120 GOPS Photonic tensor core in thin-film lithium niobate for inference and in situ training.

Photonics offers a transformative approach to artificial intelligence (AI) and neuromorphic computing by enabling low-latency, high-speed, and energy-efficient computations. However, conventional photonic tensor cores face significant challenges in constructing large-scale photonic neuromorphic networks. Here, we propose a fully integrated photonic tensor core, consisting of only two thin-film lithium niobate (TFLN) modulators, a III-V laser, and a charge-integration photoreceiver.

Reconfigurable quantum photonic circuits based on quantum dots.

Quantum photonic integrated circuits, composed of linear-optical elements, offer an efficient way for encoding and processing quantum information on-chip. At their core, these circuits rely on reconfigurable phase shifters, typically constructed from classical components such as thermo- or electro-optical materials, while quantum solid-state emitters such as quantum dots are limited to acting as single-photon sources. Here, we demonstrate the potential of quantum dots as reconfigurable phase shifters.

Physics to system-level modeling of silicon-organic-hybrid nanophotonic devices.

The continuous growth in data volume has sparked interest in silicon-organic-hybrid (SOH) nanophotonic devices integrated into silicon photonic integrated circuits (PICs). SOH devices offer improved speed and energy efficiency compared to silicon photonics devices. However, a comprehensive and accurate modeling methodology of SOH devices, such as modulators corroborating experimental results, is lacking.

Roadmapping the next generation of silicon photonics.

Silicon photonics has developed into a mainstream technology driven by advances in optical communications. The current generation has led to a proliferation of integrated photonic devices from thousands to millions-mainly in the form of communication transceivers for data centers. Products in many exciting applications, such as sensing and computing, are around the corner.

A system-on-chip microwave photonic processor solves dynamic RF interference in real time with picosecond latency.

Radio-frequency interference is a growing concern as wireless technology advances, with potentially life-threatening consequences like interference between radar altimeters and 5 G cellular networks. Mobile transceivers mix signals with varying ratios over time, posing challenges for conventional digital signal processing (DSP) due to its high latency. These challenges will worsen as future wireless technologies adopt higher carrier frequencies and data rates.

Real-time photonic blind interference cancellation.

mmWave devices can broadcast multiple spatially-separated data streams simultaneously in order to increase data transfer rates. Data transfer can, however, be compromised by interference. Photonic blind interference cancellation systems offer a power-efficient means of mitigating interference, but previous demonstrations of such systems have been limited by high latencies and the need for regular calibration.

Characterisation of Aberrant Metabolic Pathways in Hepatoblastoma Using Liquid Chromatography and Tandem Mass Spectrometry (LC-MS/MS).

Hepatoblastoma (HB) is a rare childhood tumour with an evolving molecular landscape. We present the first comprehensive metabolomic analysis using untargeted and targeted liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-MS/MS) of paired tumour and non-tumour surgical samples in HB patients ( = 8 pairs). This study demonstrates that the metabolomic landscape of HB is distinct from that of non-tumour (NT) liver tissue, with 35 differentially abundant metabolites mapping onto pathways such as fatty acid transport, glycolysis, the tricarboxylic acid (TCA) cycle, branched-chain amino acid degradation and glutathione synthesis.

Fully-integrated photonic tensor core for image convolutions.

Convolutions are one of the most critical signal and image processing operations. From spectral analysis to computer vision, convolutional filtering is often related to spatial information processing involving neighbourhood operations. As convolution operations are based around the product of two functions, vectors or matrices, dot products play a key role in the performance of such operations; for example, advanced image processing techniques require fast, dense matrix multiplications that typically take more than 90% of the computational capacity dedicated to solving convolutional neural networks.

Photonic online learning: a perspective.

Emerging neuromorphic hardware promises to solve certain problems faster and with higher energy efficiency than traditional computing by using physical processes that take place at the device level as the computational primitives in neural networks. While initial results in photonic neuromorphic hardware are very promising, such hardware requires programming or "training" that is often power-hungry and time-consuming. In this article, we examine the online learning paradigm, where the machinery for training is built deeply into the hardware itself.

Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation.

The expansion of telecommunications incurs increasingly severe crosstalk and interference, and a physical layer cognitive method, called blind source separation (BSS), can effectively address these issues. BSS requires minimal prior knowledge to recover signals from their mixtures, agnostic to the carrier frequency, signal format, and channel conditions. However, previous electronic implementations did not fulfil this versatility due to the inherently narrow bandwidth of radio-frequency (RF) components, the high energy consumption of digital signal processors (DSP), and their shared weaknesses of low scalability.

Towards a high-density photonic tensor core enabled by intensity-modulated microrings and photonic wire bonding.

We propose a photonic processing unit for high-density analog computation using intensity-modulation-based microring modulators (IM-MRMs). The output signal at the fixed resonance wavelength is directly intensity modulated by changing the extinction ratio (ER) of the IM-MRM . Thanks to the intensity-modulated approach, the proposed photonic processing unit is less sensitive to the inter-channel crosstalk.

Inducing optical self-pulsation by electrically tuning graphene on a silicon microring.

A mechanism for self-pulsation in a proposed graphene-on-silicon microring device is studied. The relevant nonlinear effects of two photon absorption, Kerr effect, saturable absorption, free carrier absorption, and dispersion are included in a coupled mode theory framework. We look at the electrical tunability of absorption and the Kerr effect in graphene.

Polymer modulators in silicon photonics: review and projections.

Optical modulators are vital for many applications, including telecommunication, data communication, optical computing, and microwave photonic links. A compact modulator with low voltage drive requirement, low power, high speed, and compatibility with CMOS foundry process is highly desirable. Current modulator technologies in Si suffer from trade-offs that constrain their power, performance (speed, drive voltage), and area.

Design automation of photonic resonator weights.

Neuromorphic photonic processors based on resonator weight banks are an emerging candidate technology for enabling modern artificial intelligence (AI) in high speed analog systems. These purpose-built analog devices implement vector multiplications with the physics of resonator devices, offering efficiency, latency, and throughput advantages over equivalent electronic circuits. Along with these advantages, however, often come the difficult challenges of compensation for fabrication variations and environmental disturbances.

Blind source separation with integrated photonics and reduced dimensional statistics.

Microwave communications have witnessed an incipient proliferation of multi-antenna and opportunistic technologies in the wake of an ever-growing demand for spectrum resources, while facing increasingly difficult network management over widespread channel interference and heterogeneous wireless broadcasting. Radio frequency (RF) blind source separation (BSS) is a powerful technique for demixing mixtures of unknown signals with minimal assumptions, but relies on frequency dependent RF electronics and prior knowledge of the target frequency band. We propose photonic BSS with unparalleled frequency agility supported by the tremendous bandwidths of photonic channels and devices.

Roadmap on emerging hardware and technology for machine learning.

Recent progress in artificial intelligence is largely attributed to the rapid development of machine learning, especially in the algorithm and neural network models. However, it is the performance of the hardware, in particular the energy efficiency of a computing system that sets the fundamental limit of the capability of machine learning. Data-centric computing requires a revolution in hardware systems, since traditional digital computers based on transistors and the von Neumann architecture were not purposely designed for neuromorphic computing.

Dichloroacetate prevents TGFβ-induced epithelial-mesenchymal transition of retinal pigment epithelial cells.

Proliferative retinopathies are associated with formation of fibrous epiretinal membranes. At present, there is no pharmacological intervention for the treatment of retinopathies. Cytokines such as TGFβ are elevated in the vitreous humor of the patients with proliferative vitro-retinopathy, diabetic retinopathy and age-related macular degeneration.

Lateral bipolar junction transistor on a silicon photonics platform.

Integration of active electronics into photonic systems is necessary for large-scale photonic integration. While heterogeneous integration leverages high-performance electronics, a monolithic scheme can coexist by aiding the electronic processing, improving overall efficiency. We report a lateral bipolar junction transistor on a commercial silicon photonics foundry process.

Photonic independent component analysis using an on-chip microring weight bank.

Independent component analysis (ICA) is a general-purpose technique for analyzing multi-dimensional data to reveal the underlying hidden factors that are maximally independent from each other. We report the first photonic ICA on mixtures of unknown signals by employing an on-chip microring (MRR) weight bank. The MRR weight bank performs so-called weighted addition (i.

Domestically Acquired Virus Causing Hemophagocytic Lymphohistiocytosis-Washington, DC, 2018.

(SEOV) infections, uncommonly reported in the United States, often result in mild illness. We report a case of hemophagocytic lymphohistiocytosis secondary to SEOV infection that was domestically acquired in Washington, DC.

Photonic principal component analysis using an on-chip microring weight bank.

Photonic principal component analysis (PCA) enables high-performance dimensionality reduction in wideband analog systems. In this paper, we report a photonic PCA approach using an on-chip microring (MRR) weight bank to perform weighted addition operations on correlated wavelength-division multiplexed (WDM) inputs. We are able to configure the MRR weight bank with record-high accuracy and precision, and generate multi-channel correlated input signals in a controllable manner.

Neuromorphic photonics with electro-absorption modulators.

Photonic neural networks benefit from both the high-channel capacity and the wave nature of light acting as an effective weighting mechanism through linear optics. Incorporating a nonlinear activation function by using active integrated photonic components allows neural networks with multiple layers to be built monolithically, eliminating the need for energy and latency costs due to external conversion. Interferometer-based modulators, while popular in communications, have been shown to require more area than absorption-based modulators, resulting in a reduced neural network density.

Feedback control for microring weight banks.

Microring weight banks present novel opportunities for reconfigurable, high-performance analog signal processing in photonics. Controlling microring filter response is a challenge due to fabrication variations and thermal sensitivity. Prior work showed continuous weight control of multiple wavelength-division multiplexed signals in a bank of microrings based on calibration and feedforward control.

Clinical and microbiological profile of infections during induction phase of acute myeloid leukemia.

Background: The primary objective of this study is to describe clinical and microbiological profile of infections during induction phase of acute myeloid leukemia (AML).

Patients And Methods: We reviewed the case records of 50 hospitalized patients with AML undergoing standard dose induction chemotherapy from January to December 2015.

Results: Out of 50 cases, 34 were males 16 females with median age of 30 years.

Simultaneous excitatory and inhibitory dynamics in an excitable laser.

Neocortical systems encode information in electrochemical spike timings, not just mean firing rates. Learning and memory in networks of spiking neurons is achieved by the precise timing of action potentials that induces synaptic strengthening (with excitation) or weakening (with inhibition). Inhibition should be incorporated into brain-inspired spike processing in the optical domain to enhance its information-processing capability.