio-temporal emission properties of semiconductor lasers, implement optical complex networks based on lasers, advance characterization techniques, and demonstrate the utility of optical complexity for information technologies including encryption and ultra-fast neuro-inspired photonic information processing.
Researchers
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Apostolos Argyris
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Pere Colet
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Miguel C. Soriano
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Ingo Fischer
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Damià Gomila
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Claudio Mirasso
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Roberta Zambrini
Recent and ongoing Research projects
POST-DIGITAL
POST-DIGITAL: Neuromorphic computing in photonic and other nonlinear media
P.I.: Ingo Fischer, Claudio Mirasso
POST-DIGITAL is a Marie Skłodowska-Curie Innovative Training Network, funded by the European Union’s Horizon 2020 research and innovation programme. POST-DIGITAL is committed to form a new generation of engineers and researchers, affording ...
ADOPD
Adaptive Optical Dendrites
P.I.: Ingo Fischer, Claudio Mirasso
The increased demand for computation with low energy consumption requires entirely novel hardware concepts. In ADOPD we develop ultra-fast computational units based on optical-fiber technologies exploiting information processing principles used by neurons ...
QuaResC
Quantum machine learning using reservoir computing
P.I.: Miguel C. Soriano, Roberta Zambrini
The QuaResC project engages in a new collaboration UIB and CSIC researchers at IFISC with the objective to address an interdisciplinary topic between artificial intelligence and quantum physics: quantum machine learning using ...
MdM-IFISC-2
Maria de Maeztu 2023-2026
P.I.: Ernesto Estrada, Ingo Fischer, Emilio Hernández-García, Rosa Lopez, Víctor M. Eguíluz, Claudio Mirasso, Jose Javier Ramasco, Raúl Toral, Roberta Zambrini
After 15 years of its existence, IFISC can point to a proven track record of impactful research. The previous 2018-2022 MdM award has significantly enhanced the institute's capabilities, as demonstrated by an ...
Recent Publications
Integrated programmable spectral filter for frequency-multiplexed neuromorphic computers
Jonuzi, Tigers; Lupo, Alessandro; Soriano, Miguel C.; Massar, Serge; Doménech, J. D. Optics Express 31, 19255-19265 (2023)
Experimental demonstration of bandwidth enhancement in photonic time delay reservoir computing
Estébanez, Irene; Argyris, Apostolos; Fischer, IngoOptics Letters 48 (9), 2449-2452 (2023)
Neural network learning with photonics and for photonic circuit design
Brunner, D.; Soriano, M. C.; Fan, S. Nanophotonics 12, 773-775 (2023)
Implementation of input correlation learning with an optoelectronic dendritic unit
Ortín, Silvia; Soriano, Miguel Cornelles; Tetzlaff, Christian; Wörgötter, Florentin; Fischer, Ingo; Mirasso, Claudio Rubén.; Argyris, ApostolosFrontiers in Physics 11, 1112295 (1-11) (2023)
Injection locking and coupling large VCSEL arrays via diffraction in an external cavity
Pflüger, Moritz; Brunner, Daniel; Heuser, Tobias; Lott, James A.; Reitzenstein, Stephan; Fischer, IngoOptics Express 31, 8704-8713 (2023)
Related News
Boosting the output power of lasers by breaking their symmetry
Nov. 11, 2021
More uniform light intensity profiles are possible in
large-aperture semiconductor lasers if the optical aperture is intentionally
deformed. An international team from Łodz University of Technology, Institute
of Microelectronics and Photonics in Warsaw, Technical University of Berlin,
and IFISC (UIB-CSIC ...
Deep Neural Networks using a single neuron
Sept. 14, 2021
Deep Neural Networks (DNNs) are a useful
tool for a wide range of tasks such as image classification, object detection,
image resizing or text generation. They are extremely powerful, but they
require sufficient computing power and large data sets to ...