arXiv subjects

Xi Zhang

Publications and source records attributed to Xi Zhang.

At least 199 records · Page 11Linked to original sources

arXiv2024

Origin of the yield stress anomaly in L12 intermetallics unveiled with physically-informed machine-learning potentials

The yield stress anomaly of L12 intermetallics such as Ni3Al or Ni3Ga is controlled by the so-called Kear-Wilsdorf lock (KWL), of which the formation and unlocking are governed by dislocation cross-slip. Despite the importance of L12 intermetallics for strengthening Ni-based superalloys, microscopic understanding of the KWL is limited. Here, molecular dynamics simulations are conducted by employing a dedicated machine-learning interatomic potential derived via physically-informed active-learning. The potential facilitates modelling of the dislocation behavior in Ni3Al with near ab initio accuracy. KWL formation and unlocking are observed and analyzed. The unlocking stress demonstrates a pronounced temperature dependence, contradicting the assumptions of existing analytical models. A phenomenological model is proposed to effectively describe the atomistic unlocking stresses and extrapolate them to the macroscopic scale. The model is general and applicable to other L12 intermetallics. The acquired knowledge of KWLs provides a deeper understanding on the origin of the yield stress anomaly.

cond-mat.mtrl-sci↗

arXiv2024

Near-Room-Temperature Field-Controllable Exchange Bias in 2D van der Waals Ferromagnet Fe3GaTe2

Exchange bias (EB) is a cornerstone of modern magnetic memory and sensing technologies. Its extension to the realm of two-dimensional (2D) van der Waals (vdW) magnets holds promise for revolutionary advancements in miniaturized and efficient atomic spintronic devices. However, the blocking temperature of EB in 2D vdW magnets is currently well below room temperature ~130 K. This study reports a robust EB phenomenon in Fe3GaTe2 thin-layer devices, which significantly increases the blocking temperature to a near-room-temperature record of 280 K. Both the bias direction and magnitude can be isothermally tuned by adjusting the field sweep range, in striking contrast to the conventional EB in ferromagnetic/antiferromagnetic (FM/AFM) bilayers. We propose an exchange spring model in which crystal defects with higher coercivity act as the pivotal pinning source for the observed EB phenomenon, deviating from the conventional FM/AFM interface mechanism. Cumulative growth of minor loops and multiple magnetization reversal paths are observed in field cycles below the saturation field, consistent with the hard FM defects behavior of our exchange spring model. These findings provide insights into the complex magnetic order in 2D ferromagnets and open new avenues for developing practical ultrathin vdW spintronic devices with EB-like properties at room temperature.

cond-mat.mes-hall↗

arXiv2024

Noninvasive magnetic detection of 2D van der Waals room-temperature ferromagnet Fe3GaTe2 using divacancy spins in SiC

Room-temperature (RT) two-dimensional (2D) van der Waals (vdW) ferromagnets hold immense promise for next-generation spintronic devices for information storage and processing. To achieve high-density energy-efficient spintronic devices, it is essential to understand local magnetic properties of RT 2D vdW magnets. In this work, we realize noninvasive in situ magnetic detection in vdW-layered ferromagnet Fe3GaTe2 using divacancy spins quantum sensor in silicon carbide (SiC) at RT. The structural features and magnetic properties of the Fe3GaTe2 are characterized utilizing Raman spectrum, magnetization and magneto-transport measurements. Further detailed analysis of temperature- and magnetic field-dependent optically detected magnetic resonances of the PL6 divacancy near the Fe3GaTe2 reveal that, the Curie temperature (Tc) of Fe3GaTe2 is ~360K, and the magnetization increases with external magnetic fields. Additionally, spin relaxometry technology is employed to probe the magnetic fluctuations of Fe3GaTe2, revealing a peak in the spin relaxation rate around Tc. These experiments give insights into the intriguing local magnetic properties of 2D vdW RT ferromagnet Fe3GaTe2 and pave the way for the application of SiC quantum sensors in noninvasive in situ magnetic detection of related 2D vdW magnets.

quant-ph↗

arXiv2024

Mobile-Agent-v2: Mobile Device Operation Assistant with Effective Navigation via Multi-Agent Collaboration

Mobile device operation tasks are increasingly becoming a popular multi-modal AI application scenario. Current Multi-modal Large Language Models (MLLMs), constrained by their training data, lack the capability to function effectively as operation assistants. Instead, MLLM-based agents, which enhance capabilities through tool invocation, are gradually being applied to this scenario. However, the two major navigation challenges in mobile device operation tasks, task progress navigation and focus content navigation, are significantly complicated under the single-agent architecture of existing work. This is due to the overly long token sequences and the interleaved text-image data format, which limit performance. To address these navigation challenges effectively, we propose Mobile-Agent-v2, a multi-agent architecture for mobile device operation assistance. The architecture comprises three agents: planning agent, decision agent, and reflection agent. The planning agent generates task progress, making the navigation of history operations more efficient. To retain focus content, we design a memory unit that updates with task progress. Additionally, to correct erroneous operations, the reflection agent observes the outcomes of each operation and handles any mistakes accordingly. Experimental results indicate that Mobile-Agent-v2 achieves over a 30% improvement in task completion compared to the single-agent architecture of Mobile-Agent. The code is open-sourced at https://github.com/X-PLUG/MobileAgent.

cs.CL↗

arXiv2024

TransGNN: Harnessing the Collaborative Power of Transformers and Graph Neural Networks for Recommender Systems

Graph Neural Networks (GNNs) have emerged as promising solutions for collaborative filtering (CF) through the modeling of user-item interaction graphs. The nucleus of existing GNN-based recommender systems involves recursive message passing along user-item interaction edges to refine encoded embeddings. Despite their demonstrated effectiveness, current GNN-based methods encounter challenges of limited receptive fields and the presence of noisy "interest-irrelevant" connections. In contrast, Transformer-based methods excel in aggregating information adaptively and globally. Nevertheless, their application to large-scale interaction graphs is hindered by inherent complexities and challenges in capturing intricate, entangled structural information. In this paper, we propose TransGNN, a novel model that integrates Transformer and GNN layers in an alternating fashion to mutually enhance their capabilities. Specifically, TransGNN leverages Transformer layers to broaden the receptive field and disentangle information aggregation from edges, which aggregates information from more relevant nodes, thereby enhancing the message passing of GNNs. Additionally, to capture graph structure information effectively, positional encoding is meticulously designed and integrated into GNN layers to encode such structural knowledge into node attributes, thus enhancing the Transformer's performance on graphs. Efficiency considerations are also alleviated by proposing the sampling of the most relevant nodes for the Transformer, along with two efficient sample update strategies to reduce complexity. Furthermore, theoretical analysis demonstrates that TransGNN offers increased expressiveness compared to GNNs, with only a marginal increase in linear complexity. Extensive experiments on five public datasets validate the effectiveness and efficiency of TransGNN.

cs.LG↗

arXiv2024

Rigidity of eigenvalues of shrinking Ricci solitons

In this paper, we study the rigidity of eigenvalues of shring Ricci solitons. It is known that the drifted Laplacian on shrinking Ricci solitons has discrete spectrum, its eigenvalues have a lower bound and a rigidity result holds. Firstly, we show that if the $n^\text{th}$ eigenvalue is close to this lower bound, then the $n$-soliton must be the trivial Gaussian soliton $\mathbb{R}^n$. Secondly, we show similar results for the $(n-1)^\text{th}$ and $(n-2)^\text{th}$ eigenvalue under a non-collapsing condition. Lastly, we give an alomost rigidity for the $k^\text{th}$ eigenvalue with general $k$. Part of our results could be viewed as an soliton (could be noncompact) analog of Theorem 1.1 (which only holds for compact manifolds) in Peterson (Invent. Math. 138 (1999): 1-21).

math.DG↗

arXiv2024

Surprising pressure-induced magnetic transformations from Helimagnetic order to Antiferromagnetic state in NiI2

Interlayer magnetic interactions play a pivotal role in determining the magnetic arrangement within van der Waals (vdW) magnets, and the remarkable tunability of these interactions through applied pressure further enhances their significance. Here, we investigate NiI2 flakes, a representative vdW magnet, under hydrostatic pressures up to 11 GPa. We reveal a notable increase in magnetic transition temperatures for both helimagnetic and antiferromagnetic states, and find that a reversible transition from helimagnetic to antiferromagnetic (AFM) phases at approximately 7 GPa challenges established theoretical and experimental expectations. While the increase in transition temperature aligns with pressure-enhanced overall exchange interaction strengths, we identify the significant role of the second-nearest neighbor interlayer interaction, which competes with intra-layer frustration and favors the AFM state as demonstrated in the Monte Carlo simulations. Experimental and simulated results converge on the existence of an intermediate helimagnetic ordered state in NiI2 before transitioning to the AFM state. These findings underscore the pivotal role of interlayer interactions in shaping the magnetic ground state, providing fresh perspectives for innovative applications in nanoscale magnetic device design.

cond-mat.mtrl-sci↗

arXiv2024

Two-Dimensional Models of Microphysical Clouds on Hot Jupiters I: Cloud Properties

We present a new two-dimensional, bin-scheme microphysical model of cloud formation in the atmospheres of hot Jupiters that includes the effects of longitudinal gas and cloud transport. We predict cloud particle size distributions as a function of planetary longitude and atmospheric height for a grid of hot Jupiters with equilibrium temperatures ranging from 1000-2100 K. The predicted 2D cloud distributions vary significantly from models that do not consider horizontal cloud transport and we discuss the microphysical and transport timescales that give rise to the differences in 2D versus 1D models. We find that the horizontal advection of cloud particles increases the cloud formation efficiency for nearly all cloud species and homogenizes cloud distributions across the planets in our model grid. In 2D models, certain cloud species are able to be transported and survive on the daysides of hot Jupiters in cases where 1D models would not predict the existence of clouds. We demonstrate that the depletion of condensible gas species varies as a function of longitude and atmospheric height across the planet, which impacts the resultant gas-phase chemistry. Finally, we discuss various model sensitivities including the sensitivity of cloud properties to microphysical parameters, which we find to be substantially less than the sensitivity to the atmospheric thermal structure and horizontal and vertical transport of condensible material.

astro-ph.EP↗

arXiv2024

Easy-to-configure zero-dimensional valley-chiral modes in a graphene point junction

The valley degree of freedom in 2D materials can be manipulated for low-dissipation quantum electronics called valleytronics. At the boundary between two regions of bilayer graphene with different atomic or electrostatic configuration, valley-polarized current has been realized. However, the demanding fabrication and operation requirements limit device reproducibility and scalability toward more advanced valleytronics circuits. We demonstrate a new device architecture of a point junction where a valley-chiral 0D PN junction is easily configured, switchable, and capable of carrying valley current with an estimated polarization of ~80%. This work provides a new building block in manipulating valley quantum numbers and scalable valleytronics.

cond-mat.mes-hall↗

arXiv2024

Electron Collimation in Twisted Bilayer Graphene via Gate-defined Moiré Barriers

Electron collimation via a graphene pn-junction allows electrostatic control of ballistic electron trajectories akin to that of an optical circuit. Similar manipulation of novel correlated electronic phases in twisted-bilayer graphene (tBLG) can provide additional probes to the underlying physics and device components towards advanced quantum electronics. In this work, we demonstrate collimation of the electron flow via gate-defined moiré barriers in a tBLG device, utilizing the band-insulator gap of the moiré superlattice. A single junction can be tuned to host a chosen combination of conventional pseudo barrier and moiré tunnel barriers, from which we demonstrate improved collimation efficiency. By measuring transport through two consecutive moiré collimators separated by 1 um, we demonstrate evidence of electron collimation in tBLG in the presence of realistic twist-angle inhomogeneity.

cond-mat.mes-hall↗

arXiv2024

Global Chemical Transport on Hot Jupiters: Insights from 2D VULCAN photochemical model

The atmospheric dynamics of tidally-locked hot Jupiters is characterized by strong equatorial winds. Understanding the interaction between global circulation and chemistry is crucial in atmospheric studies and interpreting observations. Two-dimensional (2D) photochemical transport models shed light on how the atmospheric composition depends on circulation. In this paper, we introduce the 2D photochemical (horizontal and vertical) transport model, VULCAN 2D, which improves on the pseudo-2D approaches by allowing for non-uniform zonal winds. We extensively validate our VULCAN 2D with analytical solutions and benchmark comparisons. Applications to HD 189733 b and HD 209458 b reveal a transition in mixing regimes: horizontal transport predominates below $\sim$0.1 mbar while vertical mixing is more important at higher altitudes above 0.1 mbar. Motivated by the previously inferred carbon-rich atmosphere, we find that HD 209458 b with super-solar carbon-to-oxygen ratio (C/O) exhibits pronounced C$_2$H$_4$ absorption on the morning limb but not on the evening limb, owing to horizontal transport from the nightside. We discuss when a pseudo-2D approach is a valid assumption and its inherent limitations. Finally, we demonstrate the effect of horizontal transport in transmission observations and its impact on the morning-evening limb asymmetry with synthetic spectra, highlighting the need to consider global transport when interpreting exoplanet atmospheres.

astro-ph.EP↗

arXiv2024

A Differential Geometric View and Explainability of GNN on Evolving Graphs

Graphs are ubiquitous in social networks and biochemistry, where Graph Neural Networks (GNN) are the state-of-the-art models for prediction. Graphs can be evolving and it is vital to formally model and understand how a trained GNN responds to graph evolution. We propose a smooth parameterization of the GNN predicted distributions using axiomatic attribution, where the distributions are on a low-dimensional manifold within a high-dimensional embedding space. We exploit the differential geometric viewpoint to model distributional evolution as smooth curves on the manifold. We reparameterize families of curves on the manifold and design a convex optimization problem to find a unique curve that concisely approximates the distributional evolution for human interpretation. Extensive experiments on node classification, link prediction, and graph classification tasks with evolving graphs demonstrate the better sparsity, faithfulness, and intuitiveness of the proposed method over the state-of-the-art methods.

cs.LG↗

arXiv2024

Nightside clouds and disequilibrium chemistry on the hot Jupiter WASP-43b

Hot Jupiters are among the best-studied exoplanets, but it is still poorly understood how their chemical composition and cloud properties vary with longitude. Theoretical models predict that clouds may condense on the nightside and that molecular abundances can be driven out of equilibrium by zonal winds. Here we report a phase-resolved emission spectrum of the hot Jupiter WASP-43b measured from 5-12 $μ$m with JWST's Mid-Infrared Instrument (MIRI). The spectra reveal a large day-night temperature contrast (with average brightness temperatures of 1524$\pm$35 and 863$\pm$23 Kelvin, respectively) and evidence for water absorption at all orbital phases. Comparisons with three-dimensional atmospheric models show that both the phase curve shape and emission spectra strongly suggest the presence of nightside clouds which become optically thick to thermal emission at pressures greater than ~100 mbar. The dayside is consistent with a cloudless atmosphere above the mid-infrared photosphere. Contrary to expectations from equilibrium chemistry but consistent with disequilibrium kinetics models, methane is not detected on the nightside (2$σ$ upper limit of 1-6 parts per million, depending on model assumptions).

astro-ph.EP↗

arXiv2024

The Fate of Simple Organics on Titan's Surface: A Theoretical Perspective

Atmospheric photochemistry on Titan continuously transforms methane and nitrogen gases into various organic compounds. This study explores the fate of these molecules when they land on Titan's surface. Our analytical exploration reveals that most simple organics found in Titan's atmosphere, including all nitriles, triple-bonded hydrocarbons, and benzene, land as solids. Only a few compounds are in the liquid phase, while only ethylene remains gaseous. For the simple organics that land as solids, we further examine their interactions with Titan's lake liquids. Utilizing principles of buoyancy, we found that flotation can be achieved via porosity-induced (25-60% porosity) or capillary force-induced buoyancy for HCN ices on ethane-rich lakes. Otherwise, these ices would sink and become lakebed sediments. By evaluating the timescale of flotation, our findings suggest that porosity-induced flotation of millimeter-sized and larger sediments is the only plausible mechanism for floating solids to explain the transient "magic islands" phenomena on Titan's lakes.

astro-ph.EP↗

arXiv2023

Anomalous exchange bias effect in ferromagnetic VI3 flakes

The exchange bias (EB) effect, pivotal in magnetic data storage and sensing devices, has been observed not only in interfacial regions but also in intrinsic ferromagnetic materials. Here, we've uncovered a robust and stable exchange bias effect within the layered van der Waals (vdW) ferromagnet VI3 employing magnetic circular dichroism microscopy. At 10 K, we observed a significant exchange field of approximately 0.1 T, accompanied by random shifts (positive or negative relative to zero magnetic field) after zero-field cooling. Notably, this effect is effectively controllable after field cooling, with shift direction opposing the applied magnetic field. The presence of strong magnetic anisotropic energy within VI3 results in larger coercivity-bound magnetic domains. These domains dictate the neighboring ferromagnetic alignment and induce shifts in the hysteresis loop. Our study not only contributes to comprehending fundamental nanoscale magnetic interactions but also sheds light on emergent phenomena within layered van der Waals magnets.

cond-mat.mtrl-sci↗

arXiv2023

Detecting bulk carbon ferromagnetism in graphene multi-edge structure

The emergence of bulk carbon ferromagnetism is long-expected over years. At nanoscale, carbon ferromagnetism was detected by analyzing the magnetic edge states via scanning tunneling microscopy(STM), and its origin can be explained by local redistribution of electron wave function. In larger scale, carbon ferromagnetism can be created by deliberately producing defects in graphite, and detected by macroscopic technical magnetization. Meanwhile, it becomes crucial to determine that the detected magnetization is originated from carbon rather than from magnetic impurities. One solution is X-ray magnetic circular dichroism (XMCD). Nonetheless, a reproducible, full section of XMCD spectrum across C-1s absorption energy has not appeared yet, which should be decisive for assuring the indisputable existence of bulk carbon ferromagnetism. Besides, the lack of direct observation on the atomic structure of the ferromagnetic carbon leaves the structural origin of its ferromagnetism still in mist. In this work, for detecting bulk carbon ferromagnetism, we managed to grow all-carbon film consisting of vertically aligned graphene multi-edge (VGME), which wove into a three-dimensional hyperfine-porous network. Magnetization (M-H) curves and XMCD spectra co-confirmed bulk carbon ferromagnetism of VGME at room temperature, with the average unit magnetic momentum of ~0.0006 miuB/atom. The influence of magnetic impurities on magnetization was excluded by both absorption spectra and inductively coupled plasma mass spectrometry measurements. The spin transfer behavior also verified the long-range and robust feature of the bulk carbon ferromagnetism. Our work provides direct evidence of elementary resolved bulk carbon ferromagnetism at room temperature and clarifies its origin from pi-electrons at graphene edges.

cond-mat.mtrl-sci↗

arXiv2023

The Inhomogeneity Effect III: Weather Impacts on the Heat Flow of Hot Jupiters

The interior flux of a giant planet impacts atmospheric motion, and the atmosphere dictates the interior's cooling. Here we use a non-hydrostatic general circulation model (Simulating Nonhydrostatic Atmospheres on Planets, SNAP) coupled with a multi-stream multi-scattering radiative module (High-performance Atmospheric Radiation Package, HARP) to simulate the weather impacts on the heat flow of hot Jupiters. We found that the vertical heat flux is primarily transported by convection in the lower atmosphere and regulated by dynamics and radiation in the overlying ``radiation-circulation" zone. The temperature inversion occurs on the dayside and reduces the upward radiative flux. The atmospheric dynamics relay the vertical heat transport until the radiation becomes efficient in the upper atmosphere. The cooling flux increases with atmospheric drag due to increased day-night contrast and spatial inhomogeneity. The temperature dependence of the infrared opacity greatly amplifies the opacity inhomogeneity. Although atmospheric circulation could transport heat downward in a narrow region above the radiative-convective boundary, the opacity inhomogeneity effect overcomes the dynamical effect and leads to a larger overall interior cooling than the local simulations with the same interior entropy and stellar flux. The enhancement depends critically on the equilibrium temperature, drag, and atmospheric opacity. In a strong-drag atmosphere hotter than 1600 K, a significant inhomogeneity effect in three-dimensional (3D) models can boost interior cooling several-fold compared to the 1D radiative-convective equilibrium models. This study confirms the analytical argument of the inhomogeneity effect in Zhang (2023a,b). It highlights the importance of using 3D atmospheric models in understanding the inflation mechanisms of hot Jupiters and giant planet evolution in general.

astro-ph.EP↗

arXiv2023

Word-Graph2vec: An efficient word embedding approach on word co-occurrence graph using random walk technique

Word embedding has become ubiquitous and is widely used in various natural language processing (NLP) tasks, such as web retrieval, web semantic analysis, and machine translation, and so on. Unfortunately, training the word embedding in a relatively large corpus is prohibitively expensive. We propose a graph-based word embedding algorithm, called Word-Graph2vec, which converts the large corpus into a word co-occurrence graph, then takes the word sequence samples from this graph by randomly traveling and trains the word embedding on this sampling corpus in the end. We posit that because of the limited vocabulary, huge idioms, and fixed expressions in English, the size and density of the word co-occurrence graph change slightly with the increase in the training corpus. So that Word-Graph2vec has stable runtime on the large-scale data set, and its performance advantage becomes more and more obvious with the growth of the training corpus. Extensive experiments conducted on real-world datasets show that the proposed algorithm outperforms traditional Word2vec four to five times in terms of efficiency and two to three times than FastText, while the error generated by the random walk technique is small.

cs.CL↗