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Shuai Liu

Publications and source records attributed to Shuai Liu.

At least 199 records · Page 11Linked to original sources

AIM 2019 Challenge on Constrained Super-Resolution: Methods and Results

This paper reviews the AIM 2019 challenge on constrained example-based single image super-resolution with focus on proposed solutions and results. The challenge had 3 tracks. Taking the three main aspects (i.e., number of parameters, inference/running time, fidelity (PSNR)) of MSRResNet as the baseline, Track 1 aims to reduce the amount of parameters while being constrained to maintain or improve the running time and the PSNR result, Tracks 2 and 3 aim to optimize running time and PSNR result with constrain of the other two aspects, respectively. Each track had an average of 64 registered participants, and 12 teams submitted the final results. They gauge the state-of-the-art in single image super-resolution.

eess.IV↗

Quantum-Computing Architecture based on Large-Scale Multi-Dimensional Continuous-Variable Cluster States in a Scalable Photonic Platform

Quantum computing is a disruptive paradigm widely believed to be capable of solving classically intractable problems. However, the route toward full-scale quantum computers is obstructed by immense challenges associated with the scalability of the platform, the connectivity of qubits, and the required fidelity of various components. One-way quantum computing is an appealing approach that shifts the burden from high-fidelity quantum gates and quantum memories to the generation of high-quality entangled resource states and high fidelity measurements. Cluster states are an important ingredient for one-way quantum computing, and a compact, portable, and mass producible platform for large-scale cluster states will be essential for the widespread deployment of one-way quantum computing. Here, we bridge two distinct fields---Kerr microcombs and continuous-variable (CV) quantum information---to formulate a one-way quantum computing architecture based on programmable large-scale CV cluster states. The architecture can accommodate hundreds of simultaneously addressable entangled optical modes multiplexed in the frequency domain and an unlimited number of sequentially addressable entangled optical modes in time domain. One-dimensional, two-dimensional, and three-dimensional CV cluster states can be deterministically produced. We note cluster states of at least three dimensions are required for fault-tolerant one-way quantum computing with known error-correction strategies. This architecture can be readily implemented with silicon photonics, opening a promising avenue for quantum computing at a large scale.

quant-ph↗

Chemical and Kinematic Properties of the Galactic Disk from the LAMOST and Gaia Sample Stars

We determined the chemical and kinematic properties of the Galactic thin and thick disk using a sample of 307,246 A/F/G/K-type giant stars from the LAMOST spectroscopic survey and Gaia DR2 survey. Our study found that the thick disk globally exhibits no metallicity radial gradient, but the inner disk ($R \le 8$ kpc) and the outer disk ($R>8$ kpc) have different gradients when they are studied separately. The thin disk also shows two different metallicity radial gradients for the inner disk and the outer disk, and has steep metallicity vertical gradient of d[Fe/H]/d$|z|$ $=-0.12\pm0.0007$ dex kpc$^{-1}$, but it becomes flat when it is measured at increasing radial distance, while the metallicity radial gradient becomes weaker with increasing vertical distance. Adopting a galaxy potential model, we derived the orbital eccentricity of sample stars and found a downtrend of average eccentricity with increasing metallicity for the thick disk. The variation of the rotation velocity with the metallicity shows a positive gradient for the thick disk stars and a negative one for the thin disk stars. Comparisons of our observed results with models of disk formation suggest that radial migration could have influenced the chemical evolution of the thin disk. The formation of the thick disk could be affected by more than one processes: the accretion model could play an indispensable role, while other formation mechanisms, such as the radial migration or heating scenario model could also have a contribution.

astro-ph.GA↗

A Multi-Resolution 3D-DenseNet for Chemical Shift Prediction in NMR Crystallography

We have developed a deep learning algorithm for chemical shift prediction for atoms in molecular crystals that utilizes an atom-centered Gaussian density model for the 3D data representation of a molecule. We define multiple channels that describe different spatial resolutions for each atom type that utilizes cropping, pooling, and concatenation to create a multi-resolution 3D-DenseNet architecture (MR-3D-DenseNet). Because the training and testing time scale linearly with the number of samples, the MR-3D-DenseNet can exploit data augmentation that takes into account the property of rotational invariance of the chemical shifts, thereby also increasing the size of the training dataset by an order of magnitude without additional cost. We obtain very good agreement for 13C, 15N, and 17O chemical shifts, with the highest accuracy found for 1H chemical shifts that is equivalent to the best predictions using ab initio quantum chemistry methods.

physics.chem-ph↗

Scaling-up atomically thin coplanar semiconductor-metal circuitry via phase engineered chemical assembly

Two-dimensional (2D) layered semiconductors, with their ultimate atomic thickness, have shown promise to scale down transistors for modern integrated circuitry. However, the electrical contacts that connect these materials with external bulky metals are usually unsatisfactory, which limits the transistor performance. Recently, contacting 2D semiconductors using coplanar 2D conductors has shown promise in reducing the problematic high resistance contacts. However, many of these methods are not ideal for scaled production. Here, we report on the large-scale, spatially controlled chemical assembly of the integrated 2H-MoTe2 field-effect transistors (FETs) with coplanar metallic 1T' MoTe2 contacts via phase engineered approaches. We demonstrate that the heterophase FETs exhibit ohmic contact behavior with low contact resistance, resulting from the coplanar seamless contact between 2H and 1T' MoTe2 confirmed by transmission electron microscopy characterizations. The average mobility of the heterophase FETs was measured to be as high as 23 cm2 V-1 s-1 (comparable with those of exfoliated single crystals), due to the large 2H MoTe2 single-crystalline domain (486μm). By developing a patterned growth method, we realize the 1T' MoTe2 gated heterophase FET array whose components of channel, gate, and contacts are all 2D materials. Finally, we transfer the heterophase device array onto a flexible substrate and demonstrate the near-infrared photoresponse with high photoresponsivity (~1.02 A/W). Our study provides a basis for the large-scale application of phase-engineered coplanar MoTe2 semiconductors-meter structure in advanced electronics and optoelectronics.

cond-mat.mtrl-sci↗

The substructures in the local stellar halo from Gaia and LAMOST

Based on the second Gaia data release (Gaia DR2) and spectroscopy from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data, we identified 20,089 halo stars kinematically and chemically. The halo streams in the solar neighborhood could be detected in the space of energy and angular momentum. We reshuffle the velocities of these stars to determine the significance of substructure. Finally, we identify 4 statistically significant substructures that are labeled GL-1 through 4. Among these substructures, GL-1 is previously known stream ("N2" stream) and the rest 3 substructures are new. These substructures may be the debris of dwarf galaxies accretion event, their dynamical and chemical information can help to understand the history of the Milky Way.

astro-ph.GA↗

Design and Realization of Intersection Traffic Control Simulation System Using Connected Vehicle Technology

The connected vehicle technology is a remarkable trend in the field of the intelligent transportation system. Since the actual deployment of the connected vehicle system is still lacking hitherto, simulation is widely adopted as the major method of verification in related researches. Although traditional commercial traffic simulation systems perform well in macroscopic simulations, they seem redundant in the circumstance of small-size traffic. In addition, those systems are unable to simulate the communication between vehicles and road-side infrastructures. This study designs a platform for the simulation of intersection traffic control using connected vehicle technology. By providing an abundance of customizable parameters, the platform can simulate at various levels of speed to meet different requirements, serving as a basis for testing further research.

eess.SY↗

The high velocity stars in the Local Stellar Halo from Gaia and LAMOST

Based on the first Gaia data release and spectroscopy from the LAMOST Data Release 4, we study the kinematics and chemistry of the local halo stars. The halo stars are identified kinematically with a relative speed of at least 220 km s$^{-1}$ with respect to the local standard of rest. In total, 436 halo stars are identified. From this halo sample, 16 high velocity (HiVel) stars are identified. We studied the metallicity and [$α$/Fe] distribution of these HiVel stars. Though most of HiVel stars are metal-poor, there are several stars that have metallicity above $-0.5$ dex. To understand the origin of high velocity stars, we evolve the trajectory of the star backwards along the orbit in our adopted Galaxy potential model to determine the orbital parameters and assess whether the star could have originated in the Galactic center. We found that some high velocity stars could have originated from the Galactic center, but other stars were probably kicked up from the Galactic disk.

astro-ph.GA↗

Metallicity and Kinematics of the Galactic halo from the LAMOST sample stars

We study the metallicity distribution and kinematic properties of 4,680 A/F/G/K-type giant stars with $|z|>$ 5 kpc selected from the LAMOST spectroscopic survey. The metallicity distribution of giant stars with 5 $<|z|\leqslant$ 15 kpc can be described by a three-peak Gaussian model with peaks at [Fe/H] $\sim-0.6\pm0.1$, $-1.2\pm0.3$ and $-2.0\pm0.2$, corresponding to the ratio of 19$\%$, 74$\%$ and 7$\%$, respectively. The $\rm{[α/Fe]}$ is used to associate the three peaks with the thick disk, inner-halo and outer-halo components of the Galaxy. The metallicity distribution of these giant stars, which is fit with Gaussians corresponding to the three components, show a growing fraction of inner-halo component and declining fraction of the thick-disk component with increasing distance from the Galactic plane. Adopting a galaxy potential model, we also derive the orbital parameters of the sample stars, such as orbit eccentricity and rotation velocity. The peak values of derived orbital eccentricity for stars covering different metallicity regions maintain $e\sim$ 0.75, independent of height above the plane, within the range 5$<|z|<$ 15 kpc. By comparing the MDFs of stars in different rotation velocity intervals, we find that the majority of the retrograde stars are more metal-poor than the prograde stars.

astro-ph.GA↗

Multi-vehicle Flocking Control with Deep Deterministic Policy Gradient Method

Flocking control has been studied extensively along with the wide application of multi-vehicle systems. In this paper the Multi-vehicles System (MVS) flocking control with collision avoidance and communication preserving is considered based on the deep reinforcement learning framework. Specifically the deep deterministic policy gradient (DDPG) with centralized training and distributed execution process is implemented to obtain the flocking control policy. First, to avoid the dynamically changed observation of state, a three layers tensor based representation of the observation is used so that the state remains constant although the observation dimension is changing. A reward function is designed to guide the way-points tracking, collision avoidance and communication preserving. The reward function is augmented by introducing the local reward function of neighbors. Finally, a centralized training process which trains the shared policy based on common training set among all agents. The proposed method is tested under simulated scenarios with different setup.

cs.RO↗

Iterative Learning Economic Model Predictive Control

An iterative learning based economic model predictive controller (ILEMPC) is proposed for repetitive tasks in this paper. Compared with existing works, the initial feasible trajectory of the proposed ILEMPC is not restricted to be convergent to an equilibrium so it can handle various types of control objectives: stabilization, tracking a periodic trajectory and even pure economic optimization. The controller can learn from the previous closed-loop trajectory, resulting in a performance which is guaranteed to be no worse than the previous one. Under some standard assumptions in model predictive control, we show that recursive feasibility is ensured. Furthermore, for stabilization problem, the convergence of each learned trajectory and the learning process are established provided the initial trajectory is convergent. Numerical examples show that the proposed control strategy works well for different types of control tasks and systems.

eess.SY↗

A Novel Distance Matric: Generalized Relative Entropy

Information entropy and its extension, which are important generalization of entropy, have been applied in many research domains today. In this paper, a novel generalized relative entropy is constructed to avoid some defects of traditional relative entropy. We presented the structure of generalized relative entropy after the discussion of defects in relative entropy. Moreover, some properties of the provided generalized relative entropy is presented and proved. The provided generalized relative entropy is proved to have a finite range and is a finite distance metric.

cs.IT↗

Holographic s-wave and p-wave Josephson junction with backreaction

In this paper, we study the holographic models of s-wave and p-wave Josephoson junction away from probe limit in (3+1)-dimensional spacetime, respectively. With the backreaction of the matter, we obtained the anisotropic black hole solution with the condensation of matter fields. We observe that the critical temperature of Josephoson junction decreases with increasing backreaction. In addition to this, the tunneling current and condenstion of Josephoson junction become smaller as backreaction grows larger, but the relationship between current and phase difference still holds for sine function. Moreover, condenstion of Josephoson junction deceases with increasing width of junction exponentially.

hep-th↗

Electric field control of deterministic current-induced magnetization switching in a hybrid ferromagnetic/ferroelectric structure

All-electrical and programmable manipulations of ferromagnetic bits are highly pursued for the aim of high integration and low energy consumption in modern information technology. Methods based on the spin-orbit torque switching in heavy metal/ferromagnet structures have been proposed with magnetic field, and recently are heading toward deterministic switching without external magnetic field. Here we demonstrate that an in-plane effective magnetic field can be induced by an electric field without breaking the symmetry of the structure of the thin film, and realize the deterministic magnetization switching in a hybrid ferromagnetic/ferroelectric structure with Pt/Co/Ni/Co/Pt layers on PMN-PT substrate. The effective magnetic field can be reversed by changing the direction of the applied electric field on the PMN-PT substrate, which fully replaces the controllability function of the external magnetic field. The electric field is found to generate an additional spin-orbit torque on the CoNiCo magnets, which is confirmed by macrospin calculations.

cond-mat.mtrl-sci↗

Random lasing actions in self-assembled perovskite nanoparticles

Solution-based perovskite nanoparticles have been intensively studied in past few years due to their applications in both photovoltaic and optoelectronic devices. Here, based on the common ground between the solution-based perovskite and random lasers, we have studied the mirrorless lasing actions in self-assembled perovskite nanoparticles. After the synthesis from solution, discrete lasing peaks have been observed from the optically pumped perovskites without any well-defined cavity boundaries. The obtained quality (Q) factors and thresholds of random lasers are around 500 and 60 uJ/cm2, respectively. Both values are comparable to the conventional perovskite microdisk lasers with polygon shaped cavity boundaries. From the corresponding studies on laser spectra and fluorescence microscope images, the lasing actions are considered as random lasers that are generated by strong multiple scattering in random gain media. In additional to conventional single-photon excitation, due to the strong nonlinear effects of perovskites, two-photon pumped random lasers have also been demonstrated for the first time. We believe this research will find its potential applications in low-cost coherent light sources and biomedical detection.

physics.optics↗

Formation of Single-mode Laser in Perovskite Nanowire via Nano-manipulation

Perovskite based micro- and nano- lasers have attracted considerable research attention in past two years. However, the properties of perovskite devices are mostly fixed once they are synthesized. Here we demonstrate the tailoring of lasing properties of perovskite nanowire lasers via nano-manipulation. By utilizing a tungsten probe, one nanowire has been lifted from the wafer and re-positioned its two ends on two nearby perovskite blocks. Consequently, the conventional Fabry-Perot lasers are completely suppressed and a single laser peak has been observed. The corresponding numerical model reveals that the single-mode lasing operation is formed by the whispering gallery mode in the transverse plane of perovskite nanowire. Our research provides a simple way to tailor the properties of nanowire and it will be essential for the applications of perovskite optoelectronics.

physics.optics↗

The U-Lagrangian of a prox-regular function

When restricted to a subspace, a nonsmooth function can be differentiable. It is known that for a nonsmooth convex function f and a point x, the Euclidean space can be decomposed into two subspaces: U, over which a special Lagrangian can be defined and has nice smooth properties and V, the orthogonal complement subspace of U. In this paper we generalize the definition of UV-decomposition and U-Lagrangian to the context of nonconvex functions, specifically that of a prox-regular function.

math.OC↗