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Fei Xue

Publications and source records attributed to Fei Xue.

At least 55 records · Page 3Linked to original sources
arXiv2025

Generalized Heterogeneous Functional Model with Applications to Large-scale Mobile Health Data

Physical activity is crucial for human health. With the increasing availability of large-scale mobile health data, strong associations have been found between physical activity and various diseases. However, accurately capturing this complex relationship is challenging, possibly because it varies across different subgroups of subjects, especially in large-scale datasets. To fill this gap, we propose a generalized heterogeneous functional method which simultaneously estimates functional effects and identifies subgroups within the generalized functional regression framework. The proposed method captures subgroup-specific functional relationships between physical activity and diseases, providing a more nuanced understanding of these associations. Additionally, we introduce a pre-clustering method that enhances computational efficiency for large-scale data through a finer partition of subjects compared to true subgroups. In the real data application, we examine the impact of physical activity on the risk of mental disorders and Parkinson's disease using the UK Biobank dataset, which includes over 79,000 participants. Our proposed method outperforms existing methods in future-day prediction accuracy, identifying four subgroups for mental disorder outcomes and three subgroups for Parkinson's disease diagnosis, with detailed scientific interpretations for each subgroup. We also demonstrate theoretical consistency of our methods. Supplementary materials are available online. Codes implementing the proposed method are available at: https://github.com/xiaojing777/GHFM.

stat.AP↗
arXiv2024

Pomeranchuk instability of a topological crystal

Nematic quantum fluids appear in strongly interacting systems and break the rotational symmetry of the crystallographic lattice. In metals, this is connected to a well-known instability of the Fermi liquid-the Pomeranchuk instability. Using scanning tunneling microscopy, we identified this instability in a highly unusual setting: on the surface of an elemental topological metal, arsenic. By directly visualizing the Fermi surface of the surface state via scanning tunneling spectroscopy and photoemission spectroscopy, we find that the Fermi surface gets deformed and becomes elliptical at the energies where the nematic state is present. Known instances of nematic instability typically need van-Hove singularities or multi-orbital physics as drivers. In contrast, the surface states of arsenic are essentially indistinguishable from well-confined isotropic Rashba bands near the Fermi level, rendering our finding the first realization of Pomeranchuk instability of the topological surface state.

cond-mat.str-el↗
arXiv2024

Angular dependence of spin-orbit torque in monolayer $Fe_3GeTe_2$

In ferromagnetic systems lacking inversion symmetry, an applied electric field can control the ferromagnetic order parameters through the spin-orbit torque. The prototypical example is a bilayer heterostructure composed of a ferromagnet and a heavy metal that acts as a spin current source. In addition to such bilayers, spin-orbit coupling can mediate spin-orbit torques in ferromagnets that lack bulk inversion symmetry. A recently discovered example is the two-dimensional monolayer ferromagnet $Fe_3GeTe_2$. In this work, we use first-principles calculations to study the spin-orbit torque and ensuing magnetic dynamics in this material. By expanding the torque versus magnetization direction as a series of vector spherical harmonics, we find that higher order terms (up to $\ell=4$) are significant and play important roles in the magnetic dynamics. They give rise to deterministic, magnetic field-free electrical switching of perpendicular magnetization.

cond-mat.mtrl-sci↗
arXiv2024

Intercalation of Functional Materials with Phase Transitions for Neuromorphic Applications

Introducing foreign ions, atoms, or molecules into emerging functional materials is crucial for manipulating material physical properties and innovating device applications. The intercalation of emerging new materials can induce multiple intrinsic changes, such as charge doping, chemical bonding, and lattice expansion, which facilitates the exploration of structural phase transformations, the tuning of symmetry-breaking-related physics, and the creation of brain-inspired advanced devices. Moreover, incorporating various hosts and intercalants enables a series of crystal structures with a rich spectrum of characteristics, greatly expanding the scope and fundamental understanding of existing materials. Herein, we summarize the methods typically used for the intercalation of functional materials. We highlight recent progress in intercalation-based phase transitions and their emerging physics, i.e., ferroelectric, magnetic, insulator-metal, superconducting, and charge-density-wave phase transitions. We discuss prospective device applications for intercalation-based phase transitions, i.e., neuromorphic devices. Finally, we provide potential future research lines for promoting its further development.

physics.app-ph↗
arXiv2024

Giant Hall Switching by Surface-State-Mediated Spin-Orbit Torque in a Hard Ferromagnetic Topological Insulator

Topological insulators (TI) and magnetic topological insulators (MTI) can apply highly efficient spin-orbit torque (SOT) and manipulate the magnetization with their unique topological surface states with ultra-high efficiency. Here, we demonstrate efficient SOT switching of a hard MTI, V-doped (Bi,Sb)2Te3 (VBST) with a large coercive field that can prevent the influence of an external magnetic field. A giant switched anomalous Hall resistance of 9.2 $kΩ$ is realized, among the largest of all SOT systems, which makes the Hall channel a good readout and eliminates the need to fabricate complicated magnetic tunnel junction (MTJ) structures. The SOT switching current density can be reduced to $2.8\times10^5 A/cm^2$. Moreover, as the Fermi level is moved away from the Dirac point by both gate and composition tuning, VBST exhibits a transition from edge-state-mediated to surface-state-mediated transport, thus enhancing the SOT effective field to $1.56\pm 0.12 T/ (10^6 A/cm^2)$ and the interfacial charge-to-spin conversion efficiency to $3.9\pm 0.3 nm^{-1}$. The findings establish VBST as an extraordinary candidate for energy-efficient magnetic memory devices.

cond-mat.mes-hall↗
arXiv2024

Almost primes of the form $[p^{1/γ}]$

Let $\mathcal{P}_r$ denote an almost-prime with at most $r$ prime factors, counted according to multiplicity. In this paper, it is proved that, for $0.989<γ<1$, there exist infinitely many primes $p$ such that $[p^{1/γ}]=\mathcal{P}_7$, which constitutes an improvement upon the previous result of Banks-Guo-Shparlinski [4] who showed that there exist infinitely many primes $p$ such that $[p^{1/γ}]=\mathcal{P}_8$ for $γ$ near to one.

math.NT↗
arXiv2024

Quantum transport properties of the topological Dirac Semimetal $α$-Sn

We report measurements of the electrical resistivity ($ρ$) and thermoelectric power (S) in a thin film of strained single-crystalline $α$-Sn grown by molecular beam epitaxy on an insulating substrate. The temperature (T) dependence of the resistivity of $α$-Sn can be divided into two regions:below T* $\approx$ 135 K $ρ$(T) shows a metallic-like behaviour, while above this temperature an increasing contribution from thermally excited holes to electrical transport is observed. However, it is still dominated by highly mobile electrons, resulting in a negative sign of the Seebeck coefficient above T = 47 K. In the presence of the magnetic field (B) applied along an electric field or thermal gradient, we note a negative magnetoresistance or a negative slope of S(B), respectively. The theoretical prediction for the former (calculated using density functional theory) agrees well with the experiment. However, these characteristics quickly disappear when the magnetic field is deviated from an orientation parallel to the electrical field or the thermal gradient. We indicate that the behaviour of the electrical resistivity and thermoelectric power can be explained in terms of the chiral current arising from the topologically non-trivial electronic structure of $α$-Sn. Its decay at high temperature is a consequence of the decreasing ratio between the intervalley Weyl relaxation time to the Drude scattering time.

cond-mat.str-el↗
arXiv2024

Individualized Dynamic Latent Factor Model for Multi-resolutional Data with Application to Mobile Health

Mobile health has emerged as a major success for tracking individual health status, due to the popularity and power of smartphones and wearable devices. This has also brought great challenges in handling heterogeneous, multi-resolution data which arise ubiquitously in mobile health due to irregular multivariate measurements collected from individuals. In this paper, we propose an individualized dynamic latent factor model for irregular multi-resolution time series data to interpolate unsampled measurements of time series with low resolution. One major advantage of the proposed method is the capability to integrate multiple irregular time series and multiple subjects by mapping the multi-resolution data to the latent space. In addition, the proposed individualized dynamic latent factor model is applicable to capturing heterogeneous longitudinal information through individualized dynamic latent factors. Our theory provides a bound on the integrated interpolation error and the convergence rate for B-spline approximation methods. Both the simulation studies and the application to smartwatch data demonstrate the superior performance of the proposed method compared to existing methods.

stat.ME↗
arXiv2024

VRS-NeRF: Visual Relocalization with Sparse Neural Radiance Field

Visual relocalization is a key technique to autonomous driving, robotics, and virtual/augmented reality. After decades of explorations, absolute pose regression (APR), scene coordinate regression (SCR), and hierarchical methods (HMs) have become the most popular frameworks. However, in spite of high efficiency, APRs and SCRs have limited accuracy especially in large-scale outdoor scenes; HMs are accurate but need to store a large number of 2D descriptors for matching, resulting in poor efficiency. In this paper, we propose an efficient and accurate framework, called VRS-NeRF, for visual relocalization with sparse neural radiance field. Precisely, we introduce an explicit geometric map (EGM) for 3D map representation and an implicit learning map (ILM) for sparse patches rendering. In this localization process, EGP provides priors of spare 2D points and ILM utilizes these sparse points to render patches with sparse NeRFs for matching. This allows us to discard a large number of 2D descriptors so as to reduce the map size. Moreover, rendering patches only for useful points rather than all pixels in the whole image reduces the rendering time significantly. This framework inherits the accuracy of HMs and discards their low efficiency. Experiments on 7Scenes, CambridgeLandmarks, and Aachen datasets show that our method gives much better accuracy than APRs and SCRs, and close performance to HMs but is much more efficient.

cs.CV↗
arXiv2023

Raman fingerprints of spin-phonon coupling and magnetic transition in an organic molecule intercalated Cr2Ge2Te6

The manipulation of spin-phonon coupling in both formations and explorations of magnetism in two-dimensional van der Waals ferromagnetic semiconductors facilitates unprecedented prospects for spintronics devices. The interlayer engineering tunes spin-phonon coupling significantly and holds the promise for controllable magnetism via organic cation intercalation. Here, we present spectroscopic evidence to reveal the intercalation effect on intrinsic magnetic and electronic transitions in quasi-two-dimensional Cr2Ge2Te6 using tetrabutyl ammonium as the intercalant. The temperature-evolution of Raman modes E_g^3 and A_g^1, along with the magnetization measurements, unambiguously captures the enhancement of the ferromagnetic Curie temperature in the intercalated heterostructure. Moreover, the E_g^4 mode highlighted the increased effect of spin-phonon interaction in magnetic order-induced lattice distortion. Combined with the first-principle calculations, we observed a substantial number of electrons transferred from TBA+ to Cr through the interface. These results provide the interplay between spin-phonon coupling and magnetic ordering in van der Waals magnets where Raman fingerprints would be highly beneficial for further understanding the manipulation of magnetism in layered heterostructures.

cond-mat.mtrl-sci↗
arXiv2023

Unexpected Field Evaporation Sequence in $γ$-TiAl

In atom probe tomography (APT), atoms from the surface of a needle shape specimen are evaporated under a high electric field and analyzed via time of flight mass spectrometry and position sensitive detection. 3D reconstruction of the atom positions follows a simple projection law, which can sometimes lead to artifacts due to deviation from an assumed ideal evaporation sequence. Here, we revisit the evaporation behavior of [001]-oriented $γ$-TiAl using a full-dynamics simulation approach empowered by molecular dynamics. Without any knowledge of charge states or assumptions about evaporation fields, we successfully reproduced the lack of distinct Al and Ti layers observed in reconstructions of experimental data which is traditionally attributed to the retention of Al on the evaporating surface. We further showed that a step-wise bond breaking process of Ti in contrast to the simultaneous bond breaking of Al explains the seemingly counterintuitive preferential evaporation of the strongly bonded Ti atoms.

cond-mat.mtrl-sci↗
arXiv2023

Proton-mediated reversible switching of metastable ferroelectric phases with low operation voltages

The exploration of ferroelectric phase transitions enables an in-depth understanding of ferroelectric switching and promising applications in information storage. However, controllably tuning the dynamics of ferroelectric phase transitions remains challenging owing to inaccessible hidden phases. Here, using protonic gating technology, we create a series of metastable ferroelectric phases and demonstrate their reversible transitions in van der Waals ferroelectric α-In2Se3 transistors. By varying the gate bias, protons can be incrementally injected or extracted, achieving controllable tuning of the ferroelectric α-In2Se3 protonic dynamics across the channel and obtaining numerous intermediate phases. Combining piezoelectric force microscopy and electrical hysteresis measurements, we surprisingly discover that the gate tuning of α-In2Se3 protonation is volatile, unlike the conventional gating effect, and the created new phases remain polar. Their origin, revealed by first-principles calculations, is related to the formation of metastable hydrogen-stabilized α-In2Se3 phases with switchable dipoles. Furthermore, our approach enables ultralow gate-voltage switching of different phases (below 0.4 V), and easy integration with transistor components. This work provides fundamental insights into the interactions between protons and ferroelectric phase transitions, providing a possible avenue for accessing hidden phases in ferroelectric switching and for developing energy-efficient, multilevel-switching memory devices.

cond-mat.mtrl-sci↗
arXiv2023

On Galbis' integration lemmas

We simplify in this note Galbis' proof of certain norm estimates for self-adjoint Toeplitz operators on the Fock space. This relies on an extension (and a unification) of his integration lemmas, yet with a simpler proof in the same spirit.

math.FA↗
arXiv2023

On Landau-Kato inequalities via semigroup orbits

Let $ω>0$. Given a strongly continuous semigroup $\{e^{tA}\}$ on a Banach space and an element $f\in\mathbf{D}(A^2)$ satisfying the exponential orbital estimates $$\|e^{tA}f\|\leq e^{-ωt}\|f\| \quad\text{and}\quad \|e^{tA}A^2f\|\leq e^{-ωt}\|A^2f\|,\quad t\geq0,$$ a dynamical inequality for $\|Af\|$ in terms of $\|f\|$ and $\|A^2f\|$ was derived by Herzog and Kunstmann (Studia Math., 2014). Here we provide an improvement of their result by relaxing the exponential decay to quadratic, together with a simple and direct way recovering the usual Landau inequality. Herzog and Kunstmann also demanded an analogue, again via semigroup orbits, for the Kato type inequality on Hilbert spaces. We provide such a result by using Hayashi-Ozawa machinery [Proc. Amer. Math. Soc., (2017)] which in turn relies on Hilbertian geometry.

math.FA↗
arXiv2023

A proof of the Prelov conjecture

In this paper we present a complete proof of a conjecture due to V. V. Prelov in 2010 about an information inequality for the binary entropy function.

math.CA↗
arXiv2023

Statistical Inference for High-Dimensional Linear Regression with Blockwise Missing Data

Blockwise missing data occurs frequently when we integrate multisource or multimodality data where different sources or modalities contain complementary information. In this paper, we consider a high-dimensional linear regression model with blockwise missing covariates and a partially observed response variable. Under this framework, we propose a computationally efficient estimator for the regression coefficient vector based on carefully constructed unbiased estimating equations and a blockwise imputation procedure, and obtain its rate of convergence. Furthermore, building upon an innovative projected estimating equation technique that intrinsically achieves bias-correction of the initial estimator, we propose a nearly unbiased estimator for each individual regression coefficient, which is asymptotically normally distributed under mild conditions. Based on these debiased estimators, asymptotically valid confidence intervals and statistical tests about each regression coefficient are constructed. Numerical studies and application analysis of the Alzheimer's Disease Neuroimaging Initiative data show that the proposed method performs better and benefits more from unsupervised samples than existing methods.

stat.ME↗
arXiv2023

IMP: Iterative Matching and Pose Estimation with Adaptive Pooling

Previous methods solve feature matching and pose estimation using a two-stage process by first finding matches and then estimating the pose. As they ignore the geometric relationships between the two tasks, they focus on either improving the quality of matches or filtering potential outliers, leading to limited efficiency or accuracy. In contrast, we propose an iterative matching and pose estimation framework (IMP) leveraging the geometric connections between the two tasks: a few good matches are enough for a roughly accurate pose estimation; a roughly accurate pose can be used to guide the matching by providing geometric constraints. To this end, we implement a geometry-aware recurrent attention-based module which jointly outputs sparse matches and camera poses. Specifically, for each iteration, we first implicitly embed geometric information into the module via a pose-consistency loss, allowing it to predict geometry-aware matches progressively. Second, we introduce an \textbf{e}fficient IMP, called EIMP, to dynamically discard keypoints without potential matches, avoiding redundant updating and significantly reducing the quadratic time complexity of attention computation in transformers. Experiments on YFCC100m, Scannet, and Aachen Day-Night datasets demonstrate that the proposed method outperforms previous approaches in terms of accuracy and efficiency.

cs.CV↗