From the 1 of 15 linked papers with an AI index.
14 papers · 1 filter
Spiking Photonic Neurons Based on Two-Section InP Quantum-Well Lasers Integrated on Silicon
Menelaos Skontranis, Benoit Charbonnier, Olivier Girard +2
The paper experimentally demonstrates that two-section InP quantum-well lasers integrated on silicon can exhibit neuronal-like spiking behaviors such as integrate-and-fire and reso…
Per-Span Microwave Frequency Fiber Interferometry in Subsea Cables for Scalable Deep-Ocean Geophysical Monitoring
Georgios Aias Karydis, Nicolas L. Celli, David Craig +6
We demonstrate low-cost microwave frequency fibre interferometry for per-span monitoring of a 1,770 km operational subsea cable connecting Ireland and Iceland. Over four months, th…
Quantum-Secure Physical Unclonable Function enabled by Silicon Photonics Integrated Circuits
G. Sarantoglou, N. Tzekas, G. Moustakas +8
Physical Unclonable Functions (PUFs) are hardware security primitives whose inherent physical complexity can be exploited for secure authentication and cryptographic key generation…
Experimental Analysis of a Self-Coherent M-QAM Receiver by Means of Recurrent Optical Spectrum Slicing and Direct Detection
Kostas Sozos, Francesco Da Ros, Senior Member Optica +6
High order modulation formats constitute the most prominent way for increasing spectral efficiency in transmission systems. Coherent transceivers that support such higher order for…
High-Speed Non-Volatile Barium Titanate Field Programmable Photonic Gate Array
Cristina Catalá-Lahoz, Jose Roberto Rausell-Campo, Daniel Pérez-López +10
Programmable integrated photonics aims to replicate the versatility of field-programmable gate arrays in the optical domain. However, scaling these systems has been prevented by th…
Programmable Optical Spectrum Shapers as Computing Primitives for Accelerating Convolutional Neural Networks
Georgios Moustakas, Adonis Bogris, Charis Mesaritakis
Photonic convolutional accelerators have emerged as low-energy alternatives to power-demanding digital convolutional neural networks, though they often face limitations in scalabil…