Resource theory of non-Gaussian operations

Non-Gaussian states and operations are crucial for various continuous-variable quantum information processing tasks. To quantitatively understand non-Gaussianity beyond states, we establish a resource theory for non-Gaussian operations. In our framework, we consider Gaussian operations as free operations, and non-Gaussian operations as resources. We define entanglement-assisted non-Gaussianity generating power and show that it is a monotone that is non-increasing under the set of free super-operations, i.e., concatenation and tensoring with Gaussian channels. For conditional unitary maps, this monotone can be analytically calculated. As examples, we show that the non-Gaussianity of ideal photon-number subtraction and photon-number addition equal the non-Gaussianity of the single-photon Fock state. Based on our non-Gaussianity monotone, we divide non-Gaussian operations into two classes: (1) the finite non-Gaussianity class, e.g., photon-number subtraction, photon-number addition and all Gaussian-dilatable non-Gaussian channels; and (2) the diverging non-Gaussianity class, e.g., the binary phase-shift channel and the Kerr nonlinearity. This classification also implies that not all non-Gaussian channels are exactly Gaussian-dilatable. Our resource theory enables a quantitative characterization and a first classification of non-Gaussian operations, paving the way towards the full understanding of non-Gaussianity.Comment: 15 pages, 4 figure

Hysteretic current-voltage characteristics and resistance switching at an epitaxial oxide Schottky junction SrRuO3_{3}/SrTi0.99_{0.99}Nb0.01_{0.01}O3_{3}

Transport properties have been studied for a perovskite heterojunction consisting of SrRuO$_{3}$ (SRO) film epitaxially grown on SrTi$_{0.99}$Nb$_{0.01}$O$_{3}$ (Nb:STO) substrate. The SRO/Nb:STO interface exhibits rectifying current-voltage ($I$-$V$) characteristics agreeing with those of a Schottky junction composed of a deep work-function metal (SRO) and an $n$-type semiconductor (Nb:STO). A hysteresis appears in the $I$-$V$ characteristics, where high resistance and low resistance states are induced by reverse and forward bias stresses, respectively. The resistance switching is also triggered by applying short voltage pulses of 1 $\mu$s - 10 ms duration.Comment: 3 pages, 3 figures, Appl. Phys. Lett., in pres

Using Stacked Sparse Auto-Encoder and Superpixel CRF for Long-Term Visual Scene Understanding of UGVs

Multiple images have been widely used for scene understanding and navigation of unmanned ground vehicles in long term operations. However, as the amount of visual data in multiple images is huge, the cumulative error in many cases becomes untenable. This paper proposes a novel method that can extract features from a large dataset of multiple images efficiently. Then the membership K-means clustering is used for high dimensional features, and the large dataset is divided into N subdatasets to train N conditional random field (CRF) models based on superpixel. A Softmax subdataset selector is used to decide which one of the N CRF models is chosen as the prediction model for labeling images. Furthermore, some experiments are conducted to evaluate the feasibility and performance of the proposed approach

Enhanced Eco-Approach Control of Connected Electric Vehicles at Signalized Intersection with Queue Discharge Prediction

Long queues of vehicles are often found at signalized intersections, which increases the energy consumption of all the vehicles involved. This paper proposes an enhanced eco-approach control (EEAC) strategy with consideration of the queue ahead for connected electric vehicles (EVs) at a signalized intersection. The discharge movement of the vehicle queue is predicted by an improved queue discharge prediction method (IQDP), which takes both vehicle and driver dynamics into account. Based on the prediction of the queue, the EEAC strategy is designed with a hierarchical framework: the upper-stage uses dynamic programming to find the general trend of the energy-efficient speed profile, which is followed by the lower-stage model predictive controller to computes the explicit solution for a short horizon with guaranteed safe inter-vehicular distance. Finally, numerical simulations are conducted to demonstrate the energy efficiency improvement of the EEAC strategy. Besides, the effects of the queue prediction accuracy on the performance of the EEAC strategy are also investigated

Genome-Wide characterization of ascorbate peroxidase gene family in peanut (Arachis hypogea L.) revealed their crucial role in growth and multiple stress tolerance

Ascorbate peroxidase (APX), an important antioxidant enzyme, plays a significant role in ROS scavenging by catalyzing the decrease of hydrogen peroxide under various environmental stresses. Nevertheless, information about the APX gene family and their evolutionary and functional attributes in peanut (Arachis hypogea L.) was not reported. Therefore, a comprehensive genome-wide study was performed to discover the APX genes in cultivated peanut genome. This study identified 166 AhAPX genes in the peanut genome, classified into 11 main groups. The gene duplication analysis showed that AhAPX genes had experienced segmental duplications and purifying selection pressure. Gene structure and motif investigation indicated that most of the AhAPX genes exhibited a comparatively well-preserved exon-intron pattern and motif configuration contained by the identical group. We discovered five phytohormones-, six abiotic stress-, and five growth and development-related cis-elements in the promoter regions of AhAPX. Fourteen putative ah-miRNAs from 12 families were identified, targeting 33 AhAPX genes. Furthermore, we identified 3,257 transcription factors from 38 families (including AP2, ARF, B3, bHLH, bZIP, ERF, MYB, NAC, WRKY, etc.) in 162 AhAPX genes. Gene ontology and KEGG enrichment analysis confirm the role of AhAPX genes in oxidoreductase activity, catalytic activity, cell junction, cellular response to stimulus and detoxification, biosynthesis of metabolites, and phenylpropanoid metabolism. Based on transcriptome datasets, some genes such as AhAPX4/7/17/77/82/86/130/133 and AhAPX160 showed significantly higher expression in diverse tissues/organs, i.e., flower, leaf, stem, roots, peg, testa, and cotyledon. Likewise, only a few genes, including AhAPX4/17/19/55/59/82/101/102/137 and AhAPX140, were significantly upregulated under abiotic (drought and cold), and phytohormones (ethylene, abscisic acid, paclobutrazol, brassinolide, and salicylic acid) treatments. qRT-PCR-based expression profiling presented the parallel expression trends as generated from transcriptome datasets. Our discoveries gave new visions into the evolution of APX genes and provided a base for further functional examinations of the AhAPX genes in peanut breeding programs

Entanglement-Assisted Communication Surpassing the Ultimate Classical Capacity

Entanglement underpins a variety of quantum-enhanced communication, sensing, and computing capabilities. Entanglement-assisted communication (EACOMM) leverages entanglement pre-shared by communication parties to boost the rate of classical information transmission. Pioneering theory works showed that EACOMM can enable a communication rate well beyond the ultimate classical capacity of optical communications, but an experimental demonstration of any EACOMM advantage remains elusive. Here, we report the implementation of EACOMM surpassing the classical capacity over lossy and noisy bosonic channels. We construct a high-efficiency entanglement source and a phase-conjugate quantum receiver to reap the benefit of pre-shared entanglement, despite entanglement being broken by channel loss and noise. We show that EACOMM beats the Holevo-Schumacher-Westmoreland capacity of classical communication by up to 14.6%, when both protocols are subject to the same power constraint at the transmitter. As a practical performance benchmark, a classical communication protocol without entanglement assistance is implemented, showing that EACOMM can reduce the bit-error rate by up to 69% over the same bosonic channel. Our work opens a route to provable quantum advantages in a wide range of quantum information processing tasks.Comment: 12 pages, 5 figures. Comments are welcom

Quantifying physical transport and local proliferation of phytoplankton downstream of an eutrophicated lake

Eutrophication in a freshwater system has mainly been studied in lakes and their upstream rivers, which are responsible to bring pollutants into the lakes. However, the influence of lakes on downstream rivers suffered massive algae from upstream lakes has not been fully studied. Our study area is Liangxi river, downstream of Taihu Lake, which is highly eutrophicated. The algae in Liangxi river has two origins: the physical transport from Taihu Lake and the in-situ proliferation. This paper aims to apply numerical model to quantify these two processes. The model is calibrated against the measured data in 2018. This computational condition that includes both algal processes is termed as Scheme A. Then, we regarded phytoplankton as a conservative substance by turning off the phytoplankton biological process and calculated term it as Scheme E. We selected the chl-a concentration in Hongqiao (LX2) section to represent the amount of algae in Liangxi river. The average chl-a difference in this section between Schemes A and E, Delta, can be used to quantify the magnitude of in-situ proliferation. The Delta varies seasonally, and the annual average is 7.22 mg/m³, which is 44.7% of the amount attributed to the physical transport. Liangxi river lies in an urban area which might encounter extreme events which to facilitate the in-situ proliferation, such as increased temperature and or excessive nutrient load. To quantify the level of algae under extreme situations, we design Schemes B, C and D which eliminated the limitation on algal growth by temperature, nitrogen and phosphorus respectively. Compared with the Scheme A, Schemes B, C and D oberve 21.8%, 65.7%and 61.2% respectively, increase in the average algal concentration. In the vertical direction, the chl-a concentration varies between 0.8mg/m³ and 2 mg/m³ in Scheme A, while the vertical concentration variances of chl-a in schemes B, C and D are found to be 5.56 mg/m³, 12.11 mg/m³ and 3.30 mg/m³, respectively.National Natural Science Foundation of China (No.51779075); Priority Academic Program Development of Jiangsu Higher Education Institutions; Major Science and Technology Program for Water Pollution Control and Treatment of China (2017ZX07203002-01)