arXiv subjects

Mingyu Xu

Publications and source records attributed to Mingyu Xu.

At least 55 records · Page 3Linked to original sources

arXiv2024

Competition between the modification of intrinsic superconducting properties and the pinning landscape under external pressure in CaKFe$_4$As$_4$ single crystals

Measurements of low field magnetization, trapped flux magnetization and 5 K flux creep in single crystal of CaKFe$_4$As$_4$ under pressure up to 7.5 GPa in a diamond pressure cell are presented. The observed evolution of the temperature dependence of the self-field critical current and slowing down of the base temperature flux creep rate are explained within the two sources of pinning hypothesis involving presence of CaKFe$_4$As$_4$ intergrowths suggested in the literature. Above the half collapsed tetragonal structural transition under pressure, where superconductivity is non-bulk or absent, critically diminished or no diamagnetism and flux trapped magnetization were observed.

cond-mat.supr-con↗

arXiv2024

Class-balanced Open-set Semi-supervised Object Detection for Medical Images

Medical image datasets in the real world are often unlabeled and imbalanced, and Semi-Supervised Object Detection (SSOD) can utilize unlabeled data to improve an object detector. However, existing approaches predominantly assumed that the unlabeled data and test data do not contain out-of-distribution (OOD) classes. The few open-set semi-supervised object detection methods have two weaknesses: first, the class imbalance is not considered; second, the OOD instances are distinguished and simply discarded during pseudo-labeling. In this paper, we consider the open-set semi-supervised object detection problem which leverages unlabeled data that contain OOD classes to improve object detection for medical images. Our study incorporates two key innovations: Category Control Embed (CCE) and out-of-distribution Detection Fusion Classifier (OODFC). CCE is designed to tackle dataset imbalance by constructing a Foreground information Library, while OODFC tackles open-set challenges by integrating the ``unknown'' information into basic pseudo-labels. Our method outperforms the state-of-the-art SSOD performance, achieving a 4.25 mAP improvement on the public Parasite dataset.

cs.CV↗

arXiv2024

Giant Uniaxial Magnetocrystalline Anisotropy in SmCrGe$_3$

Magnetic anisotropy is a crucial characteristic for enhancing spintronic device performance. The synthesis of SmCrGe$_3$ single crystals through a high-temperature solution method has led to the determination of uniaxial magnetocrystalline anisotropy. Phase verification was achieved using scanning transmission electron microscopy (STEM), powder, and single-crystal X-ray diffraction techniques. Electrical transport and specific heat measurements indicate a Curie temperature ($T_C$) of approximately 160 K, while magnetization measurements were utilized to determine the anisotropy fields and constants. Curie-Weiss fitting applied to magnetization data suggests the contribution of both Sm and Cr in the paramagnetic phase. Additionally, density functional theory (DFT) calculations explored the electronic structures and magnetic properties of SmCrGe$_3$, revealing a significant easy-axis single-ion Sm magnetocrystalline anisotropy of 16 meV/f.u.. Based on the magnetization measurements, easy-axis magnetocrystalline anisotropy at 20 K is 13 meV/f.u..

cond-mat.mtrl-sci↗

arXiv2024

Pressure Tuning the Mixture of Eu$^{2+}$ and Eu$^{3+}$ in Eu$_4$Bi$_6$Se$_{13}$

The investigation of crystallographic, electronic, and magnetic characteristics, especially the mixed valences of Eu$^{2+}$ and Eu$^{3+}$ under pressure of a novel europium-based bismuth selenide compound, Eu$_4$Bi$_6$Se$_{13}$, presented. This new compound adopts a monoclinic crystal structure classified under the P$2_1$/m space group (#11). It exhibits distinctive structural features, including substantial Eu-Se coordination numbers, Bi-Se ladders, and linear chains of Eu atoms that propagate along the b-axis. Electronic resistivity assessments indicate that Eu$_{4}$Bi$_{6}$Se$_{13}$ exhibits weak metallic behaviors. Magnetic characterization reveals uniaxial magnetic anisotropy, with a notable spin transition at approximately 1.2 T when the magnetic field is oriented along the b-axis. This behavior, coupled with the specific Eu-Eu interatomic distances and the magnetic saturation observed at low fields, supports the identification of metamagnetic properties attributable to the flipping of europium spins. The Curie-Weiss analysis of the magnetic susceptibility measured both perpendicular and parallel to the b-axis and high-pressure partial fluorescence yield (PFY) results detected by X-ray absorption spectroscopy (XAS) reveal the tendency of the material to enter a mixed valent state where the trivalent state becomes more prominent with the pressure increase or temperature decrease.

cond-mat.mtrl-sci↗

arXiv2024

Explainable Multimodal Emotion Recognition

Multimodal emotion recognition is an important research topic in artificial intelligence, whose main goal is to integrate multimodal clues to identify human emotional states. Current works generally assume accurate labels for benchmark datasets and focus on developing more effective architectures. However, emotion annotation relies on subjective judgment. To obtain more reliable labels, existing datasets usually restrict the label space to some basic categories, then hire plenty of annotators and use majority voting to select the most likely label. However, this process may result in some correct but non-candidate or non-majority labels being ignored. To ensure reliability without ignoring subtle emotions, we propose a new task called ``Explainable Multimodal Emotion Recognition (EMER)''. Unlike traditional emotion recognition, EMER takes a step further by providing explanations for these predictions. Through this task, we can extract relatively reliable labels since each label has a certain basis. Meanwhile, we borrow large language models (LLMs) to disambiguate unimodal clues and generate more complete multimodal explanations. From them, we can extract richer emotions in an open-vocabulary manner. This paper presents our initial attempt at this task, including introducing a new dataset, establishing baselines, and defining evaluation metrics. In addition, EMER can serve as a benchmark task to evaluate the audio-video-text understanding performance of multimodal LLMs.

cs.MM↗

arXiv2024

Base of RoPE Bounds Context Length

Position embedding is a core component of current Large Language Models (LLMs). Rotary position embedding (RoPE), a technique that encodes the position information with a rotation matrix, has been the de facto choice for position embedding in many LLMs, such as the Llama series. RoPE has been further utilized to extend long context capability, which is roughly based on adjusting the \textit{base} parameter of RoPE to mitigate out-of-distribution (OOD) problems in position embedding. However, in this paper, we find that LLMs may obtain a superficial long-context ability based on the OOD theory. We revisit the role of RoPE in LLMs and propose a novel property of long-term decay, we derive that the \textit{base of RoPE bounds context length}: there is an absolute lower bound for the base value to obtain certain context length capability. Our work reveals the relationship between context length and RoPE base both theoretically and empirically, which may shed light on future long context training.

cs.CL↗

arXiv2024

Trapped flux in a small crystal of CaKFe$_4$As$_4$ at ambient pressure and in a diamond anvil pressure cell

In an extension of our previous work, [Sergey L Bud'ko et al 2023 Supercond. Sci. Technol. 36 115001] the measurements of temperature dependent magnetization associated with trapped magnetic flux in a small single crystal of CaKFe$_4$As$_4$, using zero-field-cooled and field-cooled protocols were performed, on the same crystal, at ambient pressure without a pressure cell and at 2.2 GPa in a commercial diamond anvil cell (DAC), showing comparable results. The data show that with a proper care and understanding, trapped flux measurements in superconductors indeed can be performed on samples in DACs under pressure, as was done on superhydrides [V S Minkov et al 2023 Nat. Phys. 19 1293].

cond-mat.supr-con↗

arXiv2024

Multimodal Fusion with Pre-Trained Model Features in Affective Behaviour Analysis In-the-wild

Multimodal fusion is a significant method for most multimodal tasks. With the recent surge in the number of large pre-trained models, combining both multimodal fusion methods and pre-trained model features can achieve outstanding performance in many multimodal tasks. In this paper, we present our approach, which leverages both advantages for addressing the task of Expression (Expr) Recognition and Valence-Arousal (VA) Estimation. We evaluate the Aff-Wild2 database using pre-trained models, then extract the final hidden layers of the models as features. Following preprocessing and interpolation or convolution to align the extracted features, different models are employed for modal fusion. Our code is available at GitHub - FulgenceWen/ABAW6th.

cs.CV↗

arXiv2024

Loading-effect-based 3-D microfabrication empowers on-chip Brillouin optomechanics

The acousto-optic interaction known as stimulated Brillouin scattering (SBS) has emerged as fundamental principles for realizing crucial components and functionalities in integrated photonics. However, the main challenge of integrated Brillouin devices is how to effectively confine both optical and acoustic waves. Apart from that, the manufacturing processes for these devices need to be compatible with standard fabrication platforms, and streamlined to facilitate their large-scale integration. Here, we demonstrate a novel suspended nanowire structure that can tightly confine photons and phonons. Furthermore, tailored for this structure, we introduce a loading-effect-based three-dimensional microfabrication technique, compatible with complementary metal-oxide-semiconductor (CMOS) technology. This innovative technique allows for the fabrication of the entire structure using a single-step lithography exposure, significantly streamlining the fabrication process. Leveraging this structure and fabrication scheme, we have achieved a Brillouin gain coefficient of 1100 1/W/m on the silicon-on-insulator platform within a compact footprint. It can support a Brillouin net gain over 4.1 dB with modest pump powers. We believe that this structure can significantly advance the development of SBS on chip, unlocking new opportunities for the large-scale integration of Brillouin-based photonic devices.

physics.optics↗

arXiv2024

Anti-resonant acoustic waveguides enabled tailorable Brillouin scattering on chip

Empowering independent control of optical and acoustic modes and enhancing the photon-phonon interaction, integrated photonics boosts the advancements of on-chip stimulated Brillouin scattering (SBS). However, achieving acoustic waveguides with low loss, tailorability, and easy fabrication remains a challenge. Here, inspired by the optical anti-resonance in hollow-core fibers, we propose suspended anti-resonant acoustic waveguides (SARAWs) with superior confinement and high selectivity of acoustic modes, supporting both forward and backward SBS on chip. Furthermore, this structure streamlines the design and fabrication processes. Leveraging the advantages of SARAWs, we have showcased a series of record-breaking results for SBS within a compact footprint on the silicon-on-insulator platform. For forward SBS, a centimeter-scale SARAW supports a large net gain exceeding 6.4 dB. For backward SBS, we have observed an unprecedented Brillouin frequency shift of 27.6 GHz and a mechanical quality factor of up to 1,960 in silicon waveguides. This paradigm of acoustic waveguide propels SBS into a new era, unlocking new opportunities in the fields of optomechanics, phononic circuits, and hybrid quantum systems.

physics.optics↗

arXiv2023

Pressure-dependent "Insulator-Metal-Insulator" Behavior in Sr-doped La$_3$Ni$_2$O$_7$

Recently, superconductivity at high temperatures has been observed in bulk La$_3$Ni$_2$O$_{7-δ}$ under high pressure. However, the attainment of high-purity La$_3$Ni$_2$O$_{7-δ}$ single crystals, exhibiting controlled and homogeneous stoichiometry through the post-annealing process in an oxygen-rich floating zone furnace, remains a formidable challenge. Here, we report the crystal structure and physical properties of single crystals of Sr-doped La$_3$Ni$_2$O$_7$ synthesized at high pressure (20 GPa) and high temperature (1400 °C). Through single crystal X-ray diffraction, we showed that high-pressure-synthesized paramagnetic Sr-doped La$_3$Ni$_2$O$_7$ crystallizes in an orthorhombic structure with Ni-O-Ni bond angles of 173.4(2)°out-of-plane and 175.0(2)°and 176.7(2)°in plane. The substitution of Sr alters in band filling and the ratio of Ni$^{2+}$/Ni$^{3+}$ in Sr-doped La$_3$Ni$_2$O$_7$, aligning them with those of "La$_3$Ni$_2$O$_{7.05}$", thereby leading to significant modifications in properties under high pressure relative to the unsubstituted parent phase. At ambient pressure, Sr-doped La$_3$Ni$_2$O$_7$ exhibits insulating properties, and the conductivity increases as pressure goes up to 10 GPa. However, upon further increasing pressure beyond 10.7 GPa, Sr-doped La$_3$Ni$_2$O$_7$ transits back from a metal-like behavior to an insulator. The insulator-metal-insulator trend under high pressure dramatically differs from the behavior of the parent compound La$_3$Ni$_2$O$_{7-δ}$, despite their similar behavior in the low-pressure regime. These experimental results underscore the considerable challenge in achieving superconductivity in nickelates.

cond-mat.supr-con↗

arXiv2023

MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning

The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia. The challenge focuses on system robustness and consists of three distinct tracks: (1) MER-MULTI, where participants are required to recognize both discrete and dimensional emotions; (2) MER-NOISE, in which noise is added to test videos for modality robustness evaluation; (3) MER-SEMI, which provides a large amount of unlabeled samples for semi-supervised learning. In this paper, we introduce the motivation behind this challenge, describe the benchmark dataset, and provide some statistics about participants. To continue using this dataset after MER 2023, please sign a new End User License Agreement and send it to our official email address merchallenge.contact@gmail.com. We believe this high-quality dataset can become a new benchmark in multimodal emotion recognition, especially for the Chinese research community.

cs.CL↗

arXiv2023

Tuning superconductivity and spin-vortex fluctuations in CaKFe$_4$As$_4$ through in-plane antisymmetric strains

Lattice strains of appropriate symmetry have served as an excellent tool to explore the interaction of superconductivity in the iron-based superconductors with nematic and stripe spin-density wave (SSDW) order, which are both closely tied to an orthorhombic distortion. In this work, we contribute to a broader understanding of the coupling of strain to superconductivity and competing normal-state orders by studying CaKFe$_4$As$_4$ under large, in-plane strains of $B_{1g}$ and $B_{2g}$ symmetry. In contrast to the majority of iron-based superconductors, pure CaKFe$_4$As$_4$ exhibits superconductivity with relatively high transition temperature of $T_c\,\sim\,$35 K in proximity of a non-collinear, tetragonal, hedgehog spin-vortex crystal (SVC) order. Through experiments, we demonstrate an anisotropic in-plane strain response of $T_c$, which is reminiscent of the behavior of other pnictides with nematicity. However, our calculations suggest that in CaKFe$_4$As$_4$, this anisotropic response correlates with the one of the SVC fluctuations, highlighting the close interrelation of magnetism and high-$T_c$ superconductivity. By suggesting moderate $B_{2g}$ strains as an effective parameter to change the stability of SVC and SSDW, we outline a pathway to a unified phase diagram of iron-based superconductivity.

cond-mat.supr-con↗

arXiv2023

ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning

Noisy partial label learning (noisy PLL) is an important branch of weakly supervised learning. Unlike PLL where the ground-truth label must conceal in the candidate label set, noisy PLL relaxes this constraint and allows the ground-truth label may not be in the candidate label set. To address this challenging problem, most of the existing works attempt to detect noisy samples and estimate the ground-truth label for each noisy sample. However, detection errors are unavoidable. These errors can accumulate during training and continuously affect model optimization. To this end, we propose a novel framework for noisy PLL with theoretical guarantees, called ``Adjusting Label Importance Mechanism (ALIM)''. It aims to reduce the negative impact of detection errors by trading off the initial candidate set and model outputs. ALIM is a plug-in strategy that can be integrated with existing PLL approaches. Experimental results on benchmark datasets demonstrate that our method can achieve state-of-the-art performance on noisy PLL. \textcolor[rgb]{0.93,0.0,0.47}{Our code can be found in Supplementary Material}.

cs.CV↗

arXiv2023

VRA: Variational Rectified Activation for Out-of-distribution Detection

Out-of-distribution (OOD) detection is critical to building reliable machine learning systems in the open world. Researchers have proposed various strategies to reduce model overconfidence on OOD data. Among them, ReAct is a typical and effective technique to deal with model overconfidence, which truncates high activations to increase the gap between in-distribution and OOD. Despite its promising results, is this technique the best choice for widening the gap? To answer this question, we leverage the variational method to find the optimal operation and verify the necessity of suppressing abnormally low and high activations and amplifying intermediate activations in OOD detection, rather than focusing only on high activations like ReAct. This motivates us to propose a novel technique called ``Variational Rectified Activation (VRA)'', which simulates these suppression and amplification operations using piecewise functions. Experimental results on multiple benchmark datasets demonstrate that our method outperforms existing post-hoc strategies. Meanwhile, VRA is compatible with different scoring functions and network architectures. \textcolor[rgb]{0.93,0.0,0.47}{Our code can be found in Supplementary Material}.

cs.LG↗

arXiv2023

Twin Brownian particle method for the study of Oberbeck-Boussinesq fluid flows

We establish stochastic functional integral representations for solutions of Oberbeck-Boussinesq equations in the form of McKean-Vlasov-type mean field equations, which can be used to design numerical schemes for calculating solutions and for implementing Monte-Carlo simulations of Oberbeck-Boussinesq flows. Our approach is based on the duality of conditional laws for a class of diffusion processes associated with solenoidal vector fields, which allows us to obtain a novel integral representation theorem for solutions of some linear parabolic equations in terms of the Green function and the pinned measure of the associated diffusion. We demonstrate via numerical experiments the efficiency of the numerical schemes, which are capable of revealing numerically the details of Oberbeck-Boussinesq flows within their thin boundary layer, including B{é}nard's convection feature.

physics.flu-dyn↗

arXiv2023

Pseudo Labels Regularization for Imbalanced Partial-Label Learning

Partial-label learning (PLL) is an important branch of weakly supervised learning where the single ground truth resides in a set of candidate labels, while the research rarely considers the label imbalance. A recent study for imbalanced partial-Label learning proposed that the combinatorial challenge of partial-label learning and long-tail learning lies in matching between a decent marginal prior distribution with drawing the pseudo labels. However, we believe that even if the pseudo label matches the prior distribution, the tail classes will still be difficult to learn because the total weight is too small. Therefore, we propose a pseudo-label regularization technique specially designed for PLL. By punishing the pseudo labels of head classes, our method implements state-of-art under the standardized benchmarks compared to the previous PLL methods.

cs.LG↗

arXiv2022

Pressure-temperature phase diagram of CaK(Fe$_{1-x}$Mn$_x$)$_4$As$_4$ for $x$=0.024

Resistance measurements on single crystals of CaK(Fe$_{1-x}$Mn$_x$)$_4$As$_4$ ($x$ = 0.024) were performed under hydrostatic pressure up to 5.15 GPa. The pressure dependence of the magnetic and superconducting transition temperatures and that of the superconducting upper critical field are reported. Our results show that upon increasing pressure, the magnetic transition temperature $T_{N}$ is suppressed, whereas the superconducting transition temperature $T_{c}$ first increases and then decreases, exhibiting a maximum at a pressure $p_c$ corresponding to the intersection of the $T_{N}$($p$) and $T_{c}$($p$) lines. In addition, a minimum in the normalized slope of the superconducting upper critical field as well as a change in the pressure dependence of the inferred superconducting coherence length are observed at $p_c$, suggesting a difference in the Fermi surface of the paramagnetic and antiferromagnetic states. Finally, CaK(Fe$_{1-x}$Mn$_x$)$_4$As$_4$ ($x$ = 0.024) likely goes through a half-collapsed-tetragonal phase transition at $\sim$ 4.3 GPa, further demonstrating that the half-collapsed-tetragonal transition pressure in the CaKFe$_4$As$_4$ system is relatively insensitive to transition metal substitution.

cond-mat.supr-con↗