arXiv subjects
Publications and source records attributed to Yi Shi.
We prove that all star vector fields, including Lorenz attractors and multisingular hyperbolic vector fields, admit the intermediate entropy property. To be precise, if $X$ is a star vector field with $h_{top}(X)>0$, then for any $h\in [0,h_{top}(X))$, there exists an ergodic invariant measure $μ$ of $X$ such that $h_μ(X)=h$. Moreover, we show that the topological entropy is lower semi-continuous for star vector fields.
In many complex networked systems, such as online social networks, activity originates at certain nodes and subsequently spreads on the network through influence. In this work, we consider the problem of modeling the spread of influence and the identification of influential entities in a complex network when nodal activation can happen via two different mechanisms. The first mechanism of activation stems from factors that are intrinsic to the node. The second mechanism comes from the influence of connected neighbors. After introducing the model, we provide an algorithm to mine for the influential nodes in such a scenario by modifying the well-known influence maximization algorithm to work with our model that incorporates both forms of activation. Our model can be considered as a variation of the independent cascade diffusion model. We provide small motivating examples to facilitate an intuitive understanding of the effect of including the intrinsic activation mechanism. We sketch a proof of the submodularity of the influence function under the new formulation and demonstrate the same on larger graphs. Based on the model, we explain how influential content creators can drive engagement on social media platforms. Using additional experiments on a Twitter dataset, we then show how the formulation can be applied to real-world social media datasets. Finally, we derive a centrality metric that takes into account, both the mechanisms of activation and provides for an accurate, computationally efficient, alternate approach to the problem of identifying influencers under intrinsic activation.
We construct a family of partially hyperbolic skew-product diffeomorphisms on $\mathbb{T}^3$ that are robustly transitive and admitting two physical measures with intermingled basins. In particularly, all these diffeomorphisms are not topologically mixing. Moreover, for every such example, it exhibits a dichotomy under perturbation: every perturbation of such example either has a unique physical measure and is robustly topologically mixing, or has two physical measures with intermingled basins.
Transition-metal dichalcogenides (TMDCs) are important class of two-dimensional (2D) layered materials for electronic and optoelectronic applications, due to their ultimate body thickness, sizable and tunable bandgap, and decent theoretical room-temperature mobility of hundreds to thousands cm2/Vs. So far, however, all TMDCs show much lower mobility experimentally because of the collective effects by foreign impurities, which has become one of the most important limitations for their device applications. Here, taking MoS2 as an example, we review the key factors that bring down the mobility in TMDC transistors, including phonons, charged impurities, defects, and charge traps. We introduce a theoretical model that quantitatively captures the scaling of mobility with temperature, carrier density and thickness. By fitting the available mobility data from literature over the past few years, we are able to obtain the density of impurities and traps for a wide range of transistor structures. We show that interface engineering such as oxide surface passivation, high-k dielectrics and BN encapsulation could effectively reduce the impurities, leading to improved device performances. For few-layer TMDCs, we analytically model the lopsided carrier distribution to elucidate the experimental increase of mobility with the number of layers. From our analysis, it is clear that the charge transport in TMDC samples is a very complex problem that must be handled carefully. We hope that this Review can provide new insights and serve as a starting point for further improving the performance of TMDC transistors.
In this paper, we use the methods of subriemannian geometry to study the dual foliation of the singular Riemannian foliation induced by isometric Lie group actions on a complete Riemannian manifold M. We show that under some conditions, the dual foliation has only one leaf.
Hashing is one of the most popular and powerful approximate nearest neighbor search techniques for large-scale image retrieval. Most traditional hashing methods first represent images as off-the-shelf visual features and then produce hashing codes in a separate stage. However, off-the-shelf visual features may not be optimally compatible with the hash code learning procedure, which may result in sub-optimal hash codes. Recently, deep hashing methods have been proposed to simultaneously learn image features and hash codes using deep neural networks and have shown superior performance over traditional hashing methods. Most deep hashing methods are given supervised information in the form of pairwise labels or triplet labels. The current state-of-the-art deep hashing method DPSH~\cite{li2015feature}, which is based on pairwise labels, performs image feature learning and hash code learning simultaneously by maximizing the likelihood of pairwise similarities. Inspired by DPSH~\cite{li2015feature}, we propose a triplet label based deep hashing method which aims to maximize the likelihood of the given triplet labels. Experimental results show that our method outperforms all the baselines on CIFAR-10 and NUS-WIDE datasets, including the state-of-the-art method DPSH~\cite{li2015feature} and all the previous triplet label based deep hashing methods.
In this paper, we construct a partially hyperbolic skew-product diffeomorphism $f$ on $\mathbb{T}^3$, such that $f$ is accessible and chain transitive, but not transitive.
Neuromorphic chip refers to an unconventional computing architecture that is modelled on biological brains. It is ideally suited for processing sensory data for intelligence computing, decision-making or context cognition. Despite rapid development, conventional artificial synapses exhibit poor connection flexibility and require separate data acquisition circuitry, resulting in limited functionalities and significant hardware redundancy. Here we report a novel light-stimulated artificial synapse based on a graphene-nanotube hybrid phototransistor that can directly convert optical stimuli into a "neural image" for further neuronal analysis. Our optically-driven synapses involve multiple steps of plasticity mechanisms and importantly exhibit flexible tuning of both short- and long-term plasticity. Furthermore, our neuromorphic phototransistor can take multiple pre-synaptic light stimuli via wavelength-division multiplexing and allows advanced optical processing through charge-trap-mediated optical coupling. The capability of complex neuromorphic functionalities in a simple silicon-compatible device paves the way for novel neuromorphic computing architectures involving photonics.
Flexible metal oxide/graphene oxide hybrid multi-gate neuron transistors were fabricated on flexible graphene substrates. Dendritic integrations in both spatial and temporal modes were successfully emulated, and spatiotemporal correlated logics were obtained. A proof-of-principle visual system model for emulating lobula giant motion detector neuron was investigated. Our results are of great interest for flexible neuromorphic cognitive systems.
Pulsed lasers operating in the 2-5 μm band are important for a wide range of applications in sensing, spectroscopy, imaging and communications. Despite recent advances with mid-infrared gain media, the lack of a capable pulse generation mechanism, i.e. a passive optical switch, remains a significant technological challenge. Here we show that mid-infrared optical response of Dirac states in crystalline Cd3As2, a three-dimensional topological Dirac semimetal (TDS), constitutes an ideal ultrafast optical switching mechanism for the 2-5 μm range. Significantly, fundamental aspects of the photocarrier processes, such as relaxation time scales, are found to be flexibly controlled through element doping, a feature crucial for the development of convenient mid-infrared ultrafast sources. Although various exotic physical phenomena have been uncovered in three-dimensional TDS systems, our findings show for the first time that this emerging class of quantum materials can be harnessed to fill a long known gap in the field of photonics.
Van der Waals junctions of two-dimensional materials with an atomically sharp interface open up unprecedented opportunities to design and study functional heterostructures. Semiconducting transition metal dichalcogenides have shown tremendous potential for future applications due to their unique electronic properties and strong light-matter interaction. However, many important optoelectronic applications, such as broadband photodetection, are severely hindered by their limited spectral range and reduced light absorption. Here, we present a p-g-n heterostructure formed by sandwiching graphene with a gapless bandstructure and wide absorption spectrum in an atomically thin p-n junction to overcome these major limitations. We have successfully demonstrated a MoS2-graphene-WSe2 heterostructure for broadband photodetection in the visible to short-wavelength infrared range at room temperature that exhibits competitive device performance, including a specific detectivity of up to 1011 Jones in the near-infrared region. Our results pave the way toward the implementation of atomically thin heterostructures for broadband and sensitive optoelectronic applications.
One of the basic assumptions in organic field-effect transistors, the most fundamental device unit in organic electronics, is that charge transport occurs two-dimensionally in the first few molecular layers near the dielectric interface. Although the mobility of bulk organic semiconductors has increased dramatically, direct probing of intrinsic charge transport in the two-dimensional limit has not been possible due to excessive disorders and traps in ultrathin organic thin films. Here, highly ordered mono- to tetra-layer pentacene crystals are realized by van der Waals (vdW) epitaxy on hexagonal BN. We find that the charge transport is dominated by hopping in the first conductive layer, but transforms to band-like in subsequent layers. Such abrupt phase transition is attributed to strong modulation of the molecular packing by interfacial vdW interactions, as corroborated by quantitative structural characterization and density functional theory calculations. The structural modulation becomes negligible beyond the second conductive layer, leading to a mobility saturation thickness of only ~3nm. Highly ordered organic ultrathin films provide a platform for new physics and device structures (such as heterostructures and quantum wells) that are not possible in conventional bulk crystals.
Two-dimensional transition metal dichalcogenides are emerging with tremendous potential in many optoelectronic applications due to their strong light-matter interactions. To fully explore their potential in photoconductive detectors, high responsivity and weak signal detection are required. Here, we present high responsivity phototransistors based on few-layer rhenium disulfide (ReS2). Depending on the back gate voltage, source drain bias and incident optical light intensity, the maximum attainable photoresponsivity can reach as high as 88,600 A W-1, which is a record value compared to other two-dimensional materials with similar device structures and two orders of magnitude higher than that of monolayer MoS2. Such high photoresponsivity is attributed to the increased light absorption as well as the gain enhancement due to the existence of trap states in the few-layer ReS2 flakes. It further enables the detection of weak signals, as successfully demonstrated with weak light sources including a lighter and limited fluorescent lighting. Our studies underscore ReS2 as a promising material for future sensitive optoelectronic applications.
Massive multiple-input multiple-output (MIMO) is widely recognized as a promising technology for future 5G wireless communication systems. To achieve the theoretical performance gains in massive MIMO systems, accurate channel state information at the transmitter (CSIT) is crucial. Due to the overwhelming pilot signaling and channel feedback overhead, however, conventional downlink channel estimation and uplink channel feedback schemes might not be suitable for frequency-division duplexing (FDD) massive MIMO systems. In addition, these two topics are usually separately considered in the literature. In this paper, we propose a joint channel training and feedback scheme for FDD massive MIMO systems. Specifically, we firstly exploit the temporal correlation of time-varying channels to propose a differential channel training and feedback scheme, which simultaneously reduces the overhead for downlink training and uplink feedback. We next propose a structured compressive sampling matching pursuit (S-CoSaMP) algorithm to acquire a reliable CSIT by exploiting the structured sparsity of wireless MIMO channels. Simulation results demonstrate that the proposed scheme can achieve substantial reduction in the training and feedback overhead.
van der Waals (vdW) heterojunctions formed by two-dimensional (2D) materials have attracted tremendous attention due to their excellent electrical/optical properties and device applications. However, current 2D heterojunctions are largely limited to atomic crystals, and hybrid organic/inorganic structures are rarely explored. Here, we fabricate hybrid 2D heterostructures with p-type dioctylbenzothienobenzothiophene (C8-BTBT) and n-type MoS2. We find that few-layer C8-BTBT molecular crystals can be grown on monolayer MoS2 by vdW epitaxy, with pristine interface and controllable thickness down to monolayer. The operation of the C8-BTBT/MoS2 vertical heterojunction devices is highly tunable by bias and gate voltages between three different regimes: interfacial recombination, tunneling and blocking. The pn junction shows diode-like behavior with rectifying ratio up to 105 at the room temperature. Our devices also exhibit photovoltaic responses with power conversion efficiency of 0.31% and photoresponsivity of 22mA/W. With wide material combinations, such hybrid 2D structures will offer possibilities for opto-electronic devices that are not possible from individual constituents.
Neuron is the most important building block in our brain, and information processing in individual neuron involves the transformation of input synaptic spike trains into an appropriate output spike train. Hardware implementation of neuron by individual ionic/electronic hybrid device is of great significance for enhancing our understanding of the brain and solving sensory processing and complex recognition tasks. Here, we provide a proof-of-principle artificial neuron based on a proton conducting graphene oxide (GO) coupled oxide-based electric-double-layer (EDL) transistor with multiple driving inputs and one modulatory input terminal. Paired-pulse facilitation, dendritic integration and orientation tuning were successfully emulated. Additionally, neuronal gain control (arithmetic) in the scheme of rate coding is also experimentally demonstrated. Our results provide a new-concept approach for building brain-inspired cognitive systems.
We show that by combining high-k dielectric substrate and high density of charge carriers, Coulomb impurity can be effectively screened, leading to an unprecedented room-temperature mobility of ~150cm2/Vs in monolayer MoS2. The high sample quality enables us to quantitatively extract the mobility components limited by Coulomb impurities, intrinsic and surface optical phonons, and study their scaling with temperature, carrier density and dielectric constant. The excellent agreement between our theoretical analysis and experimental data demonstrates unambiguously that room-temperature phonon-limited transport is achieved in monolayer MoS2, which is a necessary factor for electronic device applications.
The combination of high-quality Al2O3 dielectric and thiol chemistry passivation can effectively reduce the density of interface traps and Coulomb impurities of WS2, leading to a significant improvement of the mobility and a transition of the charge transport from the insulating to the metallic regime. A record high mobility of 83 cm2/Vs (337 cm2/Vs) is reached at room temperature (low temperature) for monolayer WS2. A theoretical model for electron transport is also developed.