arXiv subjects

Tianyi Zhang

Publications and source records attributed to Tianyi Zhang.

390 records · Page 22Linked to original sources

arXiv2019

Nanoscale patterning of quasiparticle band alignment

Control of atomic-scale interfaces between materials with distinct electronic structures is crucial for the design and fabrication of most electronic devices. In the case of two-dimensional (2D) materials, disparate electronic structures can be realized even within a single uniform sheet, merely by locally applying different vertical bias voltages. Indeed, it has been suggested that nanoscale electronic patterning in a single sheet can be achieved by placing the 2D material on a suitably pre-patterned substrate, exploiting the sensitivity of 2D materials to their environment via band alignment, screening or hybridization. Here, we utilize the inherently nano-structured single layer (SL) and bilayer (BL) graphene on silicon carbide to laterally tune the electrostatic gating of adjacent SL tungsten disulphide (WS$_2$) in a van der Waals heterostructure. The electronic band alignments are mapped in energy and momentum space using angle-resolved photoemission with a spatial resolution on the order of 500~nm (nanoARPES). We find that the SL WS$_2$ band offsets track the work function of the underlying SL and BL graphene, and we relate such changes to observed lateral patterns of exciton and trion luminescence from SL WS$_2$, demonstrating ultimate control of optoelectronic properties at the nanoscale.

cond-mat.mes-hall↗

arXiv2019

Nonlinear dark-field imaging of 1D defects in monolayer dichalcogenides

Extended defects with one dimensionality smaller than that of the host, such as 2D grain boundaries in 3D materials or 1D grain boundaries in 2D materials, can be particularly damaging since they directly impede the transport of charge, spin or heat, and can introduce a metallic character into otherwise semiconducting systems. Unfortunately, a technique to rapidly and non-destructively image 1D defects in 2D materials is lacking. Scanning transmission electron microscopy (STEM), Raman, photoluminescence and nonlinear optical spectroscopies, are all extremely valuable, but current implementations suffer from low throughput and a destructive nature (STEM) or limitations in their unambiguous sensitivity at the nanoscale. Here we demonstrate that dark-field second harmonic generation (SHG) microscopy can rapidly, efficiently, and non-destructively probe grain boundaries and edges in monolayer dichalcogenides (i.e. MoSe2, MoS2 and WS2). Dark-field SHG efficiently separates the spatial components of the emitted light and exploits interference effects from crystal domains of different orientations to localize grain boundaries and edges as very bright 1D patterns through a Cerenkov-type SHG emission. The frequency dependence of this emission in MoSe2 monolayers is explained in terms of plasmon-enhanced SHG related to the defects metallic character. This new technique for nanometer-scale imaging of the grain structure, domain orientation and localized 1D plasmons in 2D different semiconductors, thus enables more rapid progress towards both applications and fundamental materials discoveries.

cond-mat.mes-hall↗

arXiv2019

Active Inductive Logic Programming for Code Search

Modern search techniques either cannot efficiently incorporate human feedback to refine search results or to express structural or semantic properties of desired code. The key insight of our interactive code search technique ALICE is that user feedback could be actively incorporated to allow users to easily express and refine search queries. We design a query language to model the structure and semantics of code as logic facts. Given a code example with user annotations, ALICE automatically extracts a logic query from features that are tagged as important. Users can refine the search query by labeling one or more examples as desired (positive) or irrelevant (negative). ALICE then infers a new logic query that separates the positives from negative examples via active inductive logic programming. Our comprehensive and systematic simulation experiment shows that ALICE removes a large number of false positives quickly by actively incorporating user feedback. Its search algorithm is also robust to noise and user labeling mistakes. Our choice of leveraging both positive and negative examples and the nested containment structure of selected code is effective in refining search queries. Compared with an existing technique, Critics, ALICE does not require a user to manually construct a search pattern and yet achieves comparable precision and recall with fewer search iterations on average. A case study with users shows that ALICE is easy to use and helps express complex code patterns.

cs.SE↗

arXiv2019

Dark-Exciton-Mediated Fano Resonance from a Single Gold Nanostructure Deposited on Monolayer WS2 at Room Temperature

Strong spatial confinement and highly reduced dielectric screening provide monolayer transition metal dichalcogenides (TMDCs) with strong many-body effects, thereby possessing optically forbidden excitonic states (i.e., dark excitons) at room temperature. Herein, we explore the interaction of surface plasmons with dark excitons in hybrid systems consisting of stacked gold nanotriangles (AuNTs) and monolayer WS2. We observe a narrow Fano resonance when the hybrid system is surrounded by water, and we attribute the narrowing of the spectral Fano linewidth to the plasmon-enhanced decay of dark K-K excitons. Our results reveal that dark excitons in monolayer WS2 can strongly modify Fano resonances in hybrid plasmon-exciton systems and can be harnessed for novel optical sensors and active nanophotonic devices.

physics.optics↗

arXiv2018

BadLink: Combining Graph and Information-Theoretical Features for Online Fraud Group Detection

Frauds severely hurt many kinds of Internet businesses. Group-based fraud detection is a popular methodology to catch fraudsters who unavoidably exhibit synchronized behaviors. We combine both graph-based features (e.g. cluster density) and information-theoretical features (e.g. probability for the similarity) of fraud groups into two intuitive metrics. Based on these metrics, we build an extensible fraud detection framework, BadLink, to support multimodal datasets with different data types and distributions in a scalable way. Experiments on real production workload, as well as extensive comparison with existing solutions demonstrate the state-of-the-art performance of BadLink, even with sophisticated camouflage traffic.

cs.CR↗

arXiv2018

TCP Decoupling for Next Generation Communication System

In traditional networks, interfaces of network nodes are duplex. But, emerging communication technologies such as visible light communication, millimeter-wave communications, can only provide a unidirectional interface when cost is limited. It's urgent to find effective solutions to utilize such new unidirectional communication skills. Decoupling implies separating one single resource to two independent resources. This idea can be applied at physical layer, link layer, network layer, even transport layer. TCP decoupling is an end to end solution provided at transport layer. With decoupled TCP, two distinct unidirectional path can be created to meet the requirements of reliable information transfer. However, it is not an easy task to decouple a bidirectional logical path at transport layer. In this paper, we dwell on the idea of TCP decoupling. Advantages of decoupling at transport layer are analyzed also. In addition, an experiment is carried out to figure out how to implement a decouple TCP. Our results show decoupling at transport layer is possible and the modified protocol is available.

cs.NI↗

arXiv2018

Decoupled Spatial Neural Attention for Weakly Supervised Semantic Segmentation

Weakly supervised semantic segmentation receives much research attention since it alleviates the need to obtain a large amount of dense pixel-wise ground-truth annotations for the training images. Compared with other forms of weak supervision, image labels are quite efficient to obtain. In our work, we focus on the weakly supervised semantic segmentation with image label annotations. Recent progress for this task has been largely dependent on the quality of generated pseudo-annotations. In this work, inspired by spatial neural-attention for image captioning, we propose a decoupled spatial neural attention network for generating pseudo-annotations. Our decoupled attention structure could simultaneously identify the object regions and localize the discriminative parts which generates high-quality pseudo-annotations in one forward path. The generated pseudo-annotations lead to the segmentation results which achieve the state-of-the-art in weakly-supervised semantic segmentation.

cs.CV↗

arXiv2018

An Improved Algorithm for Incremental DFS Tree in Undirected Graphs

Depth first search (DFS) tree is one of the most well-known data structures for designing efficient graph algorithms. Given an undirected graph $G=(V,E)$ with $n$ vertices and $m$ edges, the textbook algorithm takes $O(n+m)$ time to construct a DFS tree. In this paper, we study the problem of maintaining a DFS tree when the graph is undergoing incremental updates. Formally, we show: Given an arbitrary online sequence of edge or vertex insertions, there is an algorithm that reports a DFS tree in $O(n)$ worst case time per operation, and requires $O\left(\min\{m \log n, n^2\}\right)$ preprocessing time. Our result improves the previous $O(n \log^3 n)$ worst case update time algorithm by Baswana et al. and the $O(n \log n)$ time by Nakamura and Sadakane, and matches the trivial $Ω(n)$ lower bound when it is required to explicitly output a DFS tree. Our result builds on the framework introduced in the breakthrough work by Baswana et al., together with a novel use of a tree-partition lemma by Duan and Zhan, and the celebrated fractional cascading technique by Chazelle and Guibas.

cs.DS↗

arXiv2017

Tunable Resonance Coupling in Single Si Nanoparticle-Monolayer WS2 Structures

Two-dimensional semiconducting transition metal dichalcogenides (TMDCs) are extremely attractive materials for optoelectronic applications in the visible and near-IR range. Here, we address for the first time to the best of our knowledge the issue of resonance coupling in hybrid exciton-polariton structures based on single Si nanoparticles coupled to monolayer WS2. We predict a transition from weak to strong coupling regime , with a Rabi splitting energy exceeding 200 meV for a Si nanoparticle covered by monolayer WS 2 at the magnetic optical Mie resonance. This large transition is achieved due to the symmetry of magnetic dipole Mie mode and by changing the surrounding dielectric material from air to water. The prediction is based on the experimental estimation of TMDC dipole moment variation obtained from measured photoluminescence (PL) spectra of WS2 monolayers in different solvents. An ability of such a system to tune the resonance coupling is realized experimentally for optically resonant spherical Si nanoparticles placed on a WS2 monolayer. The Rabi splitting energy obtained for this scenario increases from 49.6 meV to 86.6 meV after replacing air by water. Our findings pave the way to develop high-efficiency optoelectronic, nanophotonic and quantum optical devices.

physics.optics↗

arXiv2017

Exploring home robot capabilities by medium fidelity prototyping

In order for autonomous robots to be able to support people's well-being in homes and everyday environments, new interactive capabilities will be required, as exemplified by the soft design used for Disney's recent robot character Baymax in popular fiction. Home robots will be required to be easy to interact with and intelligent--adaptive, fun, unobtrusive and involving little effort to power and maintain--and capable of carrying out useful tasks both on an everyday level and during emergencies. The current article adopts an exploratory medium fidelity prototyping approach for testing some new robotic capabilities in regard to recognizing people's activities and intentions and behaving in a way which is transparent to people. Results are discussed with the aim of informing next designs.

cs.RO↗

arXiv2016

Improved distance sensitivity oracles via tree partitioning

We introduce an improved structure of distance sensitivity oracle (DSO). The task is to pre-process a non-negatively weighted graph so that a data structure can quickly answer replacement path length for every triple of source, terminal and failed vertex. The previous best algorithm constructs in time $\tilde{O}(mn)$ a distance sensitivity oracle of size $O(n^2\log n)$ that processes queries in $O(1)$ time. As an improvement, our oracle takes up $O(n^2)$ space, while preserving $O(1)$ query efficiency and $\tilde{O}(mn)$ preprocessing time. One should notice that space complexity and query time of our novel data structure are asymptotically optimal.

cs.DS↗

arXiv2014

$C^0$ Discontinuous Galerkin Methods for a Kirchhoff Plate Contact Problem

Discontinuous Galerkin (DG) methods are considered for solving a plate contact problem, which is a 4th-order elliptic variational inequality of second kind. Numerous $C^0$ DG schemes for the Kirchhoff plate bending problem are extended to the variational inequality. Properties of the DG methods, such as consistency and stability, are studied, and optimal order error estimates are derived. A numerical example is presented to show the performance of the DG methods; the numerical convergence orders confirm the theoretical prediction.

math.NA↗