arXiv subjects

Jian Zhou

Publications and source records attributed to Jian Zhou.

At least 145 records · Page 8Linked to original sources

arXiv2023

Vibrational Anharmonicity Assisted Phase Transitions in Perovskite Oxides under Terahertz Irradiation

Despite extensive research interests in perovskite oxides, low energy consumption, non-destructive and maneuverable methods for phase transition in perovskite oxides are still the under its exploration, and the underlying mechanisms remain ambiguous. Here, optical susceptibility including electronic and anharmonic phononic contributions is used to evaluate Gibbs free energy variations of $\mathrm{PbTiO}_3$ and $\mathrm{BaTiO}_3$ under terahertz irradiation. This corresponds to an off-resonant light-controlled phase transition, rather than the resonant approaches that excites hot carriers over electronic band or infrared-active vibrations in the phonon band. We show that intermediate terahertz light can trigger polarization change between ferroelectric orientation variants of $\mathrm{PbTiO}_3$ at room temperature 300 K. Furthermore, the phase transition from low symmetric ferroelectric phase to high symmetric paraelectric structure in $\mathrm{PbTiO}_3$ can be driven by changing the direction and intensity of the incident light under the same conditions. Similar results are observed in $\mathrm{BaTiO}_3$. In detail, phonon spectrum and optical susceptibility are obviously modified and show temperature dependence, in which we show the significant effects of anharmonic vibration. In order to show its nonlinear optical nature, we perform an alternating electric field dressed ab initio molecular dynamics simulation, which maps the Raman-active phonon excitation under off-resonant terahertz irradiation.

cond-mat.mtrl-sci↗

arXiv2023

Lepton pair production in UPCs: towards the precision test of the resummation formalism

We present a detailed investigation of the azimuthal asymmetries and acoplanarity in lepton pair production in ultraperipheral collisions (UPCs). These observables provide a unique opportunity to test the SCET resummation formalism, given the extremely high photon flux in UPCs, which enables precise measurements of these processes. We improve the accuracy of the previous calculations by including the soft photon contributions beyond the double leading logarithm approximation. Notably, the single logarithm terms arising from the collinear region are greatly enhanced by the small mass of the leptons. Our findings demonstrate the accessibility of these sub-leading logarithm resummation effects through the analysis of angular correlations in lepton pairs produced in UPCs at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC).

hep-ph↗

arXiv2023

Spin glass behavior in amorphous Cr2Ge2Te6 phase-change alloy

The layered crystal structure of Cr2Ge2Te6 shows ferromagnetic ordering at the two-dimensional limit, which holds promise for spintronic applications. However, external voltage pulses can trigger amorphization of the material in nanoscale electronic devices, and it is unclear whether the loss of structural ordering leads to a change in magnetic properties. Here, we demonstrate that Cr2Ge2Te6 preserves the spin-polarized nature in the amorphous phase, but undergoes a magnetic transition to a spin glass state below 20 K. Quantum-mechanical computations reveal the microscopic origin of this transition in spin configuration: it is due to strong distortions of the Cr-Te-Cr bonds, connecting chromium-centered octahedra, and to the overall increase in disorder upon amorphization. The tunable magnetic properties of Cr2Ge2Te6 could be exploited for multifunctional, magnetic phase-change devices that switch between crystalline and amorphous states.

cond-mat.mtrl-sci↗

arXiv2023

Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions

Limited availability of representative time-to-failure (TTF) trajectories either limits the performance of deep learning (DL)-based approaches on remaining useful life (RUL) prediction in practice or even precludes their application. Generating synthetic data that is physically plausible is a promising way to tackle this challenge. In this study, a novel hybrid framework combining the controlled physics-informed data generation approach with a deep learning-based prediction model for prognostics is proposed. In the proposed framework, a new controlled physics-informed generative adversarial network (CPI-GAN) is developed to generate synthetic degradation trajectories that are physically interpretable and diverse. Five basic physics constraints are proposed as the controllable settings in the generator. A physics-informed loss function with penalty is designed as the regularization term, which ensures that the changing trend of system health state recorded in the synthetic data is consistent with the underlying physical laws. Then, the generated synthetic data is used as input of the DL-based prediction model to obtain the RUL estimations. The proposed framework is evaluated based on new Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS), a turbofan engine prognostics dataset where a limited avail-ability of TTF trajectories is assumed. The experimental results demonstrate that the proposed framework is able to generate synthetic TTF trajectories that are consistent with underlying degradation trends. The generated trajectories enable to significantly improve the accuracy of RUL predictions.

cs.LG↗

arXiv2023

Shift current response in elemental two-dimensional ferroelectrics

A bulk material without inversion symmetry can generate a direct current under illumination. This interface-free current generation mechanism, referred to as the bulk photovoltaic effect (BPVE), does not rely on $p$-$n$ junctions. Here, we explore the shift current generation, a major mechanism responsible for the BPVE, in single-element two-dimensional (2D) ferroelectrics represented by phosphorene-like monolayers of As, Sb, and Bi. The strong covalency, small band gap, and large joint density of states afforded by these elemental 2D materials give rise to large shift currents, outperforming many state-of-the-art materials. We find that the shift current, due to its topological nature, depends sensitively on the details of the Bloch wave functions. It is crucial to consider the electronic exchange-correlation potential beyond the generalized gradient approximation as well as the spin-orbit interaction in density functional theory calculations to obtain reliable frequency-dependent shift current responses.

cond-mat.mtrl-sci↗

arXiv2023

Observation of colossal topological Hall effect in noncoplanar ferromagnet Cr5Te6 thin films

The topological Hall effect (THE) is critical to the exploration of the spin chirality generated by the real-space Berry curvature, which has attracted worldwide attention for its prospective applications in spintronic devices. However, the prominent THE remains elusive at room temperature, which severely restricts the practical integration of chiral spin textures. Here, we show a colossal intrinsic THE in large-area ferromagnet Cr5Te6 thin films epitaxially grown by pulsed laser deposition. Such a THE can be maintained until 270 K, which is attributed to the field-stimulated noncoplanar spin textures induced by the interaction of the in-plane ferromagnet and antiferromagnet infrastructures. Our first-principles calculations further verify the considerable Dzyaloshinskii-Moriya interaction in Cr5Te6. This work not only paves the way for robust chiral spin textures near room temperature in large-area low-dimensional ferromagnetic films for practical applications, but also facilitates the development of high-density and dissipationless spintronic devices.

cond-mat.mtrl-sci↗

arXiv2023

Small but Mighty: Enhancing 3D Point Clouds Semantic Segmentation with U-Next Framework

We study the problem of semantic segmentation of large-scale 3D point clouds. In recent years, significant research efforts have been directed toward local feature aggregation, improved loss functions and sampling strategies. While the fundamental framework of point cloud semantic segmentation has been largely overlooked, with most existing approaches rely on the U-Net architecture by default. In this paper, we propose U-Next, a small but mighty framework designed for point cloud semantic segmentation. The key to this framework is to learn multi-scale hierarchical representations from semantically similar feature maps. Specifically, we build our U-Next by stacking multiple U-Net $L^1$ codecs in a nested and densely arranged manner to minimize the semantic gap, while simultaneously fusing the feature maps across scales to effectively recover the fine-grained details. We also devised a multi-level deep supervision mechanism to further smooth gradient propagation and facilitate network optimization. Extensive experiments conducted on three large-scale benchmarks including S3DIS, Toronto3D, and SensatUrban demonstrate the superiority and the effectiveness of the proposed U-Next architecture. Our U-Next architecture shows consistent and visible performance improvements across different tasks and baseline models, indicating its great potential to serve as a general framework for future research.

cs.CV↗

arXiv2023

Azimuthal asymmetries of muon pair production in ultraperipheral heavy ion collisions

In this paper we study azimuthal asymmetries of the muon pair production in ultraperipheral heavy ion collisions within the joint impact parameter and transverse momentum dependent framework. The final state QED radiation effects are resummed to all orders in perturbation theory, where the complete muon mass corrections are also taken into account. We further make numerical estimations for azimuthal asymmetries in the different kinematic regions accessible at RHIC and LHC with the derived resummation formula. We find that the lepton mass effects can give sizable corrections to the asymmetries at relatively large pair transverse momentum at RHIC energy.

hep-ph↗

arXiv2023

Valley contrasting bulk photovoltaic effect in antiferromagnetic MnPSe$_3$ monolayer

Valleytronics that uses the inequivalent electronic states at the band extrema in semiconductors have been considered to play a vital role in the future information read/write technology. In the current work, we theoretically show that sizable valley contrasting bulk photovoltaic (BPV) effect could emerge, even when the total photocurrent is symmetrically forbidden. We illustrate our theory by using a prototypical two-dimensional antiferromagnetic semiconductor, MnPSe3 monolayer, that is PT-symmetric (P and T refer to spatially inversion and time-reversal operators, respectively). We show that the Neel vector well controls the magnetic point group at the $Γ$ point, and the BPV current direction. In addition, $\mathbf{k}$-dependent photocurrent generally arises due to the reduction of little group constraints at the valley. This leads to hidden valley-polarized photoconductivity which could reach a magnitude of 1350 $μ$A/V&^2&, observable experimentally. We further predict that the MnPSe$_3$ monolayer could be two-dimensional ferrotoroidic, again depending on its Neel vector direction, which can be determined via magnetoelectric response measurements. Our work provides an exemplary platform for paving the route to future opto-spintronic and opto-valleytronic devices in a single antiferromagnetic nanomaterial.

cond-mat.mtrl-sci↗

arXiv2023

Renormalizing Antiferroelectric Nanostripes in $β'-\mathrm{In}_{2}\mathrm{Se}_{3}$ via Optomechanics

Antiferroelectric (AFE) materials have received tremendous attention owing to their high energy conversion efficiency and good tunability. Recently, an exotic two-dimensional (2D) AFE material, $β'-\mathrm{In}_{2}\mathrm{Se}_{3}$ monolayer that could host atomically thin AFE nanostripe domains has been experimentally synthesized and theoretically examined. In this work, we apply first-principles calculations and theoretical estimations to predict that light irradiation can control the nanostripe width of such a system. We suggest that an intermediate near-infrared light (below bandgap) could effectively harness the thermodynamic Gibbs free energy, and the AFE nanostripe width will gradually reduce. We also propose to use an above bandgap linearly polarized light to generate AFE nanostripespecific photocurrent, providing an all-optical pump-probe setup for such AFE nanostripe width phase transitions.

cond-mat.mtrl-sci↗

arXiv2022

Small-x Evolution of the Gluon Generalized Parton Distribution Eg of the Nucleon

We study the small-$x$ evolution equation for the gluon generalized parton distribution (GPD) $E_g$ of the nucleon. It is shown that $E_g$ at vanishing skewness exhibits the Regge behavior identical to the BFKL Pomeron, despite its association with nucleon helicity-flip processes. We also consider the effect of gluon saturation and demonstrate that $E_g$ gets saturated in the same way as its helicity-nonflip counterpart $H_g$. Our result has a direct impact on the modeling of $E_g$ as well as the small-$x$ contribution to nucleon spin sum rules.

hep-ph↗

arXiv2022

Combating Uncertainty and Class Imbalance in Facial Expression Recognition

Recognition of facial expression is a challenge when it comes to computer vision. The primary reasons are class imbalance due to data collection and uncertainty due to inherent noise such as fuzzy facial expressions and inconsistent labels. However, current research has focused either on the problem of class imbalance or on the problem of uncertainty, ignoring the intersection of how to address these two problems. Therefore, in this paper, we propose a framework based on Resnet and Attention to solve the above problems. We design weight for each class. Through the penalty mechanism, our model will pay more attention to the learning of small samples during training, and the resulting decrease in model accuracy can be improved by a Convolutional Block Attention Module (CBAM). Meanwhile, our backbone network will also learn an uncertain feature for each sample. By mixing uncertain features between samples, the model can better learn those features that can be used for classification, thus suppressing uncertainty. Experiments show that our method surpasses most basic methods in terms of accuracy on facial expression data sets (e.g., AffectNet, RAF-DB), and it also solves the problem of class imbalance well.

cs.CV↗

arXiv2022

Multi-Scale Feature Fusion Transformer Network for End-to-End Single Channel Speech Separation

Recently studies on time-domain audio separation networks (TasNets) have made a great stride in speech separation. One of the most representative TasNets is a network with a dual-path segmentation approach. However, the original model called DPRNN used a fixed feature dimension and unchanged segment size throughout all layers of the network. In this paper, we propose a multi-scale feature fusion transformer network (MSFFT-Net) based on the conventional dual-path structure for single-channel speech separation. Unlike the conventional dual-path structure where only one processing path exists, adopting several iterative blocks with alternative intra-chunk and inter-chunk operations to capture local and global context information, the proposed MSFFT-Net has multiple parallel processing paths where the feature information can be exchanged between multiple parallel processing paths. Experiments show that our proposed networks based on multi-scale feature fusion structure have achieved better results than the original dual-path model on the benchmark dataset-WSJ0-2mix, where the SI-SNRi score of MSFFT-3P is 20.7dB (1.47% improvement), and MSFFT-2P is 21.0dB (3.45% improvement), which achieves SOTA on WSJ0-2mix without any data augmentation method.

cs.SD↗

arXiv2022

Multislice forward modeling of Coherent Surface Scattering Imaging on surface and interfacial structures

To study nanostructures on substrates, surface-sensitive reflection-geometry scattering techniques such as grazing incident small angle x-ray scattering are commonly used to yield an averaged statistical structural information of the surface sample. Grazing incidence geometry can probe the absolute three-dimensional structural morphology of the sample if a highly coherent beam is used. Coherent Surface Scattering Imaging (CSSI) is a powerful yet non-invasive technique similar to Coherent X-ray Diffractive Imaging (CDI) but performed at small angles and grazing-incidence reflection geometry. A challenge with CSSI is that conventional CDI reconstruction techniques cannot be directly applied to CSSI because the Fourier-transform-based forward models cannot reproduce the dynamical scattering phenomenon near the critical angle of total external reflection of the substrate-supported samples. To overcome this challenge, we have developed a multislice forward model which can successfully simulate the dynamical or multi-beam scattering generated from surface structures and the underlying substrate. The forward model is also demonstrated to be able to reconstruct an elongated 3D pattern from a single shot scattering image in the CSSI geometry through fast-performing CUDA-assisted PyTorch optimization with automatic differentiation.

physics.comp-ph↗

arXiv2022

A parton shower generator based on the GLR equation

We develop a novel Monte Carlo parton branching algorithm based on the Gribov-Levin-Ryskin (GLR) equation. The formulations of both forward evolution and backward evolution for the GLR equation are presented. The results from the Monte Carlo implementation of the GLR equation are in full agreement with its numerical solutions. Our work thus paves the way for developing an event generator that embodies the saturation effect.

hep-ph↗

arXiv2022

Tailoring Bulk Photovoltaic Effects in Magnetic Sliding Ferroelectric Materials

The bulk photovoltaic effect that is intimately associated with crystalline symmetry has been extensively studied in various nonmagnetic materials, especially ferroelectrics with a switchable electric polarization. In order to further engineer the symmetry, one could resort to spin-polarized systems possessing an extra magnetic degree of freedom. Here, we investigate the bulk photovoltaic effect in two-dimensional magnetic sliding ferroelectric (MSFE) systems, illustrated in VSe2, FeCl2, and CrI3 bilayers. The transition metal elements in these systems exhibit intrinsic spin polarization, and the stacking mismatch between the two layers produce a finite out-of-plane electric dipole. Through symmetry analyses and first-principles calculations, we show that photoinduced in-plane bulk photovoltaic current can be effectively tuned by their magnetic order and the out-of-plane dipole moment. The underlying mechanism is elucidated from the quantum metric dipole distribution in the reciprocal space. The ease of the fabrication and manipulation of MSFEs guarantee practical optoelectronic applications.

cond-mat.mtrl-sci↗

arXiv2022

Magnetic Proximity Evoked Colossal Bulk Photovoltaics in Crystalline Symmetric Layers

Bulk photovoltaic (BPV) effect, a second order nonlinear process that generates static current under light irradiation, requires centrosymmetric broken systems as its application platform. In order to realize measurable BPV photocurrent in spatially centrosymmetric materials, various schemes such as chemical doping, structural deformation, or electric bias have been developed. In the current work, we suggest that magnetic proximity effect via van der Waals interfacial interaction, a contact-free strategy, also breaks the centrosymmetry and generate large BPV photocurrents. Using the Bi2Te3 quintuple layer as an exemplary material, we show that magnetic proximity from MnBi2Te4 septuple layers yield finite and tunable shift and injection photocurrents. We apply group analysis and first-principles calculations to evaluate the layer-specific shift and injection current generations under linearly polarized light irradiation. We find that the magnetic injection photoconductivity that localized on the Bi2Te3 layer can reach over 70*108 A/(V2s), so that a 1D linear current density on the order of 0.1 mA/nm can be achieved under an intermediate intensity light. In addition to charge current, we also extend our discussions into spin BPV current, giving pure photo-generated spin current. The vertical propagation direction between the charge and spin photocurrents suggest that they can be used individually in a single material. Compared with previously reported methods, the magnetic proximity effect via van der Waals interface does not significantly alter the intrinsic feature of the centrosymmetric material (e.g., Bi2Te3), and its manipulation can be easily achieved by the proximate magnetic configurations (of MnBi2Te4), interlayer distance, and light polarization.

cond-mat.mtrl-sci↗

arXiv2022

On-chip picosecond synchrotron pulse shaper

Synchrotrons are powerful and productive in revealing the spatiotemporal complexities in matter. However, X-ray pulses produced by the synchrotrons are predetermined in specific patterns and widths, limiting their operational flexibility and temporal resolution. Here, we introduce the on-chip picosecond synchrotron pulse shaper that shapes the sub-nm-wavelength hard X-ray pulses at individual beamlines, flexibly and efficiently beyond the synchrotron pulse limit. The pulse shaper is developed using the widely available silicon-on-insulator technology, oscillates in torsional motion at the same frequency or at harmonics of the storage ring, and manipulates X-ray pulses through the narrow Bragg peak of the crystalline silicon. Stable pulse manipulation is achieved by synchronizing the shaper timing to the X-ray timing using electrostatic closed-loop control. Tunable shaping windows down to 40 $ps$ are demonstrated, allowing X-ray pulse picking, streaking, and slicing in the majority of worldwide synchrotrons. The compact, on-chip shaper offers a simple but versatile approach to boost synchrotron operating flexibility and to investigate structural dynamics from condensed matter to biological systems beyond the current synchrotron-source limit.

physics.acc-ph↗