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DELIVERABLES

Deliverable No
Deliverable Name
Dissemination Level

D1.1

Report on suitability of existing methods for learning (backpropagation-free) in physical systems
SEN

D1.2

DRAFT Report on novel approaches to learning in photonic systems (demo implementations in simulation)
SEN

D1.3

FINALISED Report on novel approaches to learning in photonic systems (demo implementations in simulation)
PU

D1.4

Report on demo implementations of novel learning concepts in physical systems
SEN

D2.1

Report on characterization of photonic implementations for information processing.
SEN

D2.2

Report on fully trained deep laser NN for communication reconditioning and transduction
SEN

D2.3

Report on channel equalization for optical communication systems
PU

D2.4

Information processing using cavity solitons and spatio-temporal systems
SEN

D3.1

DRAFT Report on initial prototype of integrated neuromorphic systems
SEN

D3.2

FINALISED Report on initial prototype of integrated neuromorphic systems
SEN

D3.3

Report on the integrated photonic solutions for optical channel equalisation and neuromorphic information processing
SEN

D3.4

Report on optical accelerator applications
SEN

D4.1

Report on demonstration of telecom applications on optimised integrated neuromorphic system
SEN

D4.2

Experimental of photon demonstration inc learning augmented real-time imaging with 10 to the 8 frames/s
SEN

D4.3

Report on benchmarking of neuromorphic photonic information processing with respect to speed, energy consumption, footprint
SEN

D5.1

Carrer development plans
SEN

D5.2

Interim report on training completed by all DCs
PU

D5.3

Final report on training completed by all DCs
PU

D6.1

Project Website
PU

D6.2

Initial Plan for the dissemination and exploitation of results including communication activities
SEN

D6.3

Final Plan for the dissemination and exploitation of results, including communication activities
SEN

D7.1

Supervisory Board of the Network
SEN

D7.2

Progress Report
SEN

D7.3

Data Management Plan
SEN
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This Project is fully funded by the European Union Horizon Europe research and innovation programme under the Marie Skłodowska-Curie Grant Agreement 101169118 HORIZON-MSCA-2023-DN-01-01

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