Principles of Neuromorphic Photonics

In an age overrun with information, the ability to process reams of data has become crucial. The demand for data will continue to grow as smart gadgets multiply and become increasingly integrated into our daily lives. Next-generation industries in artificial intelligence services and high-performance computing are so far supported by microelectronic platforms. These data-intensive enterprises rely on continual improvements in hardware. Their prospects are running up against a stark reality: conventional one-size-fits-all solutions offered by digital electronics can no longer satisfy this need, as Moore's law (exponential hardware scaling), interconnection density, and the von Neumann architecture reach their limits. With its superior speed and reconfigurability, analog photonics can provide some relief to these problems; however, complex applications of analog photonics have remained largely unexplored due to the absence of a robust photonic integration industry. Recently, the landscape for commercially-manufacturable photonic chips has been changing rapidly and now promises to achieve economies of scale previously enjoyed solely by microelectronics. The scientific community has set out to build bridges between the domains of photonic device physics and neural networks, giving rise to the field of \emph{neuromorphic photonics}. This article reviews the recent progress in integrated neuromorphic photonics. We provide an overview of neuromorphic computing, discuss the associated technology (microelectronic and photonic) platforms and compare their metric performance. We discuss photonic neural network approaches and challenges for integrated neuromorphic photonic processors while providing an in-depth description of photonic neurons and a candidate interconnection architecture. We conclude with a future outlook of neuro-inspired photonic processing.Comment: 28 pages, 19 figure

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 5G 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. However, conventional DSPs, already on the brink of their clock frequency limit, are expected to offer only marginal speed advancements. This paper introduces a photonic processor to address dynamic interference through blind source separation (BSS). Our system-on-chip processor employs a fully integrated photonic signal pathway in the analogue domain, enabling rapid demixing of received mixtures and recovering the signal-of-interest in under 15 picoseconds. This reduction in latency surpasses electronic counterparts by more than three orders of magnitude. To complement the photonic processor, electronic peripherals based on field-programmable gate array (FPGA) assess the effectiveness of demixing and continuously update demixing weights at a rate of up to 305 Hz. This compact setup features precise dithering weight control, impedance-controlled circuit board and optical fibre packaging, suitable for handheld and mobile scenarios. We experimentally demonstrate the processor's ability to suppress transmission errors and maintain signal-to-noise ratios in two scenarios, radar altimeters and mobile communications. This work pioneers the real-time adaptability of integrated silicon photonics, enabling online learning and weight adjustments, and showcasing practical operational applications for photonic processing

Glycerine associated molecules with herbicide for controlling Adenocalymma peregrinum in cultivated pastures

The weed Adenocalymma peregrinum that is popularly known in Brazil as “ciganinha”, belongs to the family Bignoniaceae. The only way to control this plant species in crop fields is by the application of herbicides on the stump or directly on the stem. The present study aimed to analyze the effect of glycerine in controlling A. peregrinum (MIERS) L.G.Lohmann when applied on the stem. The glycerin used as a spray application of herbicide, underwent pre-purification processes with different concentrations of phosphoric acid (85%) and was characterized for water content, sulphated ash, total glycerol, matter organic non-glycerol (MONG), methanol and pH. For the analysis of the chemical composition of the stem lignin, holocellulose, extractives, calorific value and elementary quantitative determination of C, N, H, S were determined, as well as the total content of oxygen from the stem. The field work was installed at the town of Alvorada-TO, following the randomized complete block design with six treatments and four replications. Results show that the stem of A. peregrinum contains a significant amount of nitrogen, compared to other species, and high lignin content which makes it the most resistant species. The use of glycerin combined to the herbicide (picloram and triclopyr), was not efficient when compared to diesel oil. It was observed that the glycerin has potential as a vehicle for applying herbicides, leaving much to the development of new studies to make changes in its physicalchemical characteristics.Key words: Weeds, pastures, management, Adenocalymma peregrinum