arXiv subjects

Cheng Hu

Publications and source records attributed to Cheng Hu.

At least 55 records · Page 3Linked to original sources

arXiv2021

Electronic Structure Examination on the Topological Properties of CaMnSb$_{2}$ by Angle-Resolved Photoemission Spectroscopy

We have carried out detailed high resolution ARPES measurements and band structure calculations to study the electronic structure of CaMnSb$_{2}$. The observed Fermi surface mainly consists of one hole pocket around $Γ$ point and one tiny hole pocket at Y point. Strong spectral weight accumulation along the $Γ$-X direction is observed on the hole-like Fermi surface around $Γ$ point, suggesting strong anisotropy of the density of states along the Fermi surface. The tiny hole pocket at Y point originates from an anisotropic Dirac-like band with the crossing point of the linear bands lying $\sim$ 10 meV above the Fermi level. These observations are in a good agreement with the band structure calculations. In addition, we observe additional features along the $Γ$-Y line that cannot be accounted for by the band structure calculations. Our results provide important information in understanding and exploration of novel properties in CaMnSb$_{2}$ and related materials.

cond-mat.mtrl-sci↗

arXiv2021

Fano resonance enabled infrared nano-imaging of local strain in bilayer graphene

Detection of local strain at the nanometer scale with high sensitivity remains challenging. Here we report near-field infrared nano-imaging of local strains in bilayer graphene through probing strain-induced shifts of phonon frequency. As a non-polar crystal, intrinsic bilayer graphene possesses little infrared response at its transverse optical (TO) phonon frequency. The reported optical detection of local strain is enabled by applying a vertical electrical field that breaks the symmetry of the two graphene layers and introduces finite electrical dipole moment to graphene phonon. The activated phonon further interacts with continuum electronic transitions, and generates a strong Fano resonance. The resulted Fano resonance features a very sharp near-field infrared scattering peak, which leads to an extraordinary sensitivity of ~0.002% for the strain detection. Our studies demonstrate the first nano-scale near-field Fano resonance, provide a new way to probe local strains with high sensitivity in non-polar crystals, and open exciting possibilities for studying strain-induced rich phenomena.

cond-mat.mes-hall↗

arXiv2021

Quantum Capacitance Induced Non-Local Electrostatic Gating Effect in Graphene

Electrostatic gating lies in the heart of modern FET-based integrated circuits. Usually, the gate electrode has to be placed very close to the conduction channel, typically a few nanometers, in order to achieve efficient tunability. However, remote control of a FET device through a gate electrode placed far away is always highly desired, because it not only reduces the complexity of device fabrication, but also enables designing novel devices with new functionalities. Here, a non-local gating effect in graphene using both near-field optical nano-imaging and electrical transport measurement is reported. With assistance of absorbed water molecules, the charge density of graphene can be efficiently tuned by a local-gate placed over 30 μm away. The observed non-local gating effect is initially driven by an in-plane electric field established between graphene regions with different charge densities due to the quantum capacitance near the Dirac point in graphene. The nonlocality is further amplified and largely enhanced by absorbed water molecules through screening the in-plane electric field and expending the transition length. This research reveals novel non-local phenomenon of Dirac electrons, and paves the way for designing electronic devices with remote-control using 2D materials with small density of states.

cond-mat.mes-hall↗

arXiv2021

Momentum-Resolved Visualization of Electronic Evolution in Doping a Mott Insulator

High temperature superconductivity in cuprates arises from doping a parent Mott insulator by electrons or holes. A central issue is how the Mott gap evolves and the low-energy states emerge with doping. Here we report angle-resolved photoemission spectroscopy measurements on a cuprate parent compound by sequential in situ electron doping. The chemical potential jumps to the bottom of the upper Hubbard band upon a slight electron doping, making it possible to directly visualize the charge transfer band and the full Mott gap region. With increasing doping, the Mott gap rapidly collapses due to the spectral weight transfer from the charge transfer band to the gapped region and the induced low-energy states emerge in a wide energy range inside the Mott gap. These results provide key information on the electronic evolution in doping a Mott insulator and establish a basis for developing microscopic theories for cuprate superconductivity.

cond-mat.str-el↗

arXiv2020

Electronic Evolution from the Parent Mott Insulator to a Superconductor in Lightly Hole-Doped Bi2Sr2CaCu2O8+delta

High temperature superconductivity in cuprates is realized by doping the Mott insulator with charge carriers. A central issue is how such an insulating state can evolve into a conducting or superconducting state when charge carriers are introduced. Here, by in situ vacuum annealing and Rb deposition on the Bi2Sr2Ca0.6Dy0.4Cu2O8+delta (Bi2212) sample surface to push its doping level continuously from deeply underdoped (Tc=25 K, doping level p-0.066) to the near zero doping parent Mott insulator, angle-resolved photoemission spectroscopy measurements are carried out to observe the detailed electronic structure evolution in lightly hole-doped region for the first time. Our results indicate that the chemical potential lies at about 1 eV above the charge transfer band for the parent state at zero doping which is quite close to the upper Hubbard band. With increasing hole doping, the chemical potential moves continuously towards the charge transfer band and the band structure evolution exhibits a rigid band shift-like behavior. When the chemical potential approaches the charge transfer band at a doping level of -0.05, the nodal spectral weight near the Fermi level increases, followed by the emergence of the coherent quasiparticle peak and the insulator-superconductor transition. Our observations provide key insights in understanding the insulator-superconductor transition in doping the parent cuprate compound and for establishing related theories.

cond-mat.supr-con↗

arXiv2019

Reflection Phase Shift of One-dimensional Plasmon Polaritons in Carbon Nanotubes

We investigated, both experimentally and theoretically, the reflection phase shift (RPS) of one-dimensional plasmon polaritons. We launched 1D plasmon polaritons in carbon nanotube and probed the plasmon interference pattern using scanning near-field optical microscopy (SNOM) technique, through which a non-zero phase shift was observed. We further developed a theory to understand the nonzero phase shift of 1D polaritons, and found that the RPS can be understood by considering the evanescent field beyond the nanotube end. Interesting, our theory shows a strong dependence of RPS on polaritons wavelength and nanotube diameter, which is in stark contrast to 2D plasmon polaritons in graphene where the RPS is a constant. In short wave region, the RPS of 1D polaritons only depends on a dimensionless variable -- the ratio between polaritons wavelength and nanotube diameter. These results provide fundamental insights into the reflection of polaritons in 1D system, and could facilitate the design of ultrasmall 1D polaritonic devices, such as resonators, interferometers.

cond-mat.mes-hall↗

arXiv2019

Nonlinear uniaxial pressure dependence of $T_c$ in iron-based superconductors

We have systematically studied the effects of in-plane uniaxial pressure $p$ on the superconducting transition temperature $T_c$ in many iron-based superconductors. The change of $T_c$ with $p$ is composed of linear and nonlinear components. The latter can be described as a quadratic term plus a much smaller fourth-order term. In contrast to the linear component, the nonlinear $p$ dependence of $T_c$ displays a pronounced in-plane anisotropy, which is similar to the anisotropic response of the resistivity to $p$. As a result, it can be attributed to the coupling between the superconducting and nematic orders, in accordance with the expectations of a phenomenological Landau theory. Our results provide direct evidences for the interplay between nematic fluctuations and superconductivity, which may be a common behavior in iron-based superconductors.

cond-mat.supr-con↗

arXiv2019

Selective Hybridization between Main Band and Superstructure Band in Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$ Superconductor

High-resolution laser-based angle-resolved photoemission measurements have been carried out on Bi$_2$Sr$_2$CaCu$_2$O$_{8+δ}$ (Bi2212) and Bi$_2$Sr$_{2-x}$La$_x$CuO$_{6+δ}$ (Bi2201) superconductors. Unexpected hybridization between the main band and the superstructure band in Bi2212 is clearly revealed. In the momentum space where one main Fermi surface intersects with one superstructure Fermi surface, four bands are observed instead of two. The hybridization exists in both superconducting state and normal state, and in Bi2212 samples with different doping levels. Such a hybridization is not observed in Bi2201. This phenomenon can be understood by considering the bilayer splitting in Bi2212, the selective hybridization of two bands with peculiar combinations, and the altered matrix element effects of the hybridized bands. These observations provide strong evidence on the origin of the superstructure band which is intrinsic to the CuO$_2$ planes. Therefore, understanding physical properties and superconductivity mechanism in Bi2212 should consider the complete Fermi surface topology which involves the main bands, the superstructure bands and their interactions.

cond-mat.supr-con↗

arXiv2019

Evolution of Incommensurate Superstructure and Electronic Structure with Pb Substitution in (Bi$_{2-x}$Pb$_{x}$)Sr$_2$CaCu$_2$O$_{8+δ}$ Superconductors

High-quality Bi$_{2-x}$Pb$_{x}$Sr$_2$CaCu$_2$O$_{8+δ}$ (Bi2212) single crystals have been successfully grown by the traveling solvent floating zone technique with a wide range of Pb substitution ($x=0-0.8$). The samples are characterized by transmission electron microscope (TEM) and measured by high resolution laser-based angle-resolved photoemission spectroscopy (ARPES) with different photon energies. A systematic evolution of the electronic structure and superstructure with Pb substitution has been revealed for the first time. The superstructure shows a significant change with Pb substitution and the incommensurate modulation vector ($\textbf{Q}$) decreases with increasing Pb substitution. In the meantime, the superstructure intensity from ARPES measurements also decreases dramatically with increasing Pb concentration. The superstructure in Bi2212 can be effectively suppressed by Pb substitution and it nearly disappears with a Pb substitution of $x=0.8$. We also find that the superstructure bands in ARPES measurements depend sensitively on the photon energy of lasers used; they can become even stronger than the main band when using a laser photon energy of 10.897 eV. These results provide important information on the origin of the incommensurate superstructure and its control and suppression in bismuth-based high temperature superconductors.

cond-mat.supr-con↗

arXiv2019

ColCOS$Φ$: A Multiple Pheromone Communication System for Swarm Robotics and Social Insects Research

In the last few decades we have witnessed how the pheromone of social insect has become a rich inspiration source of swarm robotics. By utilising the virtual pheromone in physical swarm robot system to coordinate individuals and realise direct/indirect inter-robot communications like the social insect, stigmergic behaviour has emerged. However, many studies only take one single pheromone into account in solving swarm problems, which is not the case in real insects. In the real social insect world, diverse behaviours, complex collective performances and flexible transition from one state to another are guided by different kinds of pheromones and their interactions. Therefore, whether multiple pheromone based strategy can inspire swarm robotics research, and inversely how the performances of swarm robots controlled by multiple pheromones bring inspirations to explain the social insects' behaviours will become an interesting question. Thus, to provide a reliable system to undertake the multiple pheromone study, in this paper, we specifically proposed and realised a multiple pheromone communication system called ColCOS$Φ$. This system consists of a virtual pheromone sub-system wherein the multiple pheromone is represented by a colour image displayed on a screen, and the micro-robots platform designed for swarm robotics applications. Two case studies are undertaken to verify the effectiveness of this system: one is the multiple pheromone based on an ant's forage and another is the interactions of aggregation and alarm pheromones. The experimental results demonstrate the feasibility of ColCOS$Φ$ and its great potential in directing swarm robotics and social insects research.

cs.RO↗

arXiv2019

Visualizing the periodic modulation of Cooper pairing in a severely underdoped cuprate

A major obstacle in understanding the mechanism of Cooper pairing in the cuprates is the existence of various intertwined orders associated with spin, charge, and Cooper pairs. Of particular importance is the ubiquitous charge order features that have been observed in a variety of cuprates, especially in the underdoped regime of the phase diagram. To explain the origin of the charge order and its implication to the superconducting phase, many theoretical models have been proposed, such as charge stripes, electronic nematicity, and Fermi surface instability. A highly appealing physical picture is the so-called pair density wave (PDW), a periodic modulation of Cooper paring in space, which may also induce a charge order. To elucidate the existence and nature of the PDW order, here we use scanning tunneling microscopy (STM) to investigate a severely underdoped Bi2Sr2CaCu2O8+δ, in which superconductivity just emerges on top of a pronounced checkerboard charge order. By analyzing the spatial distribution of the spectral features characteristic of superconductivity, we observe a periodic modulation of both the superconducting coherence peak and gap depth, demonstrating the existence of a density wave order of Cooper pairing. The PDW order has the same spatial periodicity as the charge order, and the amplitudes of the two orders exhibit clear positive correlation. These results shed important new lights on the origin of and interplay between the charge order and Cooper pairing modulation in the cuprates.

cond-mat.supr-con↗

arXiv2019

New-Generation Design-Technology Co-Optimization (DTCO): Machine-Learning Assisted Modeling Framework

In this paper, we propose a machine-learning assisted modeling framework in design-technology co-optimization (DTCO) flow. Neural network (NN) based surrogate model is used as an alternative of compact model of new devices without prior knowledge of device physics to predict device and circuit electrical characteristics. This modeling framework is demonstrated and verified in FinFET with high predicted accuracy in device and circuit level. Details about the data handling and prediction results are discussed. Moreover, same framework is applied to new mechanism device tunnel FET (TFET) to predict device and circuit characteristics. This work provides new modeling method for DTCO flow.

cs.OH↗

arXiv2019

Synthetic Neural Vision System Design for Motion Pattern Recognition in Dynamic Robot Scenes

Insects have tiny brains but complicated visual systems for motion perception. A handful of insect visual neurons have been computationally modeled and successfully applied for robotics. How different neurons collaborate on motion perception, is an open question to date. In this paper, we propose a novel embedded vision system in autonomous micro-robots, to recognize motion patterns in dynamic robot scenes. Here, the basic motion patterns are categorized into movements of looming (proximity), recession, translation, and other irrelevant ones. The presented system is a synthetic neural network, which comprises two complementary sub-systems with four spiking neurons -- the lobula giant movement detectors (LGMD1 and LGMD2) in locusts for sensing looming and recession, and the direction selective neurons (DSN-R and DSN-L) in flies for translational motion extraction. Images are transformed to spikes via spatiotemporal computations towards a switch function and decision making mechanisms, in order to invoke proper robot behaviors amongst collision avoidance, tracking and wandering, in dynamic robot scenes. Our robot experiments demonstrated two main contributions: (1) This neural vision system is effective to recognize the basic motion patterns corresponding to timely and proper robot behaviors in dynamic scenes. (2) The arena tests with multi-robots demonstrated the effectiveness in recognizing more abundant motion features for collision detection, which is a great improvement compared with former studies.

cs.NE↗

arXiv2019

An LGMD Based Competitive Collision Avoidance Strategy for UAV

Building a reliable and efficient collision avoidance system for unmanned aerial vehicles (UAVs) is still a challenging problem. This research takes inspiration from locusts, which can fly in dense swarms for hundreds of miles without collision. In the locust's brain, a visual pathway of LGMD-DCMD (lobula giant movement detector and descending contra-lateral motion detector) has been identified as collision perception system guiding fast collision avoidance for locusts, which is ideal for designing artificial vision systems. However, there is very few works investigating its potential in real-world UAV applications. In this paper, we present an LGMD based competitive collision avoidance method for UAV indoor navigation. Compared to previous works, we divided the UAV's field of view into four subfields each handled by an LGMD neuron. Therefore, four individual competitive LGMDs (C-LGMD) compete for guiding the directional collision avoidance of UAV. With more degrees of freedom compared to ground robots and vehicles, the UAV can escape from collision along four cardinal directions (e.g. the object approaching from the left-side triggers a rightward shifting of the UAV). Our proposed method has been validated by both simulations and real-time quadcopter arena experiments.

cs.RO↗

arXiv2019

Weighted-Sum Average Age of Information in Unilaterally Powered Two-Way Data Exchanging Systems

This paper considers a two-way data exchanging system with a constant powered access point and an energy-harvesting powered smart device. The access point simultaneously transmits information and energy to the smart device with fixed powers $\barρ P_\text{t}$ and $ρP_\text{t}$, respectively. Upon collecting enough energy, the smart device performs one block of transmission immediately. We investigate the timeless of the two-way data exchange in terms of age of information (AoI). Specifically, we investigate the trade-off between downlink timeliness and uplink timeliness by optimizing the weighted-sum average AoI. Moreover, we provide a gradient based method to compute this ratio numerically. Our numerical results show that power-splitting based systems outperform time-splitting based systems in terms of timeliness in general.

cs.IT↗

arXiv2019

Towards Computational Models and Applications of Insect Visual Systems for Motion Perception: A Review

Motion perception is a critical capability determining a variety of aspects of insects' life, including avoiding predators, foraging and so forth. A good number of motion detectors have been identified in the insects' visual pathways. Computational modelling of these motion detectors has not only been providing effective solutions to artificial intelligence, but also benefiting the understanding of complicated biological visual systems. These biological mechanisms through millions of years of evolutionary development will have formed solid modules for constructing dynamic vision systems for future intelligent machines. This article reviews the computational motion perception models originating from biological research of insects' visual systems in the literature. These motion perception models or neural networks comprise the looming sensitive neuronal models of lobula giant movement detectors (LGMDs) in locusts, the translation sensitive neural systems of direction selective neurons (DSNs) in fruit flies, bees and locusts, as well as the small target motion detectors (STMDs) in dragonflies and hover flies. We also review the applications of these models to robots and vehicles. Through these modelling studies, we summarise the methodologies that generate different direction and size selectivity in motion perception. At last, we discuss about multiple systems integration and hardware realisation of these bio-inspired motion perception models.

cs.CV↗

arXiv2019

Angular Velocity Estimation of Image Motion Mimicking the Honeybee Tunnel Centring Behaviour

Insects use visual information to estimate angular velocity of retinal image motion, which determines a variety of flight behaviours including speed regulation, tunnel centring and visual navigation. For angular velocity estimation, honeybees show large spatial-independence against visual stimuli, whereas the previous models have not fulfilled such an ability. To address this issue, we propose a bio-plausible model for estimating the image motion velocity based on behavioural experiments of the honeybee flying through patterned tunnels. The proposed model contains mainly three parts, the texture estimation layer for spatial information extraction, the delay-and-correlate layer for temporal information extraction and the decoding layer for angular velocity estimation. This model produces responses that are largely independent of the spatial frequency in grating experiments. And the model has been implemented in a virtual bee for tunnel centring simulations. The results coincide with both electro-physiological neuron spike and behavioural path recordings, which indicates our proposed method provides a better explanation of the honeybee's image motion detection mechanism guiding the tunnel centring behaviour.

q-bio.NC↗

arXiv2019

Emergence of Superconductivity from Fully Incoherent Normal State in an Iron-Based Superconductor (Ba$_{0.6}$K$_{0.4}$)Fe$_2$As$_2$

In unconventional superconductors, it is generally believed that understanding the physical properties of the normal state is a pre-requisite for understanding the superconductivity mechanism. In conventional superconductors like niobium or lead, the normal state is a Fermi liquid with a well-defined Fermi surface and well-defined quasipartcles along the Fermi surface. Superconductivity is realized in this case by the Fermi surface instability in the superconducting state and the formation and condensation of the electron pairs (Cooper pairing). The high temperature cuprate superconductors, on the other hand, represent another extreme case that superconductivity can be realized in the underdoped region where there is neither well-defined Fermi surface due to the pseudogap formation nor quasiparticles near the antinodal regions in the normal state. Here we report a novel scenario that superconductivity is realized in a system with well-defined Fermi surface but without quasiparticles along the Fermi surface in the normal state. High resolution laser-based angle-resolved photoemission measurements have been performed on an optimally-doped iron-based superconductor (Ba$_{0.6}$K$_{0.4}$)Fe$_2$As$_2$. We find that, while sharp superconducting coherence peaks emerge in the superconducting state on the hole-like Fermi surface sheets, no quasiparticle peak is present in the normal state. Its electronic behaviours deviate strongly from a Fermi liquid system. The superconducting gap of such a system exhibits an unusual temperature dependence that it is nearly a constant in the superconducting state and abruptly closes at T$_c$. These observations have provided a new platform to study unconventional superconductivity in a non-Fermi liquid system.

cond-mat.supr-con↗