Miguel C. Soriano

Miguel Cornelles Soriano
Perfil
Miguel C. Soriano (Miguel Cornelles Soriano) holds a "Ramón y Cajal" research position at the Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC). His research line covers the topics of information processing based on reservoir computing and nonlinear dynamics. His main research interests also include the experimental and numerical study of semiconductor lasers subject to delayed-coupling and the synchronization of chaotic oscillators.

Publicacions recents

Opportunities in Quantum Reservoir Computing and Extreme Learning Machines

Mujal, Pere; Martínez-Peña, Rodrigo; Nokkala, Johannes; García-Beni, Jorge; Giorgi, Gian Luca; Soriano, Miguel C.; Zambrini, Roberta
Advanced Quantum Technologies , 2100027 (2021)

Unveiling the role of plasticity rules in reservoir computing

Morales, Guillermo B.; Mirasso, Claudio R.; Soriano, Miguel C.
Neurocomputing , (2021)

Gaussian states of continuous-variable quantum systems provide universal and versatile reservoir computing

Nokkala, Johannes;Martínez-Peña, Rodrigo;Giorgi, Gian Luca; Parigi, Valentina;Soriano, Miguel C.;Zambrini, Roberta
Communications Physics 4, 53 (2021)

Dynamical phase transitions in quantum reservoir computing

Martínez-Peña, Rodrigo; Giorgi, Gian Luca; Nokkala, Johannes; Soriano, Miguel C.; Zambrini, Roberta
Submitted (2021)

Influence of Measurements on Continuous Variable Quantum Reservoir Computing

García Beni, Jorge (Advisors: Miguel C. Soriano and Roberta Zambrini)
Master Thesis (2021)

Projectes de recerca recents i vigents

POST-DIGITAL

POST-DIGITAL: Neuromorphic computing in photonic and other nonlinear media

I.P.: 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

I.P.: 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

I.P.: 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 ...

QUAREC

Machine learning with quantum reservoir computing

I.P.: Roberta Zambrini
Project funded by the government of the Balearic Islands with the goal of extending Reservoir Computing into the quantum domain. The project is mainly theoretical/numerical, but also deals with the identification of ...

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