RESEARCH UNIT ON NEUROMORPHIC COMPUTING AND PHOTONICS (RNCP)
Optical communication systems suffer from linear and nonlinear effects of the optical channel. Although modern ASICs can handle linear effects such as polarization mode dispersion and chromatic dispersion, the major limitation regarding the maximum capacity that can be achieved comes from the nonlinearities attributed to Kerr effect. RCNP investigates state of the art recursive neural networks and reservoir computing techniques so as to mitigate the nonlinear effects in long-haul WDM transmission systems. The same activity seeks for applying low complexity machine learning algorithms in short-area networks where consumption matters.
One of the key areas that MCP has invested is the envision-design and development of cryptographic devices based on electronic-photonics hardware for cyber-physical applications. In particular MCP has developed multiple designs of optical modules as non-replicable authentication tokens and secure pseudo-random generators able to be integrated in IoT ecosystems and solidifying their resilience against cyber-physical attacks. More importantly MCP is working towards combining its solid background on neuromoprhic engineering and crypto-systems, so as to spawn a new generation of electronic-photonic neuro-cryptographic devices able to offer a twofold advantage. On one hand, provide solid security features, such as data encryption and authentication, based on physical properties and secondly employ the same modules for anomaly detection and edge machine learning