arXiv subjects

Jianli Wang

Publications and source records attributed to Jianli Wang.

At least 19 recordsLinked to original sources

arXiv2026

Status report towards implementation of a Compton polarimeter at BEPCII

Precision beam polarization measurements based on Compton polarimeters are essential for the physics program of future high-energy colliders. In order to prepare for these and to extend the scope of physics measurements of the BESIII experiment at the BEPCII, a diagnostic of electron beam transverse polarization at BEPCII is of interest. The design and status report of the commissioning, until July 2025, of this device is reported in this paper. We report unambiguous observation of Compton interaction, discuss current limitations of the experimental setup and draw prospects for improvements and actual measurement of electron beam polarization in the near future.

physics.acc-ph↗

arXiv2026

Robust Electrocaloric Performance Enabled by Highly-Polar Frustrated Nanodomains in NaNbO3-Based Ferrodistortive Relaxor

Solid-state refrigeration technologies, represented by electrocaloric effect (ECE), are renowned for zero global-warming-potential and high cooling efficiency. Synergistically achieving high electrocaloric effect (ΔT) and wide temperature span (ΔTspan) for EC materials takes a leapfrog toward practical cooling applications, typical for integrated circuits. Guided by phase-field simulation, Ba(Ti, Hf)O3 dubbed as a polar wrench, establishes polar frustration by setting up local stress field and manipulating octahedral oxygen tilt (OOT) in NaNbO3-based relaxor. The resultant P4bm framework entails short-range and highly-polar ferrodistortive nanodomains, i.e., the abundant highly-polar nanodomains facilitate to increase entropy change and robust OOT enables to impede thermal perturbations. Consequently, a large ΔT of 0.85 K and 0.70 K with an ultrawide ΔTspan of 118 K and 130 K is obtained, contributing to an ultrahigh figure of merit of > 90 K2 in NaNbO3-Ba(Ti, Hf)O3, significantly outperforms its counterparts. The local structure responsible for robust EC performances are decrypted through 2D information from atomic-resolution scanning transmission electron microscope, 3D big-box model constructed from neutron total scattering and DFT calculations. These findings highlight that polar frustration strategy in ferrodistortive relaxor enables to pioneer emergent EC performances, and also unearth potential entropy-change-based ferroelectric and ferromagnetic materials beyond.

cond-mat.mtrl-sci↗

arXiv2025

Anharmonicity-driven phonon avoided crossing and anomalous thermal transport in nodal-line semimetal ZrSiS

Understanding thermal and electrical transport in topological materials is essential for advancing their applications in quantum technologies and energy conversion. Herein, we employ first-principles calculations to systematically investigate phonon and charge transport in the prototypical nodal-line semimetal ZrSiS. The results unveil that anharmonic phonon renormalization results in the pronounced softening of heat-carrying phonons and suppressed lattice thermal conductivity ($κ_{\rm L}$). Crucially, anharmonic effects are found to noticeably weaken Zr-S interactions, triggering avoided-crossing behavior of low-frequency optical phonons. The combination of phonon softening and avoided crossing synergistically reduces phonon group velocities, yielding a 16\% suppression in $κ_{\rm L}$ along the $c$-axis at room temperature. Contrary to conventional metals, we discover that the lattice contribution to thermal conductivity in ZrSiS is abnormally large, even dominating heat conduction along the $c$-axis. This unusual behavior results in a substantial deviation of the Lorenz number from the Sommerfeld value -- exceeding it by up to threefold -- thereby challenging the validation of standard Wiedemann-Franz law for thermal conductivity estimation. Moreover, our calculations demonstrate that ZrSiS exhibits exceptional electrical conductivity, attributed to its topological electronic Dirac states that account for both high Fermi velocities and weak electron-phonon coupling. This study provides critical insights into the electrical and thermal transport mechanisms in ZrSiS and highlights the importance of anharmonic effects in the lattice dynamics and thermal transport of metallic materials.

cond-mat.mtrl-sci↗

arXiv2025

Superpixel-informed Continuous Low-Rank Tensor Representation for Multi-Dimensional Data Recovery

Low-rank tensor representation (LRTR) has emerged as a powerful tool for multi-dimensional data processing. However, classical LRTR-based methods face two critical limitations: (1) they typically assume that the holistic data is low-rank, this assumption is often violated in real-world scenarios with significant spatial variations; and (2) they are constrained to discrete meshgrid data, limiting their flexibility and applicability. To overcome these limitations, we propose a Superpixel-informed Continuous low-rank Tensor Representation (SCTR) framework, which enables continuous and flexible modeling of multi-dimensional data beyond traditional grid-based constraints. Our approach introduces two main innovations: First, motivated by the observation that semantically coherent regions exhibit stronger low-rank characteristics than holistic data, we employ superpixels as the basic modeling units. This design not only encodes rich semantic information, but also enhances adaptability to diverse forms of data streams. Second, we propose a novel asymmetric low-rank tensor factorization (ALTF) where superpixel-specific factor matrices are parameterized by a shared neural network with specialized heads. By strategically separating global pattern learning from local adaptation, this framework efficiently captures both cross-superpixel commonalities and within-superpixel variations. This yields a representation that is both highly expressive and compact, balancing model efficiency with adaptability. Extensive experiments on several benchmark datasets demonstrate that SCTR achieves 3-5 dB PSNR improvements over existing LRTR-based methods across multispectral images, videos, and color images.

cs.CV↗

arXiv2025

Neutron scattering studies of complex lattice dynamics in energy materials

Lattice dynamics play a crucial role in understanding the physical mechanisms of cutting-edge energy materials. Many excellent energy materials have complex multiple-sublattice structures, with intricate lattice dynamics, and the underlying mechanisms are difficult to understand. Neutron scattering technologies, which are known for their high energy and momentum resolution, are powerful tools for simultaneously characterizing material structure and complex lattice dynamics. In recent years, neutron scattering techniques have made significant contributions to the study of energy materials, shedding light on their physical mechanisms. This review article details several neutron scattering techniques commonly used in energy material research, including neutron diffraction, total neutron scattering, quasi-elastic and inelastic neutron scattering. Then, some important research progress made in the field of energy materials in recent years using neutron scattering as the main characterization method is reviewed, including ultra-low lattice thermal conductivity in superionic thermoelectric materials, ion diffusion mechanism of solid-state electrolytes, plastic-crystalline phase transition and configuration entropy changes in barocaloric materials, lattice anharmonicity and charge transport in photovoltaic materials, and first-order magnetic-structural phase transition in magnetocaloric materials. In these complex energy conversion and storage materials, lattice dynamics do not work independently, and their functioning in macroscopic physical properties is always achieved through correlation or mutual coupling with other degrees of freedom, such as sublattices, charge, spin, etc. Through these typical examples, this review paper can provide a reference for further exploring and understanding the energy materials and lattice dynamics.

cond-mat.mtrl-sci↗

arXiv2025

Under-Sampled High-Dimensional Data Recovery via Symbiotic Multi-Prior Tensor Reconstruction

The advancement of sensing technology has driven the widespread application of high-dimensional data. However, issues such as missing entries during acquisition and transmission negatively impact the accuracy of subsequent tasks. Tensor reconstruction aims to recover the underlying complete data from under-sampled observed data by exploring prior information in high-dimensional data. However, due to insufficient exploration, reconstruction methods still face challenges when sampling rate is extremely low. This work proposes a tensor reconstruction method integrating multiple priors to comprehensively exploit the inherent structure of the data. Specifically, the method combines learnable tensor decomposition to enforce low-rank constraints of the reconstructed data, a pre-trained convolutional neural network for smoothing and denoising, and block-matching and 3D filtering regularization to enhance the non-local similarity in the reconstructed data. An alternating direction method of the multipliers algorithm is designed to decompose the resulting optimization problem into three subproblems for efficient resolution. Extensive experiments on color images, hyperspectral images, and grayscale videos datasets demonstrate the superiority of our method in extreme cases as compared with state-of-the-art methods.

eess.IV↗

arXiv2024

Superpixel-informed Implicit Neural Representation for Multi-Dimensional Data

Recently, implicit neural representations (INRs) have attracted increasing attention for multi-dimensional data recovery. However, INRs simply map coordinates via a multi-layer perception (MLP) to corresponding values, ignoring the inherent semantic information of the data. To leverage semantic priors from the data, we propose a novel Superpixel-informed INR (S-INR). Specifically, we suggest utilizing generalized superpixel instead of pixel as an alternative basic unit of INR for multi-dimensional data (e.g., images and weather data). The coordinates of generalized superpixels are first fed into exclusive attention-based MLPs, and then the intermediate results interact with a shared dictionary matrix. The elaborately designed modules in S-INR allow us to ingenuously exploit the semantic information within and across generalized superpixels. Extensive experiments on various applications validate the effectiveness and efficacy of our S-INR compared to state-of-the-art INR methods.

cs.CV↗

arXiv2024

Optimized Cryo-CMOS Technology with VTH<0.2V and Ion>1.2mA/um for High-Peformance Computing

We report the design-technology co-optimization (DTCO) scheme to develop a 28-nm cryogenic CMOS (Cryo-CMOS) technology for high-performance computing (HPC). The precise adjustment of halo implants manages to compensate the threshold voltage (VTH) shift at low temperatures. The optimized NMOS and PMOS transistors, featured by VTH<0.2V, sub-threshold swing (SS)<30 mV/dec, and on-state current (Ion)>1.2mA/um at 77K, warrant a reliable sub-0.6V operation. Moreover, the enhanced driving strength of Cryo-CMOS inherited from a higher transconductance leads to marked improvements in elevating the ring oscillator frequency by 20%, while reducing the power consumption of the compute-intensive cryogenic IC system by 37% at 77K.

eess.SY↗

arXiv2024

Quantitative determination of the orbital-selective Mott transition and quantum entanglement in the orbital-selective Mott phase

We examine the orbital-selective Mott transition in the non-hybridized two-band Hubbard model using the dynamical mean-field theory. We find that the orbital-selective Mott transition could be quantitatively depicted by the {local two-qubit fidelity}. Furthermore, within the orbital-selective Mott phase, the combined characteristics of the two orbitals lead to the presence of quantum entanglement, which is characterized by the non-semi-integer values of local two-qubit fidelity. It is demonstrated that the Hund's coupling results in the ground states of both wide and narrow bands exhibiting the specific superposition states, indicating the existence of quantum entanglement within orbital-selective Mott phase. Without Hund's coupling, there are no specific superposition states, nor does quantum entanglement occur within the orbital-selective Mott phase. The mechanisms underlying the orbital-selective Mott transition show prominent variations depending on the presence or absence of Hund's coupling and its transverse terms.

cond-mat.str-el↗

arXiv2023

Quantitative Determination of the Critical Points of Mott Metal-Insulator Transition in Strongly Correlated Systems

Mottness is at the heart of the essential physics in a strongly correlated system as many novel quantum phenomena occur in the metallic phase near the Mott metal-insulator transition. We investigate the Mott transition in a Hubbard model by using the dynamical mean-field theory and introduce the local quantum state fidelity to depict the Mott metal-insulator transition. The local quantum state fidelity provides a convenient approach for determining the critical point of the Mott transition. Additionally, it presents a consistent description of the two distinct forms of the Mott transition points.

cond-mat.str-el↗

arXiv2023

H2TF for Hyperspectral Image Denoising: Where Hierarchical Nonlinear Transform Meets Hierarchical Matrix Factorization

Recently, tensor singular value decomposition (t-SVD) has emerged as a promising tool for hyperspectral image (HSI) processing. In the t-SVD, there are two key building blocks: (i) the low-rank enhanced transform and (ii) the accompanying low-rank characterization of transformed frontal slices. Previous t-SVD methods mainly focus on the developments of (i), while neglecting the other important aspect, i.e., the exact characterization of transformed frontal slices. In this letter, we exploit the potentiality in both building blocks by leveraging the \underline{\bf H}ierarchical nonlinear transform and the \underline{\bf H}ierarchical matrix factorization to establish a new \underline{\bf T}ensor \underline{\bf F}actorization (termed as H2TF). Compared to shallow counter partners, e.g., low-rank matrix factorization or its convex surrogates, H2TF can better capture complex structures of transformed frontal slices due to its hierarchical modeling abilities. We then suggest the H2TF-based HSI denoising model and develop an alternating direction method of multipliers-based algorithm to address the resultant model. Extensive experiments validate the superiority of our method over state-of-the-art HSI denoising methods.

cs.CV↗

arXiv2023

Jahn-Teller distortion driven ferromagnetism in a perovskite fluoride monolayer

The Jahn-Teller distortion and the resulting orbital order usually cause some fascinating correlated electronic behaviors, and generally lead to antiferromagnetism in perovskite bulks. Here we demonstrate that the Jahn-Teller distortion present in the perovskite fluoride KCrF$_3$ bulk can be retained to the two-dimensional limit, resulting in a staggered orbital order and ferromagnetism in the perovskite monolayer. Octahedral tilt and rotation distortion also appear in the ground-state structure of the perovskite monolayer, which have minor effects on the electronic and magnetic properties with respect to the Jahn-Teller distortion. In addition, in the prototype phase without structural distortion, the partial occupation of the $e_g$ orbitals leads to a ferromagnetic metallic state. This work facilitates the design of two-dimensional ferromagnets and functional properties based on Jahn-Teller distortion and orbital order

cond-mat.mtrl-sci↗

arXiv2023

Uncertainty-Aware Unsupervised Image Deblurring with Deep Residual Prior

Non-blind deblurring methods achieve decent performance under the accurate blur kernel assumption. Since the kernel uncertainty (i.e. kernel error) is inevitable in practice, semi-blind deblurring is suggested to handle it by introducing the prior of the kernel (or induced) error. However, how to design a suitable prior for the kernel (or induced) error remains challenging. Hand-crafted prior, incorporating domain knowledge, generally performs well but may lead to poor performance when kernel (or induced) error is complex. Data-driven prior, which excessively depends on the diversity and abundance of training data, is vulnerable to out-of-distribution blurs and images. To address this challenge, we suggest a dataset-free deep residual prior for the kernel induced error (termed as residual) expressed by a customized untrained deep neural network, which allows us to flexibly adapt to different blurs and images in real scenarios. By organically integrating the respective strengths of deep priors and hand-crafted priors, we propose an unsupervised semi-blind deblurring model which recovers the latent image from the blurry image and inaccurate blur kernel. To tackle the formulated model, an efficient alternating minimization algorithm is developed. Extensive experiments demonstrate the favorable performance of the proposed method as compared to data-driven and model-driven methods in terms of image quality and the robustness to the kernel error.

cs.CV↗

arXiv2022

Observation of short-period helical spin order and magnetic transition in a non-chiral centrosymmetric helimagnet

The search for materials exhibiting nanoscale spiral order continues to be fuelled by the promise of emergent inductors. Although such spin textures have been reported in many materials, most of them exhibit long periods or are limited to operate far below room temperature. Here, we present the real-space observation of an ordered helical spin order with a period of 3.2 nm in a non-chiral centrosymmetric helimagnet MnCoSi at room temperature via multi-angle and multi-azimuth approach of Lorentz transmission electron microscopy (TEM). A magnetic transition from the ordered helical spin order to a cycloidal spin order below 228 K is clearly revealed by in situ neutron powder diffraction and Lorentz TEM, which is closely correlated with temperature-induced variation in magneto-crystalline anisotropy. These results reveal the origin of spiral ordered spin textures in non-chiral centrosymmetric helimagnet, which can serve as a new strategy for searching materials with nanoscale spin order with potential applications in emergent electromagnetism.

cond-mat.mtrl-sci↗

arXiv2021

Coherent spin rotation-induced zero thermal expansion in MnCoSi-based spiral magnets

Materials exhibiting zero thermal expansion (ZTE), namely, volume invariance during temperature change, can resist thermal shock and are highly desired in modern industries as high-precision components. However, pure ZTE materials are rare, especially those that are metallic. Here, we report the discovery of a pure metallic ZTE material: an orthorhombic Mn1-xNixCoSi spiral magnet. The introduction of Ni can efficiently enhance the ferromagnetic exchange interaction and construct the transition from a spiral magnetic state to a ferromagnetic-like state in MnCoSi-based alloys. Systematic in situ neutron powder diffraction revealed a new cycloidal spiral magnetic structure in bc plane at ground state which would transform to the helical spiral in the ab plane with increasing temperature. Combined with Lorentz transmission electron microscopy techniques, the cycloidal and helical spin order coherently rotated at varying periods along the c axis during the magnetic transition. This spin rotation drove the continuous movement of the coupled crystalline lattice and induced a large negative thermal expansion along the a axis, eventually leading to a wide-temperature ZTE effect. Our work not only introduces a new ZTE alloy but also presents a new mechanism by which to discover or design ZTE magnets.

cond-mat.mtrl-sci↗

arXiv2017

Commissioning of te China-ADS injector-I testing facility

The 10 MeV accelerator-driven subcritical system (ADS) Injector-I test stand at Institute of High Energy Physics (IHEP) is a testing facility dedicated to demonstrate one of the two injector design schemes [Injector Scheme-I, which works at 325 MHz], for the ADS project in China. The Injector adopted a four vane copper structure RFQ with output energy of 3.2 MeV and a superconducting (SC) section accommodating fourteen \b{eta}g=0.12 single spoke cavities, fourteen SC solenoids and fourteen cold BPMs. The ion source was installed since April of 2014, periods of commissioning are regularly scheduled between installation phases of the rest of the injector. Continuous wave (CW) beam was shooting through the injector and 10 MeV CW proton beam with average beam current around 2 mA was obtained recently. This contribution describe the results achieved so far and the difficulties encountered in CW commissioning.

physics.acc-ph↗

arXiv2016

Quantum capacitance anomalies of two-dimensional non-equilibrium states under microwave irradiation

We report our direct study of the compressibility on ultrahigh mobility two-dimensional electron system ($μ_{e} \sim 1 \times 10^{7}$ cm$^{2}$/Vs) in GaAs/AlGaAs quantum wells under microwave (MW) irradiation. The field penetration current results show that the quantum capacitance oscillates with microwave induced resistance oscillations (MIRO), however, the trend is opposite with respect to the compressibility for usual equilibrium states in previous theoretical explanations. The anomalous phenomena provide a platform for study on the non-equilibrium system under microwave, and point to the current domains and inhomogeneity induced by radiation. Moreover, the quantum capacitance indication for multi-photon process around $j = 1/2$ is detected under intensive microwave below 30 GHz.

cond-mat.mes-hall↗

arXiv2016

Photovoltage Detection of Edge Magnetoplasmon Oscillations and Giant Magnetoplasmon Resonances in A Two-Dimensional Hole System

In our high mobility p-type AlGaAs/GaAs two-dimensional hole samples, we originally observe the B-periodic oscillation induced by microwave (MW) in photovoltage (PV) measurements. In the frequency range of our measurements (5 - 40 GHz), the period (ΔB) is inversely proportional to the microwave frequency (f). The distinct oscillations come from the edge magnetoplasmon (EMP) in the high quality heavy hole system. In our hole sample with a very large effective mass, the observation of the EMP oscillations is in neither the low frequency limit nor the high frequency limit, and the damping of the EMP oscillations is very weak under high magnetic fields. Simultaneously, we observe the giant plasmon resonance signals in our measurements on the shallow two-dimensional hole system (2DHS).

cond-mat.mes-hall↗