000344442 001__ 344442
000344442 005__ 20230827173501.0
000344442 0247_ $$2CORDIS$$aG:(EU-Grant)101046329$$d101046329
000344442 0247_ $$2CORDIS$$aG:(EU-Call)HORIZON-EIC-2021-PATHFINDEROPEN-01$$dHORIZON-EIC-2021-PATHFINDEROPEN-01
000344442 0247_ $$2originalID$$acorda_____he::101046329
000344442 035__ $$aG:(EU-Grant)101046329
000344442 150__ $$aNeuromorphic computing Enabled by Heavily doped semiconductor Optics$$y2023-01-01 - 2025-12-31
000344442 372__ $$aHORIZON-EIC-2021-PATHFINDEROPEN-01$$s2023-01-01$$t2025-12-31
000344442 450__ $$aNEHO$$wd$$y2023-01-01 - 2025-12-31
000344442 5101_ $$0I:(DE-588b)5098525-5$$2CORDIS$$aEuropean Union
000344442 680__ $$aNEHO will develop a novel photonic integrated circuit platform that enables ultrafast and low-energy consumption neuromorphic information processes by means of a newly developed nonlinear photon-plasmon semiconductor technology at mid-infrared wavelengths (8-12 μm). NEHO vision will be achieved by unconventional use of semiconductors to optimize and control plasmonic effects that will provide the optical nonlinearity required to implement the functionalities of an artificial neuron. NEHO's optical neuron will be the building block for the realization of ultrafast optical neural networks.  We will combine the flexibility of field-effect devices realized on semiconductors with the nanoscale nature of plasmonic processes so to enable the reconfigurability of the nonlinear optical coefficient at each node of the network, simply obtained by controlling DC electric potential levels. At the heart of NEHO is the idea of exploiting the rich electron dynamics of semiconductors. Doped semiconductors undergo an interesting transition from the size-quantization regime to the classical regime of plasmon oscillations. This transition region can exhibit strong nonlocal and nonlinear optical response due to a large variety of electron-electron interactions. The decrease in electron density induced on the semiconductor surface by an external bias can be used to modulate the nonlinear response strength. This unprecedented feature will be used to leverage the hardware implementation of a neural network into the development of new machine learning optimization techniques, including the optimization of the nonlinear activation function to different tasks. This extra degree of freedom will offer tremendous benefits for a large variety of machine learning applications.
000344442 909CO $$ooai:juser.fz-juelich.de:1013802$$pauthority:GRANT$$pauthority
000344442 909CO $$ooai:juser.fz-juelich.de:1013802
000344442 980__ $$aG
000344442 980__ $$aCORDIS
000344442 980__ $$aAUTHORITY