arXiv subjects
Publications and source records attributed to Jun Liu.
In this letter, a novel synchronization method for MIMO-OFDM systems is proposed. The new approach has an accurate estimate of both symbol timing and large frequency offest. Simulation results show the excellent robustness of our method in double-selective channel even if the strongest multipath component arrives behind the first path.
Single-shot and incoherent imaging are two important properties for digital holography technique to extend its application range. In this paper, a simple and compact in-line Fresnel incoherent digital holographic recording system with capability of single-shot and three-dimensional imaging is proposed. A GP lens is used as the common-path interferometer based on its special wave separation property. Parallel phase-shifting holography is used to achieve single-shot operation by using a polarization imaging camera together with space-division multiplexing. The capability of the proposed technique and the setup was experimentally confirmed by images of two standard test charts.
Recently, the targeted ENO (TENO) schemes give a novel framework to keep optimal high-order spatial reconstruction wherever discontinuity is deemed to be vanished, including at smooth critical points, and to avoid oscillations by completely removing stencils crossing discontinuities. Moreover, the smoothness measurement of TENO schemes is in fact acting as shock-detectors, which are capable for distinguishing discontinuities and smooth critical points. Following the idea of a recent improvement, i.e. TENO-NA, the shock-detection and stencil-selection are completely separated in this work. Higher-order polynomials using neighbouring points of the standard five-point TENO scheme are applied for achieving higher-order accuracy without significantly increasing computation cost, by exploring the neighbouring smoothness measurements. In this work, seventh-order spatial accuracy is achieved, and the computational complexity is similar to that of the five-point TENO scheme. Especially, the presented method introduces new flexibility in constructing high-order numerical methods. Numerical results are given to show the shock-capturing and wave-resolving capabilities.
When randomly displacing the nodes of a crystalline and unstressed spring network, we find that the Possion's ratio decreases with the increase of structural disorder and even becomes negative. Employing our finding that longer springs tend to contribute more to the shear modulus but less to the bulk modulus, we are able to achieve negative Poisson's ratio with lower structural disorder by attributing each spring a length dependent stiffness. Even with perfect crystalline structure, the network can have negative Possion's ratio, if the stiffness of each spring is set by its virtual length after a virtual network distortion. We also reveal that the nonaffine contribution arising from the structural or spring constant disorder produced in some cooperative way by network distortion is essential to the emergence of negative Poisson's ratio.
Discrete scale invariance (DSI) is a phenomenon featuring intriguing log-periodicity which can be rarely observed in quantum systems. Here we report the log-periodic quantum oscillations in the magnetoresistance (MR) and the Hall traces of HfTe5 crystals, which reveals the appearance of DSI. The oscillations show the same logB-periodicity in the behavior of MR and Hall, indicating an overall effect of the DSI on the transport properties. Moreover, the DSI feature in the Hall resistance signals its close relation to the carriers. Combined with theoretical simulations, we further clarify the origin of the log-periodic oscillations and the DSI in the topological materials. Our work evidences the universality of the DSI in the Dirac materials and paves way for the full understanding of the novel phenomenon.
Direct-current (d.c.) electricity generation using moving Schottky contact is emerging as a new strategy for mechanical energy conversion. Here, we demonstrate the generation of d.c.tunneling current with a density of ~35 A/m2 at a metal-insulator-semiconductor (MIS) sliding system using micro-tips. The measured current densities were found to be three to four orders of magnitude higher than that observed with the conventional polymer-based triboelectric nanogenerators (TENGs). The electromotive force for the tribo-tunneling transport comes from the dynamic electronic excitation at the frictional interface rather than from the electrostatically trapped surface charges as in the case of conventional TENGs. The strong electronic excitation can give rise to a non-equilibrium interfacial charge variation. Depending on the energy distribution of the excited electrons/holes, the charge variation subsequently dissipates non-adiabatically into tunneling current and trapped surface charges, or adiabatically into heat. These fundamental results not only enhance our understanding of the triboelectric phenomenon, but also open up new paths for the development of next-generation mechanical energy harvesting and sensing techniques.
A key purpose of the U.S. government fuel economy ratings is to provide precise and unbiased fuel economy estimates to assist consumers in their vehicle purchase decisions. For the official fuel economy ratings to be useful, the numbers must be relatively reliable. This study focuses on quantifying the variations of on-road fuel economy relative to official government ratings (fuel economy gap) and seeks proper characterizations for the degree of stochastic dependence between the fuel economy gaps of pairs of vehicles.By using unique data reported by customers of the U.S. government website www.fueleconomy.gov, the study presents an innovative copula-based joint-modeling and forecasting framework for exploring the complex stochastic dependencies (both nonlinear and non-normal) between the fuel economy gaps of vehicles reported by the same person. While the EPA label estimates are similar to the average numbers reported by website customers, significant, non-linear variation exists in the fuel economy gaps for the two vehicles across the sample. In particular, a positive dependence, characterized by Student-t copula, is observed between the fuel economy gaps of the two vehicles with significant dependencies in the tails of the bivariate distribution; a pair in which one vehicle achieves better (worse) fuel economy is likely to contain a second vehicle getting better (worse) fuel economy as well. However, the results also suggest that the strength of overall association is weak (Kendall Tau = 0.28). This implies a lack of compelling agreement between fuel economy gaps which could weaken consumers confidence in making relative comparisons among vehicles.
Plants can sense both intracellular and extracellular mechanical forces and can respond through morphological changes. The signaling components responsible for mechanotransduction of the touch response are largely unknown. Here, we performed a high-throughput SILIA (stable isotope labeling in Arabidopsis)-based quantitative phosphoproteomics analysis to profile changes in protein phosphorylation resulting from 40 seconds of force stimulation in Arabidopsis thaliana. Of the 24 touch-responsive phosphopeptides identified, many were derived from kinases, phosphatases, cytoskeleton proteins, membrane proteins and ion transporters. TOUCH-REGULATED PHOSPHOPROTEIN1 (TREPH1) and MAP KINASE KINASE 2 (MKK2) and/or MKK1 became rapidly phosphorylated in touch-stimulated plants. Both TREPH1 and MKK2 are required for touch-induced delayed flowering, a major component of thigmomorphogenesis. The treph1-1 and mkk2 mutants also exhibited defects in touch-inducible gene expression. A non-phosphorylatable site-specific isoform of TREPH1 (S625A) failed to restore touch-induced flowering delay of treph1-1, indicating the necessity of S625 for TREPH1 function and providing evidence consistent with the possible functional relevance of the touch-regulated TREPH1 phosphorylation. Bioinformatic analysis and biochemical subcellular fractionation of TREPH1 protein indicate that it is a soluble protein. Altogether, these findings identify new protein players in Arabidopsis thigmomorphogenesis regulation, suggesting that protein phosphorylation may play a critical role in plant force responses.
In this paper, we analyze the convergence of several discretize-then-optimize algorithms, based on either a second-order or a fourth-order finite difference discretization, for solving elliptic PDE-constrained optimization or optimal control problems. To ensure the convergence of a discretize-then-optimize algorithm, one well-accepted criterion is to choose or redesign the discretization scheme such that the resultant discretize-then-optimize algorithm commutes with the corresponding optimize-then-discretize algorithm. In other words, both types of algorithms would give rise to exactly the same discrete optimality system. However, such an approach is not trivial. In this work, by investigating a simple distributed elliptic optimal control problem, we first show that enforcing such a stringent condition of commutative property is only sufficient but not necessary for achieving the desired convergence. We then propose to add some suitable $H_1$ semi-norm penalty/regularization terms to recover the lost convergence due to the inconsistency caused by the loss of commutativity. Numerical experiments are carried out to verify our theoretical analysis and also validate the effectiveness of our proposed regularization techniques.
To define and characterize optical systems, obtaining information on the amplitude, phase, and polarization profile of optical beams is of utmost importance. Polarimetry using bulk optics is well established to characterize the polarization state. Recently, metasurfaces and metalenses have successfully been introduced as compact optical components. Here, we take the metasurface concept to the system level by realizing arrays of metalens 2*3 sub-arrays, allowing to determine the polarization profile of an optical beam. We use silicon-based metalenses with a numerical aperture of 0.32 and a mean measured diffraction efficiency in transmission mode of 28% at 1550 nm wavelength. Together with a standard camera recording the array foci, our system is extremely compact and allows for real-time beam diagnostics by inspecting the foci amplitudes. By further analyzing the foci displacements in the spirit of a Hartmann-Shack wavefront sensor, we can simultaneously detect phase-gradient profiles. As application examples, we diagnose the polarization profiles of a radially polarized beam, an azimuthally polarized beam, and of a vortex beam.
Quantum oscillations are usually the manifestation of the underlying physical nature in condensed matter systems. Here we report a new type of log-periodic quantum oscillations in ultra-quantum three-dimensional topological materials. Beyond the quantum limit (QL), the log-periodic oscillations involving up to five oscillating cycles (5 peaks and 5 dips) are observed on the magnetoresistance (MR) of high quality single-crystal ZrTe5, virtually showing the clearest feature of discrete scale invariance (DSI). Further theoretical analyses show that the two-body quasi-bound states can be responsible for the DSI feature. Our work provides a new perspective on the ground state of topological materials beyond the QL.
We present the design and the test results of a dual-channel Vertical-Cavity Surface-Emitting Laser (VCSEL) driver ASIC LOCld65 for detector front-end readout. LOCld65 is designed in a commercial 65-nm CMOS technology with a power supply of 1.2 V. LOCld65 contains two separate channels with the same structure and the two channels share an I2C slave. Each channel consists of an input amplifier, four stages of limiting amplifiers (LAs), a high-current output driver, and a bias-current generator. In order to extend the bandwidth, the input amplifier uses an inductive peaking technique and the LAs use a shared inductive peaking technique. The input amplifier and the output driver each utilize a Continuous-Time Linear Equalizer (CTLE). The LAs employ active feedback. The modulation current, the bias current, the peaking strength of the CTLEs, and the feedback strength of LAs are programmable through an I2C interface. In order to protect from the radiation damage, the I2C slave is implemented with triple modular redundancy. Each channel of LOCld65 is tested to operate up to 14 Gbps with typical power dissipations (the VCSEL included) of 68.3 mW/channel and 62.1 mW/channel at the VCSEL voltages of 3.3 V and 2.5 V, respectively. LOCld65 survives 4.9 kGy(SiO2). LOCld65 is an excellent match for the serializer-deserializer ASIC lpGBT in single- or dual-channel optical transmitters in HL-LHC upgrade applications.
This paper presents development and characterization of a 3.2 Gb/s serial link transmitter for CMOS image sensors. The transmitter incorporates Reed-Solomon code to achieve low error rate in the harsh environment of subatomic physics experiments. Pre-emphasis is implemented in the transmitter, allowing data transmission over low-mass cables. It is fabricated in a 0.18 $μm$ CMOS image process as a standalone chip to characterize its performance, with the core area of 1.8 $mm^2$. A frame data rate of $3\cdot10^{-12}$ with a confidence level of 94.5$\%$ was measured through an FPGA based receiver. The measured nominal power consumption is 135 mW. The transmitter functions normally after irradiated with 4.5 Mrad TID.
Maps are an important medium that enable people to comprehensively understand the configuration of cultural activities and natural elements over different times and places. Although massive maps are available in the digital era, how to effectively and accurately access the required map remains a challenge today. Previous works partially related to map-type classification mainly focused on map comparison and map matching at the local scale. The features derived from local map areas might be insufficient to characterize map content. To facilitate establishing an automatic approach for accessing the needed map, this paper reports our investigation into using deep learning techniques to recognize seven types of map, including topographic map, terrain map, physical map, urban scene map, the National Map, 3D map, nighttime map, orthophoto map, and land cover classification map. Experimental results show that the state-of-the-art deep convolutional neural networks can support automatic map-type classification. Additionally, the classification accuracy varies according to different map-types. We hope our work can contribute to the implementation of deep learning techniques in cartographical community and advance the progress of Geographical Artificial Intelligence (GeoAI).
We propose a geometric convexity shape prior preservation method for variational level set based image segmentation methods. Our method is built upon the fact that the level set of a convex signed distanced function must be convex. This property enables us to transfer a complicated geometrical convexity prior into a simple inequality constraint on the function. An active set based Gauss-Seidel iteration is used to handle this constrained minimization problem to get an efficient algorithm. We apply our method to region and edge based level set segmentation models including Chan-Vese (CV) model with guarantee that the segmented region will be convex. Experimental results show the effectiveness and quality of the proposed model and algorithm.
In this paper, the traditional model based variational method and learning based algorithms are naturally integrated to address mixed noise removal problem. To be different from single type noise (e.g. Gaussian) removal, it is a challenge problem to accurately discriminate noise types and levels for each pixel. We propose a variational method to iteratively estimate the noise parameters, and then the algorithm can automatically classify the noise according to the different statistical parameters. The proposed variational problem can be separated into regularization, synthesis, parameter estimation and noise classification four steps with the operator splitting scheme. Each step is related to an optimization subproblem. To enforce the regularization, the deep learning method is employed to learn the natural images priori. Compared with some model based regularizations, the CNN regularizer can significantly improve the quality of the restored images. Compared with some learning based methods, the synthesis step can produce better reconstructions by analyzing the recognized noise types and levels. In our method, the convolution neutral network (CNN) can be regarded as an operator which associated to a variational functional. From this viewpoint, the proposed method can be extended to many image reconstruction and inverse problems. Numerical experiments in the paper show that our method can achieve some state-of-the-art results for mixed noise removal.
Chance constrained optimal power flow (OPF) has been recognized as a promising framework to manage the risk from variable renewable energy (VRE). In presence of VRE uncertainties, this paper discusses a distributionally robust chance constrained approximate AC-OPF. The power flow model employed in the proposed OPF formulation combines an exact AC power flow model at the nominal operation point and an approximate linear power flow model to reflect the system response under uncertainties. The ambiguity set employed in the distributionally robust formulation is the Wasserstein ball centered at the empirical distribution. The proposed OPF model minimizes the expectation of the quadratic cost function w.r.t. the worst-case probability distribution and guarantees the chance constraints satisfied for any distribution in the ambiguity set. The whole method is data-driven in the sense that the ambiguity set is constructed from historical data without any presumption on the type of the probability distribution, and more data leads to smaller ambiguity set and less conservative strategy. Moreover, special problem structures of the proposed problem formulation are exploited to develop an efficient and scalable solution approach. Case studies are carried out on IEEE 14 and 118 bus systems to show the accuracy and necessity of the approximate AC model and the attractive features of the distributionally robust optimization approach compared with other methods to deal with uncertainties.
Analysis of rapid variability at 4.85 GHz for the BL BLac object 0925+504 is presented and discussed. The structure functions (SF) are investigated with both refractive and weak interstellar scintillation (RISS/WISS) models analytically. Parameters obtained with these models are quantitatively compared, suggesting that the emission region of IDV is remarkably compact and the responsible interstellar scintillation medium (ISM) lies very close to the observer. Furthermore possible evidence of annual modulation of the variability timescales is detected in this source. Our findings indicate that the observed rapid variability in 0925+504 is predominantly caused by a scattering screen located along the line of sight to the source, at a distance of $\sim 110\,pc$ to the observer.