ARC Centre of Excellence for Transformative Meta-Optical Systems

Coherent optical orthogonal frequency division multiplexing is proposed to combat dispersion in optical media. It is shown that optical-signal-to-noise ratio penalty at 10 Gbit/s is maintained below 2 dB for 3000 km transmission of standard-singlemode fibre without dispersion compensation.

Summary Much of humanity relies on rice ( Oryza sativa ) as a food source, but cultivation is water intensive and the crop is vulnerable to drought and high temperatures. Under climate change, periods of reduced water availability and high temperature are expected to become more frequent, leading to detrimental effects on rice yields. We engineered the high‐yielding rice cultivar ‘ IR 64’ to produce fewer stomata by manipulating the level of a developmental signal. We overexpressed the rice epidermal patterning factor Os EPF 1 , creating plants with substantially reduced stomatal density and correspondingly low stomatal conductance. Low stomatal density rice lines were more able to conserve water, using c . 60% of the normal amount between weeks 4 and 5 post germination. When grown at elevated atmospheric CO 2 , rice plants with low stomatal density were able to maintain their stomatal conductance and survive drought and high temperature (40°C) for longer than control plants. Low stomatal density rice gave equivalent or even improved yields, despite a reduced rate of photosynthesis in some conditions. Rice plants with fewer stomata are drought tolerant and more conservative in their water use, and they should perform better in the future when climate change is expected to threaten food security.

This paper presents an analysis of optical buffers based on slow-light optical delay lines. The focus of this paper is on slow-light delay lines in which the group velocity is reduced using linear processes, including electromagnetically induced transparency (EIT), population oscillations (POs), and microresonator-based photonic-crystal (PC) filters. We also consider slow-light delay lines in which the group velocity is reduced by an adiabatic process of bandwidth compression. A framework is developed for comparing these techniques and identifying fundamental physical limitations of linear slow-light technologies. It is shown that slow-light delay lines have limited capacity and delay-bandwidth product. In principle, the group velocity in slow-light delay lines can be made to approach zero. But very slow group velocity always comes at the cost of very low bandwidth or throughput. In many applications, miniaturization of the delay line is an important consideration. For all delay-line buffers, the minimum physical size of the buffer for a given number of buffered data bits is ultimately limited by the physical size of each stored bit. We show that in slow-light optical buffers, the minimum achievable size of 1 b is approximately equal to the wavelength of light in the buffer. We also compare the capabilities and limitations of a range of delay-line buffers, investigate the impact of waveguide losses on the buffer capacity, and look at the applicability of slow-light delay lines in a number of applications.

As community concerns about global energy consumption grow, the power consumption of the Internet is becoming an issue of increasing importance. In this paper, we present a network-based model of power consumption in optical IP networks and use this model to estimate the energy consumption of the Internet. The model includes the core, metro and edge, access and video distribution networks, and takes into account energy consumption in switching and transmission equipment. We include a number of access technologies, including digital subscriber line with ADSL2+, fiber to the home using passive optical networks, fiber to the node combined with very high-speed digital subscriber line and point-to-point optical systems. In addition to estimating the power consumption of today's Internet, we make predictions of power consumption in a future higher capacity Internet using estimates of improvements in efficiency in coming generations of network equipment. We estimate that the Internet currently consumes about 0.4% of electricity consumption in broadband-enabled countries. While the energy efficiency of network equipment will improve, and savings can be made by employing optical bypass and multicast, the power consumption of the Internet could approach 1% of electricity consumption as access rates increase. The energy consumption per bit of data on the Internet is around 75\bm muJ at low access rates and decreases to around 2-4 \bm muJ at an access rate of 100 Mb/s.

This paper presents novel algorithms that iteratively converge to a local minimum of a real-valued function f (X) subject to the constraint that the columns of the complex-valued matrix X are mutually orthogonal and have unit norm. The algorithms are derived by reformulating the constrained optimization problem as an unconstrained one on a suitable manifold. This significantly reduces the dimensionality of the optimization problem. Pertinent features of the proposed framework are illustrated by using the framework to derive an algorithm for computing the eigenvector associated with either the largest or the smallest eigenvalue of a Hermitian matrix.

Global food security depends on three main cereal crops (wheat, rice and maize) achieving and maintaining high yields, as well as increasing their future yields. Fundamental to the production of this biomass is photosynthesis. The process of photosynthesis involves a large number of proteins that together account for the majority of the nitrogen in leaves. As large amounts of nitrogen are removed in the harvested grain, this needs to be replaced either from synthetic fertilizer or biological nitrogen fixation. Knowledge about photosynthetic properties of leaves in natural ecosystems is also important, particularly when we consider the potential impacts of climate change. While the relationship between nitrogen and photosynthetic capacity of a leaf differs between species, leaf nitrogen content provides a useful way to incorporate photosynthesis into models of ecosystems and the terrestrial biosphere. This review provides a generalized nitrogen budget for a C3 leaf cell and discusses the potential for improving photosynthesis from a nitrogen perspective.

Hybrid fiber-wireless networks incorporating WDM technology for fixed wireless access operating in the sub-millimeter-wave and millimeter-wave (mm-wave) frequency regions are being actively pursued to provide untethered connectivity for ultrahigh bandwidth communications. The architecture of such radio networks requires a large number of antenna base-stations with high throughput to be deployed to maximize the geographical coverage with the main switching and routing functionalities located in a centralized location. The transportation of mm-wave wireless signals within the hybrid network is subject to several impairments including low opto-electronic conversion efficiency, fiber chromatic dispersion and also degradation due to nonlinearities along the link. One of the major technical challenges in implementing such networks lies in the mitigation of these various optical impairments that the wireless signals experience within the hybrid network. In this paper, we present an overview of different techniques to optically transport mm-wave wireless signals and to overcome impairments associated with the transport of the wireless signals. We also review the different designs of subsystems for integrating fiber-wireless technology onto existing optical infrastructure.

Metasurfaces have recently risen to prominence in optical research, providing unique functionalities that can be used for imaging, beam forming, holography, polarimetry, and many more, while keeping device dimensions small. Despite the fact that a vast range of basic metasurface designs has already been thoroughly studied in the literature, the number of metasurface-related papers is still growing at a rapid pace, as metasurface research is now spreading to adjacent fields, including computational imaging, augmented and virtual reality, automotive, display, biosensing, nonlinear, quantum and topological optics, optical computing, and more. At the same time, the ability of metasurfaces to perform optical functions in much more compact optical systems has triggered strong and constantly growing interest from various industries that greatly benefit from the availability of miniaturized, highly functional, and efficient optical components that can be integrated in optoelectronic systems at low cost. This creates a truly unique opportunity for the field of metasurfaces to make both a scientific and an industrial impact. The goal of this Roadmap is to mark this "golden age" of metasurface research and define future directions to encourage scientists and engineers to drive research and development in the field of metasurfaces toward both scientific excellence and broad industrial adoption.

Crop improvement efforts are targeting increased above-ground biomass and radiation-use efficiency as drivers for greater yield. Early ground cover and canopy height contribute to biomass production, but manual measurements of these traits, and in particular above-ground biomass, are slow and labour-intensive, more so when made at multiple developmental stages. These constraints limit the ability to capture these data in a temporal fashion, hampering insights that could be gained from multi-dimensional data. Here we demonstrate the capacity of Light Detection And Ranging (LiDAR), mounted on a lightweight, mobile, ground-based platform, for rapid multi-temporal and non-destructive estimation of canopy height, ground cover and above-ground biomass. Field validation of LiDAR measurements is presented. For canopy height, strong relationships with LiDAR (r² of 0.99 and root mean square error of 0.017 m) were obtained. Ground cover was estimated from LiDAR using two methodologies: red reflectance image and canopy height. In contrast to NDVI, LiDAR was not affected by saturation at high ground cover, and the comparison of both LiDAR methodologies showed strong association (r²=0.92 and slope=1.02) at ground cover above 0.8. For above-ground biomass, a dedicated field experiment was performed with destructive biomass sampled eight times across different developmental stages. Two methodologies are presented for the estimation of biomass from LiDAR: 3D voxel index (3DVI) and 3D profile index (3DPI). The parameters involved in the calculation of 3DVI and 3DPI were optimised for each sample event from tillering to maturity, as well as generalized for any developmental stage. Individual sample point predictions were strong while predictions across all eight sample events, provided the strongest association with biomass (r²=0.93 and r²=0.92) for 3DPI and 3DVI, respectively. Given these results, we believe that application of this system will provide new opportunities to deliver improved genotypes and agronomic interventions via more efficient and reliable phenotyping of these important traits in large experiments.

Imprinting vision as memory is a core attribute of human cognitive learning. Fundamental to artificial intelligence systems are bioinspired neuromorphic vision components for the visible and invisible segments of the electromagnetic spectrum. Realization of a single imaging unit with a combination of in-built memory and signal processing capability is imperative to deploy efficient brain-like vision systems. However, the lack of a platform that can be fully controlled by light without the need to apply alternating polarity electric signals has hampered this technological advance. Here, a neuromorphic imaging element based on a fully light-modulated 2D semiconductor in a simple reconfigurable phototransistor structure is presented. This standalone device exhibits inherent characteristics that enable neuromorphic image pre-processing and recognition. Fundamentally, the unique photoresponse induced by oxidation-related defects in 2D black phosphorus (BP) is exploited to achieve visual memory, wavelength-selective multibit programming, and erasing functions, which allow in-pixel image pre-processing. Furthermore, all-optically driven neuromorphic computation is demonstrated by machine learning to classify numbers and recognize images with an accuracy of over 90%. The devices provide a promising approach toward neurorobotics, human-machine interaction technologies, and scalable bionic systems with visual data storage/buffering and processing.

Abstract 2D materials, such as graphene, transition metal dichalcogenides, black phosphorus, and tellurium, have been demonstrated to be promising building blocks for the fabrication of next‐generation high‐performance infrared (IR) photodetectors with diverse device architectures and impressive device performance. Integrating IR photodetectors with nanophotonic structures, such as surface plasmon structures, optical waveguides, and optical cavities, has proven to be a promising strategy to maximize the light absorption of 2D absorbers, thus enhancing the detector performance. In this review, the state‐of‐the‐art progress of IR photodetectors is comprehensively summarized based on 2D materials and nanophotonic structures. First, the advantages of using 2D materials for IR photodetectors are discussed. Following that, 2D material‐based IR detectors are classified based on their composition, and their detection mechanisms, key figures‐of‐merit, and the principle of absorption enhancement are discussed using nanophotonic approaches. Then, recent advances in 2D material‐based IR photodetectors are reviewed, categorized by device architecture, i.e., photoconductors, van der Waals heterojunctions, and hybrid systems consisting of 2D materials and nanophotonic structures. The review is concluded by providing perspectives on the challenges and future directions of this field.

Dynamic Spectrum Management of Digital Subscriber Lines (DSL) has the potential to dramatically increase the capacity of the aging last-mile copper access network. This paper takes an important step toward fulfilling this potential through power spectrum balancing. We derive a novel algorithm called SCALE, that provides a significant performance improvement over the existing iterative water-filling (IWF) algorithm in multi-user DSL networks, doing so with comparable low complexity. The algorithm is easily distributed through measurement and limited message-passing with the use of a Spectrum Management Center. We outline how overhead can be managed, and show that in the limit of zero message-passing, performance reduces to IWF. Numerical convergence of SCALE was found to be extremely fast when applied to VDSL, with performance exceeding that of iterative water-filling in just a few iterations, and to over 90% of the final rate in under 5 iterations. Lastly, we return to the problem of iterative water-filling and derive a new algorithm named SCAWF that is shown to be a very simple way to waterfill, particularly suited to the multi-user context.

Abstract Spin defects in solid-state materials are strong candidate systems for quantum information technology and sensing applications. Here we explore in details the recently discovered negatively charged boron vacancies (V B − ) in hexagonal boron nitride (hBN) and demonstrate their use as atomic scale sensors for temperature, magnetic fields and externally applied pressure. These applications are possible due to the high-spin triplet ground state and bright spin-dependent photoluminescence of the V B − . Specifically, we find that the frequency shift in optically detected magnetic resonance measurements is not only sensitive to static magnetic fields, but also to temperature and pressure changes which we relate to crystal lattice parameters. We show that spin-rich hBN films are potentially applicable as intrinsic sensors in heterostructures made of functionalized 2D materials.

Improving photosynthesis to raise wheat yield potential has emerged as a major target for wheat physiologists. Photosynthesis-related traits, such as nitrogen per unit leaf area (Narea) and leaf dry mass per area (LMA), require laborious, destructive, laboratory-based methods, while physiological traits underpinning photosynthetic capacity, such as maximum Rubisco activity normalized to 25 °C (Vcmax25) and electron transport rate (J), require time-consuming gas exchange measurements. The aim of this study was to assess whether hyperspectral reflectance (350-2500 nm) can be used to rapidly estimate these traits on intact wheat leaves. Predictive models were constructed using gas exchange and hyperspectral reflectance data from 76 genotypes grown in glasshouses with different nitrogen levels and/or in the field under yield potential conditions. Models were developed using half of the observed data with the remainder used for validation, yielding correlation coefficients (R2 values) of 0.62 for Vcmax25, 0.7 for J, 0.81 for SPAD, 0.89 for LMA, and 0.93 for Narea, with bias <0.7%. The models were tested on elite lines and landraces that had not been used to create the models. The bias varied between -2.3% and -5.5% while relative error of prediction was similar for SPAD but slightly greater for LMA and Narea.

Identifying misbehaviors is an important challenge for monitoring, fault diagnosis and intrusion detection in wireless sensor networks. A key problem is how to minimize the communication overhead and energy consumption in the network when identifying misbehaviors. Our approach to this problem is based on a distributed, cluster-based anomaly detection algorithm. We minimize the communication overhead by clustering the sensor measurements and merging clusters before sending a description of the clusters to the other nodes. In order to evaluate our distributed scheme, we implemented our algorithm in a simulation based on the sensor data gathered from the Great Duck Island project. We demonstrate that our scheme achieves comparable accuracy compared to a centralized scheme with a significant reduction in communication overhead

Abstract A bound state in the continuum (BIC) is a nonradiating state of light embedded in the continuum of propagating modes providing drastic enhancement of the electromagnetic field and its localization at micro–nanoscale. However, access to such modes in the far‐field requires symmetry breaking. Here, it is demonstrated that a nanometric dielectric or semiconductor layer, 1000 times thinner than the resonant wavelength (λ/1000), induces a dynamically controllable quasi‐bound state in the continuum (QBIC) with ultrahigh quality factor in a symmetric metallic metasurface at terahertz frequencies. Photoexcitation of nanostrips of germanium activates ultrafast switching of a QBIC resonance with 200% transmission intensity modulation and complete recovery within 7 ps on a low‐loss flexible substrate. The nanostrips also form microchannels that provide an opportunity for BIC‐based refractive index sensing. An optimization model is presented for (switchable) QBIC resonances of metamaterial arrays of planar symmetric resonators modified with any (active) dielectric for inverse metamaterial design that can serve as an enabling platform for active micro–nanophotonic devices.

Optically addressable solid-state spins are important platforms for quantum technologies, such as repeaters and sensors. Spins in two-dimensional materials offer an advantage, as the reduced dimensionality enables feasible on-chip integration into devices. Here, we report room-temperature optically detected magnetic resonance (ODMR) from single carbon-related defects in hexagonal boron nitride with up to 100 times stronger contrast than the ensemble average. We identify two distinct bunching timescales in the second-order intensity-correlation measurements for ODMR-active defects, but only one for those without an ODMR response. We also observe either positive or negative ODMR signal for each defect. Based on kinematic models, we relate this bipolarity to highly tuneable internal optical rates. Finally, we resolve an ODMR fine structure in the form of an angle-dependent doublet resonance, indicative of weak but finite zero-field splitting. Our results offer a promising route towards realising a room-temperature spin-photon quantum interface in hexagonal boron nitride.

In this paper, we introduce a practical scheme to defend against distributed denial of service (DDoS) attacks based on IP source address filtering. The edge router keeps a history of all the legitimate IP addresses which have previously appeared in the network. When the edge router is overloaded, this history is used to decide whether to admit an incoming Ip packet. Unlike other proposals to defend against DDoS attacks, our scheme works well during highly-distributed DDoS attacks, i.e., from a large number of sources. We present several heuristic methods to make the IP address database accurate and robust, and we present experimental results that demonstrate the effectiveness of our scheme in defending against highly-distributed DDoS attacks.

Summary Photorespiratory metabolism is essential for plants to maintain functional photosynthesis in an oxygen‐containing environment. Because the oxygenation reaction of Rubisco is followed by the loss of previously fixed carbon, photorespiration is often considered a wasteful process and considerable efforts are aimed at minimizing the negative impact of photorespiration on the plant’s carbon uptake. However, the photorespiratory pathway has also many positive aspects, as it is well integrated within other metabolic processes, such as nitrogen assimilation and C 1 metabolism, and it is important for maintaining the redox balance of the plant. The overall effect of photorespiratory carbon loss on the net CO 2 fixation of the plant is also strongly influenced by the physiology of the leaf related to CO 2 diffusion. This review outlines the distinction between Rubisco oxygenation and photorespiratory CO 2 release as a basis to evaluate the costs and benefits of photorespiration.

We review technologies and architectures for WDM optical IP networks from the viewpoint of capital expenditure and network energy consumption. We show how requirements of low cost and low energy consumption can influence the choice of switching technologies as well as the overall network architecture.