SymFET: A Proposed Symmetric Graphene Tunneling Field Effect Transistor

In this work, an analytical model to calculate the channel potential and current-voltage characteristics in a Symmetric tunneling Field-Effect-Transistor (SymFET) is presented. The current in a SymFET flows by tunneling from an n-type graphene layer to a p-type graphene layer. A large current peak occurs when the Dirac points are aligned at a particular drain-to- source bias VDS . Our model shows that the current of the SymFET is very weakly dependent on temperature. The resonant current peak is controlled by chemical doping and applied gate bias. The on/off ratio increases with graphene coherence length and doping. The symmetric resonant peak is a good candidate for high-speed analog applications, and can enable digital logic similar to the BiSFET. Our analytical model also offers the benefit of permitting simple analysis of features such as the full-width-at-half-maximum (FWHM) of the resonant peak and higher order harmonics of the nonlinear current. The SymFET takes advantage of the perfect symmetry of the bandstructure of 2D graphene, a feature that is not present in conventional semiconductors

Effective generation of Ising interaction and cluster states in coupled microcavities

We propose a scheme for realizing the Ising spin-spin interaction and atomic cluster states utilizing trapped atoms in coupled microcavities. It is shown that the atoms can interact with each other via the exchange of virtual photons of the cavities. Through suitably tuning the parameters, an effective Ising spin-spin interaction can be generated in this optical system, which is used to produce the cluster states. This scheme does not need the preparation of initial states of atoms and cavity modes, and is insensitive to cavity decay.Comment: 11pages, 2 figures, Revtex

Non-Abelian Quantum Hall Effect in Topological Flat Bands

Inspired by recent theoretical discovery of robust fractional topological phases without a magnetic field, we search for the non-Abelian quantum Hall effect (NA-QHE) in lattice models with topological flat bands (TFBs). Through extensive numerical studies on the Haldane model with three-body hard-core bosons loaded into a TFB, we find convincing numerical evidence of a stable $\nu=1$ bosonic NA-QHE, with the characteristic three-fold quasi-degeneracy of ground states on a torus, a quantized Chern number, and a robust spectrum gap. Moreover, the spectrum for two-quasihole states also shows a finite energy gap, with the number of states in the lower energy sector satisfying the same counting rule as the Moore-Read Pfaffian state.Comment: 5 pages, 7 figure

Quantum-dot gain without inversion:Effects of dark plasmon-exciton hybridization

We propose an initial-state-dependent quantum-dot gain without population inversion in the vicinity of a resonant metallic nanoparticle. The gain originates from the hybridization of a dark plasmon-exciton and is accompanied by efficient energy transfer from the nanoparticle to the quantum dot. This hybridization of the dark plasmon-exciton, attached to the hybridization of the bright plasmon-exciton, strengthens nonlinear light-quantum emitter interactions at the nanoscale, thus the spectral overlap between the dark and the bright plasmons enhances the gain effect. This hybrid system has potential applications in ultracompact tunable quantum devices.Physics, Condensed MatterSCI(E)[email protected]

Benchmarking Robustness of Text-Image Composed Retrieval

Text-image composed retrieval aims to retrieve the target image through the composed query, which is specified in the form of an image plus some text that describes desired modifications to the input image. It has recently attracted attention due to its ability to leverage both information-rich images and concise language to precisely express the requirements for target images. However, the robustness of these approaches against real-world corruptions or further text understanding has never been studied. In this paper, we perform the first robustness study and establish three new diversified benchmarks for systematic analysis of text-image composed retrieval against natural corruptions in both vision and text and further probe textural understanding. For natural corruption analysis, we introduce two new large-scale benchmark datasets, CIRR-C and FashionIQ-C for testing in open domain and fashion domain respectively, both of which apply 15 visual corruptions and 7 textural corruptions. For textural understanding analysis, we introduce a new diagnostic dataset CIRR-D by expanding the original raw data with synthetic data, which contains modified text to better probe textual understanding ability including numerical variation, attribute variation, object removal, background variation, and fine-grained evaluation. The code and benchmark datasets are available at https://github.com/SunTongtongtong/Benchmark-Robustness-Text-Image-Compose-Retrieval.Comment: Accepted by R0-FoMo: Workshop on Robustness of Few-shot and Zero-shot Learning in Foundation Models at NeurIPS 202

The Impact of the Belt and Road Initiative Investment in Digital Connectivity and Information and Communication Technologies on Achieving the SDGs

The lion’s share of the “Belt and Road Initiative (BRI)” investment in infrastructure from the Chinese investors has gone to the energy and transportation sectors, and only a very small share to the information and communication technologies (ICT) sector. However, the ICT sector has attracted growing investment not only from the public sector but also from the private enterprises in China, and stronger interests from the stakeholders in the BRI-related countries. The existing Chinese literature shows that the current investment in ICTs as well as digital connectivity and digital economy has had some positive influence on the implementation of the Sustainable Development Goals in those recipient countries. It has helped to facilitate economic growth of the least developed countries and rural areas of middle-income countries, to promote development of small and medium-sized enterprises, to encourage digital transformation of traditional industries and green growth, to narrow down the digital gap, and to enhance digital inclusion

Fractional Quantum Hall Effect of Hard-Core Bosons in Topological Flat Bands

Recent proposals of topological flat band (TFB) models have provided a new route to realize the fractional quantum Hall effect (FQHE) without Landau levels. We study hard-core bosons with short-range interactions in two representative TFB models, one of which is the well known Haldane model (but with different parameters). We demonstrate that FQHE states emerge with signatures of even number of quasi-degenerate ground states on a torus and a robust spectrum gap separating these states from higher energy spectrum. We also establish quantum phase diagrams for the filling factor 1/2 and illustrate quantum phase transitions to other competing symmetry-breaking phases.Comment: 4 pages, 6 figure