All-Optical Reconfigurable Electronic Memory in a Graphene/SrTiO3 Heterostructure

Direct optical data coding in an electronic device is meaningful for photonic technology. Herein, we report electronic memory in a graphene/SrTiO₃ heterostructure, which presents the all-optical logic operation (encoding and decoding). The underlying physics have been elucidated in which the synergistic effect of surface localization with interface band bending is responsible for optical encoding and decoding in the electronic memory device of the graphene/SrTiO₃ heterostructure. Further, we demonstrate a robust retention and synaptic-like processing of optical signals, which may lead to significant applications in neuromorphic imaging sensors.

The Future Role of High-Performance Computing in Cardiovascular Medicine and Science -Impact of Multi-Dimensional Data Analysis

Advances in High-performance computing (HPC) technology have reached the capacity to inform cardiovascular (CV) science in the realm of both inductive and constructive approaches. Clinical trials allow for the comparison of the effect of an intervention without the need to understand the mechanism. This is a typical example of an inductive approach. In the HPC field, training an artificial intelligence (AI) model, constructed by neural networks, to predict future CV events with the use of large scale multi-dimensional datasets is the counterpart that may rely on as well as inform understanding of mechanistic underpinnings for optimization. However, in contrast to clinical trials, AI can calculate event risk at the individual level and has the potential to inform and refine the application of personalized medicine.

Despite this clear strength, results from AI analyses may identify otherwise unidentified/unexpected (i.e. non-intuitive) relationships between multi-dimensional data and clinical outcomes that may further unravel potential mechanistic pathways and identify potential therapeutic targets, therebycontributing to the parsing of observational associations from causal links. The constructive approach will remain critical to overcome limitations of existing knowledge and anchored biases to actualize a more sophisticated understanding of the complex pathobiology of CV diseases.

HPC technology has the potential to underpin this constructive approach in CV basic and clinical science. In general, even complex biological phenomena can be reduced to combinations of simple biological/chemical/physical laws. In the deductive approach, the focus/intent is to explain complex CV diseases by combinations of simple principles.

Auxiliary graph based routing, wavelength, and time-slot assignment in metro quantum optical networks with a novel node structure

Nowadays, critical sectors in government, finance, and military are facing increasingly high security challenges. However, traditional public-key crypto-systems based on computational complexity are likely to suffer from upgrade computational power. Quantum key distribution (QKD) is a promising technology to effectively address the challenge by providing secret keys due to the laws of quantum physics. Limited by the transmission distance of quantum communications, remote parties have to share secret keys by exchanging keys through the trusted relay nodes hop by hop. However, if relaying hop by hop is still used in metro quantum-optical networks (MQON), a large amount of key resources will be wasted since the distance between any two nodes is short. Therefore, the problem of how to distribute quantum keys with lower waste of key resources over MQON is urgent. In order to solve this problem, we design a novel quantum node structure that is able to bypass itself. Also, by extending the connectivity graph, auxiliary graphs are constructed to describe the adjacency of quantum nodes in different levels influenced by the physical distance. Based on the novel node, two routing, wavelength and time-slot assignment algorithms are proposed, in which some middle nodes can be bypassed to reduce the resource consumption as long as the distance between the two parties meets the requirement of quantum key distribution. Simulations have been conducted to verify the performance of the proposed algorithms in terms of blocking probability, resource utilization, number of bypassed nodes, and security rate per service. Numerical results illustrate that our algorithms perform better on resource utilization than a traditional scheme without bypass. Furthermore, a tradeoff between the keys saved and blocking probability is analyzed and discussed in our paper.

Capillary-driven elastic attraction between quantum dots

We present a novel self-assembly route to align SiGe quantum dots. By a combination of theoretical analyses and experimental investigation, we show that epitaxial SiGe quantum dots can cluster in ordered closely packed assemblies, revealing an attractive phenomenon. We compute nucleation energy barriers, accounting for elastic effects between quantum dots through both elastic energy and strain-dependent surface energy. If the former is mostly repulsive, we show that the decrease in the surface energy close to an existing island reduces the nucleation barrier. It subsequently increases the probability of nucleation close to an existing island, and turns out to be equivalent to an effective attraction between dots. We show by Monte-Carlo simulations that this effect describes well the experimental results, revealing a new mechanism ruling self-organisation of quantum dots. Such a generic process could be observed in various heterogeneous systems and could pave the way for a wide range of applications.

SDQaaS: software defined networking for quantum key distribution as a service

Quantum key distribution (QKD) holds the potential of providing long-term integrity and confidentiality for data and communications. Currently, many fiber-based QKD systems have been commercialized and several QKD networks have been deployed. Given the high cost and complexity of QKD network deployment, QKD as a service (QaaS) becomes a promising pattern for future QKD networks. The QaaS concept is that multiple users can apply for QKD services to obtain their required secret-key rates (SKRs) from the same QKD network infrastructure instead of deploying their dedicated QKD networks. Accordingly, how to provide efficient and flexible QaaS for fulfilling the SKR requirements of multiple users over a QKD network infrastructure becomes a new challenge. This study introduces the software defined networking (SDN) technique to overcome this challenge, since SDN can add flexibility together with efficient QKD network management. A new framework of SDN for QaaS (SDQaaS) is proposed, where the QaaS functions are developed in the SDN controller. We present the protocol extension, intercommunication workflow, and routing and SKR assignment strategy for QaaS implementation in the SDQaaS framework. We also establish a SDQaaS experimental testbed and perform the numerical simulation to verify our presented approaches. Experimental results demonstrate that our presented approaches can achieve efficient and flexible QaaS over the QKD network. Moreover, simulation results indicate that the success probability of QKD service requests can be increased via lowering the flexibility of SKR requirements for QKD service creation, sacrificing more cost to produce higher SKR over the QKD network, or gradually reducing SKR requirements with the modification of QKD service.

Enabling single qubit addressability in a molecular semiconductor comprising gold-supported organic radicals

A bis(dithiolene)gold complex is presented as a model for an organic molecular electron spin qubit attached to a metallic surface that acts as a conduit to electrically address the qubit. A two-membered electron transfer series is developed of the formula [AuIII(adt)2]1-/0, where adt is a redox-active dithiolene ligand that is sequentially oxidized as the series is traversed while the central metal ion remains AuIII and steadfastly square planar. One-electron oxidation of diamagnetic [AuIII(adt)2]1- (1) produces an S = 1/2 charge-neutral complex, [AuIII(adt2 3-˙)] (2) which is spectroscopically and theoretically characterized with a near negligible Au contribution to the ground state. A phase memory time (T M) of 21 μs is recorded in 4 : 1 CS2/CCl4 at 10 K, which is the longest ever reported for a coordination complex possessing a third-row transition metal ion. With increasing temperature, T M dramatically decreases becoming unmeasurable above 80 K as a consequence of the diminishing spin-lattice (T 1) relaxation time fueled by spin-orbit coupling. These relaxation times are 1-2 orders of magnitude shorter for the solid dilution of 2 in isoelectronic [Ni(adt)2] because this material is a molecular semiconductor. Although the conducting properties of this material provide efficient pathways to dissipate the energy through the lattice, it can also be used to electrically address the paramagnetic dopant by tapping into the mild reduction potential to switch magnetism "on" and "off" in the gold complex without compromising the integrity of its structure. These results serve to highlight the need to consider all components of these spintronic assemblies.

Multi-tenant secret-key assignment over quantum key distribution networks

Quantum key distribution (QKD) networks are promising to progress towards widespread practical deployment over existing fiber infrastructures in the near future. Given the high cost and difficulty of deploying QKD networks, multi-tenancy becomes promising to improve cost efficiency for future QKD networks. In a multi-tenant QKD network, multiple QKD tenants can share the same QKD network infrastructure to obtain secret keys for securing their data transfer. Since the secret-key resources are finite and precious in QKD networks, how to achieve efficient multi-tenant secret-key assignment (MTKA) to satisfy the secret-key demands of multiple QKD tenants over QKD networks becomes a significant problem. In this regard, this study addresses the MTKA problem over QKD networks. A new multi-tenant QKD network architecture is proposed based on software defined networking (SDN) and quantum key pool (QKP) techniques. A secret-key rate sharing scheme is presented and a heuristic algorithm is designed to implement efficient MTKA over QKD networks. A new performance metric, namely matching degree (MD) that reflects the balance between QKD network secret-key resources and QKD tenant requests, is defined and evaluated. Simulation studies indicate that high QKD tenant requests accommodation and efficient secret-key resource usage can be achieved via maximizing the value of MD.

Understanding Forest Health with Remote Sensing, Part III: Requirements for a Scalable Multi-Source Forest Health Monitoring Network Based on Data Science Approaches

Forest ecosystems fulfill a whole host of ecosystem functions that are essential for life on our planet. However, an unprecedented level of anthropogenic influences is reducing the resilience and stability of our forest ecosystems as well as their ecosystem functions. The relationships between drivers, stress, and ecosystem functions in forest ecosystems are complex, multi-faceted, and often non-linear, and yet forest managers, decision makers, and politicians need to be able to make rapid decisions that are data-driven and based on short and long-term monitoring information, complex modeling, and analysis approaches. A huge number of long-standing and standardized forest health inventory approaches already exist, and are increasingly integrating remote-sensing based monitoring approaches. Unfortunately, these approaches in monitoring, data storage, analysis, prognosis, and assessment still do not satisfy the future requirements of information and digital knowledge processing of the 21st century. Therefore, this paper discusses and presents in detail five sets of requirements, including their relevance, necessity, and the possible solutions that would be necessary for establishing a feasible multi-source forest health monitoring network for the 21st century. Namely, these requirements are: (1) understanding the effects of multiple stressors on forest health; (2) using remote sensing (RS) approaches to monitor forest health; (3) coupling different monitoring approaches; (4) using data science as a bridge between complex and multidimensional big forest health (FH) data; and (5) a future multi-source forest health monitoring network. It became apparent that no existing monitoring approach, technique, model, or platform is sufficient on its own to monitor, model, forecast, or assess forest health and its resilience. In order to advance the development of a multi-source forest health monitoring network, we argue that in order to gain a better understanding of forest health in our complex world, it would be conducive to implement the concepts of data science with the components: (i) digitalization; (ii) standardization with metadata management after the FAIR (Findability, Accessibility, Interoperability, and Reusability) principles; (iii) Semantic Web; (iv) proof, trust, and uncertainties; (v) tools for data science analysis; and (vi) easy tools for scientists, data managers, and stakeholders for decision-making support.