Daten zum Projekt

Neuromorphic Computing using QD-Networks (NeuroQNet)

Zur Projekt-Website

Initiative: Integration molekularer Komponenten in funktionale makroskopische Systeme (beendet, nur noch Fortsetzungsanträge)
Bewilligung: 02.12.2015
Laufzeit: 3 Jahre


The goal of this project is to develop a new nanophotonics based platform for neuro-inspired information processing. Dense arrays of semiconductor microlasers and single photon sources with quantum dots in the active layer will take a role comparable to neurons in the brain. Neuron-connectivity is being established via diffractive coupling by an external spatial light modulator. Similar to the brain's primary sensory cortex, computation is provided by induced macroscopic network-dynamics, which allows for efficient information processing with diverse applications such as pattern classification, nonlinear prediction and ultra-fast control loops. A particularly attractive aspect of the scheme is that it merges the inherently parallel concepts of reservoir computing and photonics within a compact and scalable physical machine learning implementation. As such, an ultra-fast (GHz bandwidth) and versatile platform complementary to recent large-scale electronic approaches (e.g. human brain project, IBM or Google) will be developed.


  • Prof. Dr. Stephan Reitzenstein

    Technische Universität Berlin
    Fakultät II
    Institut für Festkörperphysik
    Sekretariat EW 5-3

  • Daniel Brunner, Ph.D.

    CNRS - Centre National de la Recherche
    Département d'Optique
    Institut FEMTO-ST
    UMR CNRS 6174
    Office N1-BUR-04
    Besancon (cedex)

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