arXiv subjects

Meng Meng

Publications and source records attributed to Meng Meng.

25 records · Page 2Linked to original sources

arXiv2023

Magnetism and berry phase manipulation in an emergent structure of perovskite ruthenate by (111) strain engineering

The interplay among symmetry of lattices, electronic correlations, and Berry phase of the Bloch states in solids has led to fascinating quantum phases of matter. A prototypical system is the magnetic Weyl candidate SrRuO3, where designing and creating electronic and topological properties on artificial lattice geometry is highly demanded yet remains elusive. Here, we establish an emergent trigonal structure of SrRuO3 by means of heteroepitaxial strain engineering along the [111] crystallographic axis. Distinctive from bulk, the trigonal SrRuO3 exhibits a peculiar XY-type ferromagnetic ground state, with the coexistence of high-mobility holes likely from linear Weyl bands and low-mobility electrons from normal quadratic bands as carriers. The presence of Weyl nodes are further corroborated by capturing intrinsic anomalous Hall effect, acting as momentum-space sources of Berry curvatures. The experimental observations are consistent with our first-principles calculations, shedding light on the detailed band topology of trigonal SrRuO3 with multiple pairs of Weyl nodes near the Fermi level. Our findings signify the essence of magnetism and Berry phase manipulation via lattice design and pave the way towards unveiling nontrivial correlated topological phenomena.

cond-mat.str-el↗

arXiv2023

Tuning the Magnetism in Ultrathin CrxTey Films by Lattice Dimensionality

Two-dimensional (2D) magnetic transition metal compounds with atomic thickness exhibit intriguing physics in fundamental research and great potential for device applications. Understanding the correlations between their macrosopic magnetic properties and the dimensionality of microscopic magnetic exchange interactions are valuable for the designing and applications of 2D magnetic crystals. Here, using spin-polarized scanning tunneling microscopy, magnetization and magneto-transport measurements, we identify the zigzag-antiferromagnetism in monolayer CrTe2, incipient ferromagnetism in bilayer CrTe2, and robust ferromagnetism in bilayer Cr3Te4 films. Our density functional theory calculations unravel that the magnetic ordering in ultrathin CrTe2 is sensitive to the lattice parameters, while robust ferromagnetism with large perpendicular magnetic anisotropy in Cr3Te4 is stabilized through its anisotropic 3D magnetic exchange interactions.

cond-mat.mtrl-sci↗

arXiv2019

Role of disorder and correlations in metal-insulator transition in ultrathin SrVO3 films

Metallic oxide SrVO3 represents a prototype system for the study of the mechanism behind thickness-induced metal-to-insulator transition (MIT) or crossover in thin films due to its simple cubic symmetry with one electron in the 3d state in the bulk. Here we report a deviation of chemical composition and distortion of lattice structure existing in the initial 3 unit cells of SrVO3 films grown on SrTiO3 (001) from its bulk form, which shows a direct correlation to the thickness-dependent MIT. In-situ photoemission and scanning tunneling spectroscopy indicate a MIT at the critical thickness of ~3 unit cell (u.c.), which coincides with the formation of a (root2Xroot2)R45 surface reconstruction. However, atomically resolved scanning transmission electron microscopy and electron energy loss spectroscopy show depletion of Sr, change of V valence, thus implying the existence of a significant amount of oxygen vacancies in the 3 u.c. of SrVO3 near the interface. Transport and magneto-transport measurements further reveal that disorder, rather than electron correlations, is likely to be the main cause for the MIT in the SrVO3 ultrathin films.

cond-mat.str-el↗

arXiv2018

In-Session Personalization for Talent Search

Previous efforts in recommendation of candidates for talent search followed the general pattern of receiving an initial search criteria and generating a set of candidates utilizing a pre-trained model. Traditionally, the generated recommendations are final, that is, the list of potential candidates is not modified unless the user explicitly changes his/her search criteria. In this paper, we are proposing a candidate recommendation model which takes into account the immediate feedback of the user, and updates the candidate recommendations at each step. This setting also allows for very uninformative initial search queries, since we pinpoint the user's intent due to the feedback during the search session. To achieve our goal, we employ an intent clustering method based on topic modeling which separates the candidate space into meaningful, possibly overlapping, subsets (which we call intent clusters) for each position. On top of the candidate segments, we apply a multi-armed bandit approach to choose which intent cluster is more appropriate for the current session. We also present an online learning scheme which updates the intent clusters within the session, due to user feedback, to achieve further personalization. Our offline experiments as well as the results from the online deployment of our solution demonstrate the benefits of our proposed methodology.

cs.AI↗

arXiv2017

Observation of Giant Exchange Bias and Topological Hall Effect in Manganese Nitride Films

Magnetic and magneto-transport properties of manganese nitride films grown by molecular beam epitaxy have been investigated. Due to the mixed ferrimagnetic (FI) phase ($ε$-phase with TFI ~ 738 K) and the antiferromagnetic phase ($ζ$-phase with TN ~ 273 K), we observe magnetization hysteresis loops with non-zero exchange bias below TN, reaching ~ 0.22 T at 5 K. This indicates that noncollinear spins exist at the interfaces between two phases, creating a competition between interfacial Dzyaloshinskii-Moriya (DM) and exchange interactions. Strikingly, in addition to the normal Hall effect by Lorentz force and anomalous Hall effect by magnetization, we observe new contribution namely topological Hall effect below 75 K. This verifies the existence of topological spin texture, which is the consequence of competing interactions controlled by both applied field and temperature. Our work demonstrates that spintronic devices may be fabricated exploiting rich magnetic properties of different phases.

cond-mat.mtrl-sci↗

arXiv2014

Joint Video and Text Parsing for Understanding Events and Answering Queries

We propose a framework for parsing video and text jointly for understanding events and answering user queries. Our framework produces a parse graph that represents the compositional structures of spatial information (objects and scenes), temporal information (actions and events) and causal information (causalities between events and fluents) in the video and text. The knowledge representation of our framework is based on a spatial-temporal-causal And-Or graph (S/T/C-AOG), which jointly models possible hierarchical compositions of objects, scenes and events as well as their interactions and mutual contexts, and specifies the prior probabilistic distribution of the parse graphs. We present a probabilistic generative model for joint parsing that captures the relations between the input video/text, their corresponding parse graphs and the joint parse graph. Based on the probabilistic model, we propose a joint parsing system consisting of three modules: video parsing, text parsing and joint inference. Video parsing and text parsing produce two parse graphs from the input video and text respectively. The joint inference module produces a joint parse graph by performing matching, deduction and revision on the video and text parse graphs. The proposed framework has the following objectives: Firstly, we aim at deep semantic parsing of video and text that goes beyond the traditional bag-of-words approaches; Secondly, we perform parsing and reasoning across the spatial, temporal and causal dimensions based on the joint S/T/C-AOG representation; Thirdly, we show that deep joint parsing facilitates subsequent applications such as generating narrative text descriptions and answering queries in the forms of who, what, when, where and why. We empirically evaluated our system based on comparison against ground-truth as well as accuracy of query answering and obtained satisfactory results.

cs.CV↗

arXiv2004

Epidemic Spreading in Dynamic Small World Networks

In this paper, we use a series of small world networks to simulate the epidemic spreading in the real world. To make our model more similar to the real world, we employ a parameter $p_{move}$ to denote its moving probability, which corresponds with the general mobility of individuals in realistic social network. The networks keep the same small world properties when they are varying. And the SIRS model is used to simulate the disease propagation. From these simulations we see the moving probability of a small world network has a profound effect on the velocity for the spread of an infection. The quantitative results show that the characteristic time $τ$ of infection at initial stage decreases exponentially with $p_{move}$.

nlin.AO↗