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

  • Pere Colet

    Pere Colet

  • Ingo Fischer

    Ingo Fischer

  • Damià Gomila

    Damià Gomila

  • Claudio Mirasso

    Claudio Mirasso

  • Roberta Zambrini

    Roberta Zambrini

  • Apostolos Argyris

    Apostolos Argyris

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 ...

Decaph

Dendrite-based Computation Applied to PHotonics systems

P.I.: Apostolos Argyris, Ingo Fischer, Claudio Mirasso
The DECAPH project addresses fundamental aspects of cognitive computing introducing a disruptive architecture that mimics in more detail the actual operations that are performed in the brain. By mimicking such neuron structures ...

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 ...

AIHUB

AIHUB

P.I.: Jose Javier Ramasco
HUB CSIC for fomenting the research and services on Artificial Intelligence.

Recent Publications

Non-Hermitian invisibility in tight-binding lattices

Longhi, Stefano; Pinotti, Ermanno
Physical Review B 106, 094205 (1-11) (2022)

Invisible non-Hermitian potentials in discrete-time photonic quantum walks

Longhi; Stefano
Optics Letters 47, 4091-4094 (2022)

Hacia la soberanía digital para sostener la sociedad futura

Zambrini, R; Rius, G.
CSIC Investiga 4: Sociedad Digital 4, 3-3 (2022)

Non-Hermitian skin effect and self-acceleration

Longhi; Stefano
Physical Review B 105, 245143 (1-13) (2022)

High-Performance Reservoir Computing With Fluctuations in Linear Networks

Nokkala, Johannes; Martínez-Peña, Rodrigo; Zambrini, Roberta; Soriano, Miguel C.
IEEE Transactions on Neural Networks and Learning Systems 33, 2664-2675 (2022)

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 ...

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