Distortion-free amplification of 100†GHz mode-locked optical frequency comb using quantum dot technology.

Semiconductor mode-locked optical frequency comb (ML-OFC) sources with extremely high repetition rates are central to many high-frequency applications, such as dense wavelength-division multiplexing. Dealing with distortion-free amplification of ultra-fast pulse trains from such ML-OFC sources in high-speed data transmission networks requires the deployment of semiconductor optical amplifiers (SOAs) with ultrafast gain recovery dynamics. Quantum dot (QD) technology now lies at the heart of many photonic devices/systems owing to their unique properties at the O-band, including low alpha factor, broad gain spectrum, ultrafast gain dynamics, and pattern-effect free amplification. In this swork, we report on ultrafast and pattern-free amplification of ∼100 GHz pulsed trains from a passively ML-OFC and up to 80 Gbaud/s non-return-to-zero (NRZ) data transmission using an SOA. Most significantly, both key photonic devices presented in this work are fabricated from identical InAs/GaAs QD materials operating at O-band, which paves the way for future advanced photonic chips, where ML-OFCs could be monolithically integrated with SOAs and other photonic components, all originated from the same QD-based epi-wafer.

Information Fragmentation, Encryption and Information Flow in Complex Biological Networks.

Assessing where and how information is stored in biological networks (such as neuronal and genetic networks) is a central task both in neuroscience and in molecular genetics, but most available tools focus on the network's structure as opposed to its function. Here, we introduce a new information-theoretic tool-information fragmentation analysis-that, given full phenotypic data, allows us to localize information in complex networks, determine how fragmented (across multiple nodes of the network) the information is, and assess the level of encryption of that information. Using information fragmentation matrices we can also create information flow graphs that illustrate how information propagates through these networks. We illustrate the use of this tool by analyzing how artificial brains that evolved in silico solve particular tasks, and show how information fragmentation analysis provides deeper insights into how these brains process information and "think". The measures of information fragmentation and encryption that result from our methods also quantify complexity of information processing in these networks and how this processing complexity differs between primary exposure to sensory data (early in the lifetime) and later routine processing.

Electrically pumped continuous-wave O-band quantum-dot superluminescent diode on silicon.

High-power, broadband quantum-dot (QD) superluminescent diodes (SLDs) are ideal light sources for optical coherence tomography (OCT) imaging systems but have previously mainly been fabricated on native GaAs- or InP-based substrates. Recently, significant progress has been made to emigrate QD SLDs from native substrates to silicon substrates. Here, we demonstrate electrically pumped continuous-wave InAs QD SLDs monolithically grown on silicon substrates with significantly improved performance thanks to the achievement of a low density of defects in the III-V epilayers. The fabricated narrow-ridge-waveguide device exhibits a maximum 3 dB bandwidth of 103 nm emission spectrum centered at the O-band together with a maximum single facet output power of 3.8 mW at room temperature. The silicon-based SLD has been assessed for application in an OCT system. Under optimized conditions, a predicted axial resolution of ∼5.3µm is achieved with a corresponding output power of 0.66 mW/facet.