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 ...
INFOLANET
Information processing with coupled laser networks
P.I.: Apostolos Argyris, Miguel C. Soriano
In the INFOLANET project, we will combine the expertise of the PIs on dynamical systems and machine learning to advance information processing concepts, based on a high-speed photonic implementation. We anticipate that ...
Recent Publications
Complex Optical Networks based on Vertical-Cavity Surface-Emitting Lasers (VCSELs)
Pflüger, MoritzPhD Thesis (2023)
Non-Hermitian control of localization in mosaic photonic lattices
Longhi; StefanoApplied Physics Letters 123, 161102 (2023)
Time and wavelength multiplexing in photonic neural networks
Jiménez González, Pedro (advisors: Miguel C. Soriano, Claudio R. Mirasso)Master Thesis (2023)
Delocalization of light in photonic lattices with unbounded potentials
Longhi; StefanoOptics Letters 48, 5293-5296 (2023)
Exploiting oscillatory dynamics of delay systems for reservoir computing
Goldmann, Mirko; Fischer, Ingo ; Mirasso, Claudio R.; Soriano, Miguel C. Chaos 33, 093139 (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 ...