The identification of neuromorphic computing as a highly promising alternative computing system has been emerged from its potential to increase rapidly the computational efficiency that is currently restricted by Moore’s law end. First electronic neuromorphic chips like IBM’s TrueNorth and Intel’s Loihi revealed a tremendous performance improvement in terms of computational speed and density; however, they are still operating in MHz rates. To this end, neuromorphic photonic integrated circuits can further increase the computational speed and density, having a large portfolio of components with GHz-bandwidth and low-energy. Herein, we present an all-optical sigmoid activation function as well as a single-λ linear neuron. The all-optical sigmoid activation function comprises a Semiconductor Optical Amplifier-Mach-Zehnder Interferometer (SOA-MZI) configured in differentially-biased scheme followed by an SOA. Its thresholding capabilities have been experimentally demonstrated with 100psec optical pulses. Then, we introduce an all-optical phase-encoded weighting scheme and we experimentally demonstrate its linear algebra operational credentials by the means of a typical IQ modulator operated at 10Gbaud/s.
NON-SPIE: Fundamentals of Physics 1
This course is designed to be an introduction to the fundamental laws of kinematics, dinamics, mechanical waves and oscillatory motion.
Throughout this course stundents are introduced to the fundamental laws of the light propagation, basic optical elements, flud mechanics, heat transfer and thermodynamics, as well as elements of modern physics: quantum, atomic and nuclear physics.
The main goal of this course is to encourage students to build mathematical models of some more advanced and complex physical problems that play an important role in the field of contemporary electrical engineering.
In this course students are introduced to the fundamentals of optical information transfer methods which are in the foundations of the recent generations of modern high bit-rate communication networks.