arXiv subjects

Yujun Zhang

Publications and source records attributed to Yujun Zhang.

43 records · Page 3Linked to original sources

arXiv2019

Magnetic order induced polarization anomaly of Raman scattering in 2D magnet CrI$_3$

The recent discovery of 2D magnets has revealed various intriguing phenomena due to the coupling between spin and other degree of freedoms (such as helical photoluminescence, nonreciprocal SHG). Previous research on the spin-phonon coupling effect mainly focuses on the renormalization of phonon frequency. Here we demonstrate that the Raman polarization selection rules of optical phonons can be greatly modified by the magnetic ordering in 2D magnet CrI$_3$. For monolayer samples, the dominant A$\rm_{1g}$ peak shows abnormally high intensity in the cross polarization channel at low temperature, which is forbidden by the selection rule based on the lattice symmetry. While for bilayer, this peak is absent in the cross polarization channel for the layered antiferromagnetic (AFM) state and reappears when it is tuned to the ferromagnetic (FM) state by an external magnetic field. Our findings shed light on exploring the emergent magneto-optical effects in 2D magnets.

cond-mat.mes-hall↗

arXiv2019

BTS-DSN: Deeply Supervised Neural Network with Short Connections for Retinal Vessel Segmentation

Background and Objective: The condition of vessel of the human eye is an important factor for the diagnosis of ophthalmological diseases. Vessel segmentation in fundus images is a challenging task due to complex vessel structure, the presence of similar structures such as microaneurysms and hemorrhages, micro-vessel with only one to several pixels wide, and requirements for finer results. Methods:In this paper, we present a multi-scale deeply supervised network with short connections (BTS-DSN) for vessel segmentation. We used short connections to transfer semantic information between side-output layers. Bottom-top short connections pass low level semantic information to high level for refining results in high-level side-outputs, and top-bottom short connection passes much structural information to low level for reducing noises in low-level side-outputs. In addition, we employ cross-training to show that our model is suitable for real world fundus images. Results: The proposed BTS-DSN has been verified on DRIVE, STARE and CHASE_DB1 datasets, and showed competitive performance over other state-of-the-art methods. Specially, with patch level input, the network achieved 0.7891/0.8212 sensitivity, 0.9804/0.9843 specificity, 0.9806/0.9859 AUC, and 0.8249/0.8421 F1-score on DRIVE and STARE, respectively. Moreover, our model behaves better than other methods in cross-training experiments. Conclusions: BTS-DSN achieves competitive performance in vessel segmentation task on three public datasets. It is suitable for vessel segmentation. The source code of our method is available at https://github.com/guomugong/BTS-DSN.

cs.CV↗

arXiv2019

Multiple Human Association between Top and Horizontal Views by Matching Subjects' Spatial Distributions

Video surveillance can be significantly enhanced by using both top-view data, e.g., those from drone-mounted cameras in the air, and horizontal-view data, e.g., those from wearable cameras on the ground. Collaborative analysis of different-view data can facilitate various kinds of applications, such as human tracking, person identification, and human activity recognition. However, for such collaborative analysis, the first step is to associate people, referred to as subjects in this paper, across these two views. This is a very challenging problem due to large human-appearance difference between top and horizontal views. In this paper, we present a new approach to address this problem by exploring and matching the subjects' spatial distributions between the two views. More specifically, on the top-view image, we model and match subjects' relative positions to the horizontal-view camera in both views and define a matching cost to decide the actual location of horizontal-view camera and its view angle in the top-view image. We collect a new dataset consisting of top-view and horizontal-view image pairs for performance evaluation and the experimental results show the effectiveness of the proposed method.

cs.CV↗

arXiv2019

Photoemission and Dynamical Mean Field Theory Study of Electronic Correlation in a $t_{2g}^{5}$ Metal of SrRhO$_{3}$ Thin Film

Perovskite rhodates are characterized by intermediate strengths of both electronic correlation as well as spin-orbit coupling (SOC) and usually behave as moderately correlated metals. A recent publication (Phys. Rev. B 95, 245121(2017)) on epitaxial SrRhO$_3$ thin films unexpectedly reported a bad-metallic behavior and suggested the occurrence of antiferromagnetism below 100 K. We studied this SrRhO$_3$ thin film by hard x-ray photoemission spectroscopy and found a very small density of states (DOS) at Fermi level, which is consistent with the reported bad-metallic behavior. However, this negligible DOS persists up to room temperature, which contradicts with the explanation of antiferromagnetic transition at around 100 K. We also employed electronic structure calculations within the framework of density functional theory and dynamical mean-field theory. In contrast to the experimental results, our calculations indicate metallic behavior of both bulk SrRhO$_3$ and the SrRhO$_3$ thin film. The thin film exhibits stronger correlation effects than the bulk, but the correlation effects are not sufficient to drive a transition to an insulating state. The calculated uniform magnetic susceptibility is substantially larger in the thin film than that in the bulk. The role of SOC was also investigated and only a moderate modulation of the electronic structure was observed. Hence SOC is not expected to play an important role for electronic correlation in SrRhO$_3$.

cond-mat.str-el↗

arXiv2019

Nature of carrier doping in T'-La1.8-xEu0.2SrxCuO4 studied by X-Ray Photoemission and Absorption Spectroscopy

Recently, hole-doped superconducting cuprates with the T'-structure La1.8-xEu0.2SrxCuO4 (LESCO) have attracted a lot of attention. We have performed x-ray photoemission and absorption spectroscopy measurements on as-grown and reduced T0-LESCO. Results show that electrons and holes were doped by reduction annealing and Sr substitution, respectively. However, it is shown that the system remains on the electron-doped side of the Mott insulator or that the charge-transfer gap is collapsed in the parent compound.

cond-mat.supr-con↗

arXiv2018

Raman evidence for dimerization and Mott collapse in $α$-RuCl$_3$ under pressures

We perform Raman spectroscopy studies on $α$-RuCl$_3$ at room temperature to explore its phase transitions of magnetism and chemical bonding under pressures. The Raman measurements resolve two critical pressures, about $p_1=1.1$~GPa and $p_2=1.7$~GPa, involving very different intertwining behaviors between the structural and magnetic excitations. With increasing pressures, a stacking order phase transition of $α$-RuCl$_3$ layers develops at $p_1=1.1$~GPa, indicated by the new Raman phonon modes and the modest Raman magnetic susceptibility adjustment. The abnormal softening and splitting of the Ru in-plane Raman mode provide direct evidence of the in-plane dimerization of the Ru-Ru bonds at $p_2=1.7$~GPa. The Raman susceptibility is greatly enhanced with pressure increasing and sharply suppressed after the dimerization. We propose that the system undergoes Mott collapse at $p_2=1.7$~GPa and turns into a dimerized correlated band insulator. Our studies demonstrate competitions between Kitaev physics, magnetism, and chemical bondings in Kitaev compounds.

cond-mat.str-el↗

arXiv2015

ELDA: Towards Efficient and Lightweight Detection of Cache Pollution Attacks in NDN

As a promising architectural design for future Internet, named data networking (NDN) relies on in-network caching to efficiently deliver name-based content. However, the in-network caching is vulnerable to cache pollution attacks (CPA), which can reduce cache hits by violating cache locality and significantly degrade the overall performance of NDN. To defend against CPA attacks, the most effective way is to first detect the attacks and then throttle them. Since the CPA attack itself has already imposed a huge burden on victims, to avoid exhausting the remaining resources on the victims for detection purpose, we expect a lightweight detection solution. We thus propose ELDA, an Efficient and Lightweight Detection scheme against cache pollution Attacks, in which we design a Lightweight Flajolet-Martin (LFM) sketch to monitor the interest traffic. Our analysis and simulations demonstrate that, by consuming a few computation and memory resources, ELDA can effectively and efficiently detect CPA attacks.

cs.CR↗