arXiv subjects

Yao Shen

Publications and source records attributed to Yao Shen.

At least 37 records · Page 2Linked to original sources

arXiv2024

CEC: A Noisy Label Detection Method for Speaker Recognition

Noisy labels are inevitable, even in well-annotated datasets. The detection of noisy labels is of significant importance to enhance the robustness of speaker recognition models. In this paper, we propose a novel noisy label detection approach based on two new statistical metrics: Continuous Inconsistent Counting (CIC) and Total Inconsistent Counting (TIC). These metrics are calculated through Cross-Epoch Counting (CEC) and correspond to the early and late stages of training, respectively. Additionally, we categorize samples based on their prediction results into three categories: inconsistent samples, hard samples, and easy samples. During training, we gradually increase the difficulty of hard samples to update model parameters, preventing noisy labels from being overfitted. Compared to contrastive schemes, our approach not only achieves the best performance in speaker verification but also excels in noisy label detection.

eess.AS↗

arXiv2024

Anyonic quantum multipartite maskers in the Kitaev model

The structure of quantum mechanics forbids a bipartite scenario for masking quantum information, however, it allows multipartite maskers. The Latin squares are found to be closely related to a series of tripartite maskers. This adds another item, significantly different from the original no-cloning theorem, to the no-go theorems. On the other hand, anyonic excitations in two dimensions exhibit exotic collective behaviors of quantum physics, and open the avenue of fault-tolerant topological quantum computing. Here, we give the Latin-square construction of Abelian and Ising anyons %of in the Kitaev model and study the maskable space configuration in anyonic space. The circling and braiding of Kitaev anyons are masking operations on extended hyperdisks in anyonic space. We also realize quantum information masking in a teleportation way in the Kitaev Ising anyon model.

quant-ph↗

arXiv2023

MECPformer: Multi-estimations Complementary Patch with CNN-Transformers for Weakly Supervised Semantic Segmentation

The initial seed based on the convolutional neural network (CNN) for weakly supervised semantic segmentation always highlights the most discriminative regions but fails to identify the global target information. Methods based on transformers have been proposed successively benefiting from the advantage of capturing long-range feature representations. However, we observe a flaw regardless of the gifts based on the transformer. Given a class, the initial seeds generated based on the transformer may invade regions belonging to other classes. Inspired by the mentioned issues, we devise a simple yet effective method with Multi-estimations Complementary Patch (MECP) strategy and Adaptive Conflict Module (ACM), dubbed MECPformer. Given an image, we manipulate it with the MECP strategy at different epochs, and the network mines and deeply fuses the semantic information at different levels. In addition, ACM adaptively removes conflicting pixels and exploits the network self-training capability to mine potential target information. Without bells and whistles, our MECPformer has reached new state-of-the-art 72.0% mIoU on the PASCAL VOC 2012 and 42.4% on MS COCO 2014 dataset. The code is available at https://github.com/ChunmengLiu1/MECPformer.

cs.CV↗

arXiv2023

Multi-objective Generative Design of Three-Dimensional Composite Materials

Composite materials with 3D architectures are desirable in a variety of applications for the capability of tailoring their properties to meet multiple functional requirements. By the arrangement of materials' internal components, structure design is of great significance in tuning the properties of the composites. However, most of the composite structures are proposed by empirical designs following existing patterns. Hindered by the complexity of 3D structures, it is hard to extract customized structures with multiple desired properties from large design space. Here we report a multi-objective driven Wasserstein generative adversarial network (MDWGAN) to implement inverse designs of 3D composite structures according to given geometrical, structural and mechanical requirements. Our framework consists a GAN based network which generates 3D composite structures possessing with similar geometrical and structural features to the target dataset. Besides, multiple objectives are introduced to our framework for the control of mechanical property and isotropy of the composites. Real time calculation of the properties in training iterations is achieved by an accurate surrogate model. We constructed a small and concise dataset to illustrate our framework. With multiple objectives combined by their weight, and the 3D-GAN act as a soft constraint, our framework is proved to be capable of tuning the properties of the generated composites in multiple aspects, while keeping the selected features of different kinds of structures. The feasibility on small dataset and potential scalability on objectives of other properties make our work a novel, effective approach to provide fast, experience free composite structure designs for various functional materials.

cond-mat.mtrl-sci↗

arXiv2023

Perfect teleportation with a partially entangled quantum channel

Quantum teleportation provides a way to transfer unknown quantum states from one system to another via an entangled state as a quantum channel without physical transmission of the object itself. The entangled channel, measurement performed by the sender (Alice), and classical information sent to the receiver (Bob) are three key ingredients in the procedure, which need to cooperate with each other. To study the relationship among the three parts, we propose a scheme for perfect teleportation of a qubit through a high-dimensional quantum channel in a pure state with two equal largest Schmidt coefficients. The scheme requires less entanglement of Alice's measurement but more classical bits than the original scheme via a Bell state. The two quantities increase with the entanglement of the quantum channel when its dimension is fixed and thereby can be regard as Alice's necessary capabilities to use the quantum channel. And the two capabilities appear complementary to each other.

quant-ph↗

arXiv2022

Frustrated magnetic interactions and quenched spin fluctuations in CrAs

The discovery of pressure-induced superconductivity in helimagnets (CrAs, MnP) has attracted considerable interest in understanding the relationship between complex magnetism and unconventional superconductivity. However, the nature of the magnetism and magnetic interactions that drive the unusual double-helical magnetic order in these materials remains unclear. Here, we report neutron scattering measurements of magnetic excitations in CrAs single crystals at ambient pressure. Our experiments reveal well defined spin wave excitations up to about 150 meV with a pseudogap below 7 meV, which can be effectively described by the Heisenberg model with nearest neighbor exchange interactions. Most surprisingly, the spin excitations are largely quenched above the Neel temperature, in contrast to cuprates and iron pnictides where the spectral weight is mostly preserved in the paramagnetic state. Our results suggest that the helimagnetic order is driven by strongly frustrated exchange interactions, and that CrAs is at the verge of itinerant and correlation-induced localized states, which is therefore highly pressure-tunable and favorable for superconductivity.

cond-mat.supr-con↗

arXiv2022

Precise Single-stage Detector

There are still two problems in SDD causing some inaccurate results: (1) In the process of feature extraction, with the layer-by-layer acquisition of semantic information, local information is gradually lost, resulting into less representative feature maps; (2) During the Non-Maximum Suppression (NMS) algorithm due to inconsistency in classification and regression tasks, the classification confidence and predicted detection position cannot accurately indicate the position of the prediction boxes. Methods: In order to address these aforementioned issues, we propose a new architecture, a modified version of Single Shot Multibox Detector (SSD), named Precise Single Stage Detector (PSSD). Firstly, we improve the features by adding extra layers to SSD. Secondly, we construct a simple and effective feature enhancement module to expand the receptive field step by step for each layer and enhance its local and semantic information. Finally, we design a more efficient loss function to predict the IOU between the prediction boxes and ground truth boxes, and the threshold IOU guides classification training and attenuates the scores, which are used by the NMS algorithm. Main Results: Benefiting from the above optimization, the proposed model PSSD achieves exciting performance in real-time. Specifically, with the hardware of Titan Xp and the input size of 320 pix, PSSD achieves 33.8 mAP at 45 FPS speed on MS COCO benchmark and 81.28 mAP at 66 FPS speed on Pascal VOC 2007 outperforming state-of-the-art object detection models. Besides, the proposed model performs significantly well with larger input size. Under 512 pix, PSSD can obtain 37.2 mAP with 27 FPS on MS COCO and 82.82 mAP with 40 FPS on Pascal VOC 2007. The experiment results prove that the proposed model has a better trade-off between speed and accuracy.

cs.CV↗

arXiv2022

Light in the Larynx: a Miniaturized Robotic Optical Fiber for In-office Laser Surgery of the Vocal Folds

This letter reports the design, construction, and experimental validation of a novel hand-held robot for in-office laser surgery of the vocal folds. In-office endoscopic laser surgery is an emerging trend in Laryngology: It promises to deliver the same patient outcomes of traditional surgical treatment (i.e., in the operating room), at a fraction of the cost. Unfortunately, office procedures can be challenging to perform; the optical fibers used for laser delivery can only emit light forward in a line-of-sight fashion, which severely limits anatomical access. The robot we present in this letter aims to overcome these challenges. The end effector of the robot is a steerable laser fiber, created through the combination of a thin optical fiber (0.225 mm) with a tendon-actuated Nickel-Titanium notched sheath that provides bending. This device can be seamlessly used with most commercially available endoscopes, as it is sufficiently small (1.1 mm) to pass through a working channel. To control the fiber, we propose a compact actuation unit that can be mounted on top of the endoscope handle, so that, during a procedure, the operating physician can operate both the endoscope and the steerable fiber with a single hand. We report simulation and phantom experiments demonstrating that the proposed device substantially enhances surgical access compared to current clinical fibers.

cs.RO↗

arXiv2022

Intensity-modulated optical fiber strain sensor for continuous measurements of below-the-surface food deformation during drying

We present a mm-scale optical fiber strain sensor to continuously measure the food deformation below the surface during the drying process. The sensor has a soft buffer sleeve, which enables a large measurable deformation range and minimizes the influence on the native food deformation. The sensor performance was investigated both theoretically and experimentally. To demonstrate the application in foods, we embedded the sensor inside fresh banana slices during a 4-hour-long air-drying process, where its wet basis moisture contents dropped from around 80% to 40%. The fiber sensor measurements covered the full normal strain of ~20% of the banana slices and revealed the shell-hardening characteristics in both the spatial and time dependences, by the comparison with the surface strains measured by the computer vision. Our work provides an unprecedented strain sensor that holds a high potential to contribute to improving both fundamental understandings and process monitoring of food drying processes.

physics.app-ph↗

arXiv2021

Field-Tuned Quantum Effects in a Triangular-Lattice Ising Magnet

We report thermodynamic and neutron scattering measurements of the triangular-lattice quantum Ising magnet TmMgGaO 4 in longitudinal magnetic fields. Our experiments reveal a quasi-plateau state induced by quantum fluctuations. This state exhibits an unconventional non-monotonic field and temperature dependence of the magnetic order and excitation gap. In the high field regime where the quantum fluctuations are largely suppressed, we observed a disordered state with coherent magnon-like excitations despite the suppression of the spin excitation intensity. Through detailed semi-classical calculations, we are able to understand these behaviors quantitatively from the subtle competition between quantum fluctuations and frustrated Ising interactions.

cond-mat.str-el↗

arXiv2021

GMAIR: Unsupervised Object Detection Based on Spatial Attention and Gaussian Mixture

Recent studies on unsupervised object detection based on spatial attention have achieved promising results. Models, such as AIR and SPAIR, output "what" and "where" latent variables that represent the attributes and locations of objects in a scene, respectively. Most of the previous studies concentrate on the "where" localization performance; however, we claim that acquiring "what" object attributes is also essential for representation learning. This paper presents a framework, GMAIR, for unsupervised object detection. It incorporates spatial attention and a Gaussian mixture in a unified deep generative model. GMAIR can locate objects in a scene and simultaneously cluster them without supervision. Furthermore, we analyze the "what" latent variables and clustering process. Finally, we evaluate our model on MultiMNIST and Fruit2D datasets and show that GMAIR achieves competitive results on localization and clustering compared to state-of-the-art methods.

cs.CV↗

arXiv2021

A group method solving many-body systems in intermediate statistical representation

The exact solution of the interacting many-body system is important and is difficult to solve. In this paper, we introduce a group method to solve the interacting many-body problem using the relation between the permutation group and the unitary group. We prove a group theorem first, then using the theorem, we represent the Hamiltonian of the interacting many-body system by the Casimir operators of unitary group. The eigenvalues of Casimir operators could give the exact values of energy and thus solve those problems exactly. This method maps the interacting many-body system onto an intermediate statistical representation. We give the relation between the conjugacy-class operator of permutation group and the Casimir operator of unitary group in the intermediate statistical representation, called the Gentile representation. Bose and Fermi cases are two limitations of the Gentile representation. We also discuss the representation space of symmetric and unitary group in the Gentile representation and give an example of the Heisenberg model to demonstrate this method. It is shown that this method is effective to solve interacting many-body problems.

quant-ph↗

arXiv2021

Converting Lattices into Networks: The Heisenberg Model and Its Generalizations with Long-Range Interactions

In this paper, we convert the lattice configurations into networks with different modes of links and consider models on networks with arbitrary numbers of interacting particle-pairs. We solve the Heisenberg model by revealing the relation between the Casimir operator of the unitary group and the conjugacy-class operator of the permutation group. We generalize the Heisenberg model by this relation and give a series of exactly solvable models. Moreover, by numerically calculating the eigenvalue of Heisenberg models and random walks on network with different numbers of links, we show that a system on lattice configurations with interactions between more particle-pairs have higher degeneracy of eigenstates. The highest degeneracy of eigenstates of a lattice model is discussed.

math-ph↗

arXiv2020

Intermediate symmetric construction of transformation between anyon and Gentile statistics

Gentile statistics describes fractional statistical systems in the occupation number representation. Anyon statistics researches those systems in the winding number representation. Both of them are intermediate statistics between Bose-Einstein and Fermi-Dirac statistics. The second quantization of Gentile statistics shows a lot of advantages. According to the symmetry requirement of the wave function, we give the general construction of transformation between anyon and Gentile statistics. In other words, we introduce the second quantization form of anyons in a easy way. Basic relations of second quantization operators, the coherent state and Berry phase are also discussed.

quant-ph↗

arXiv2019

Neutron Spin Resonance in the Heavily Hole-doped KFe$_{2}$As$_{2}$ Superconductor

We report high-resolution neutron scattering measurements of the low energy spin fluctuations of KFe$_{2}$As$_{2}$, the end member of the hole-doped Ba$_{1-x}$K$_x$Fe$_2$As$_2$ family with only hole pockets, above and below its superconducting transition temperature $T_c$ ($\sim$ 3.5 K). Our data reveals clear spin fluctuations at the incommensurate wave vector ($0.5\pmδ$, 0, $L$), ($δ$ = 0.2)(1-Fe unit cell), which exhibit $L$-modulation peaking at $L=0.5$. Upon cooling to the superconducting state, the incommensurate spin fluctuations gradually open a spin-gap and form a sharp spin resonance mode. The incommensurability ($2δ$ = 0.4) of the resonance mode ($\sim1.2$ meV) is considerably larger than the previously reported value ($2δ$ $\approx0.32$) at higher energies ($\ge\sim6$ meV). The determination of the momentum structure of spin fluctuation in the low energy limit allows a direct comparison with the realistic Fermi surface and superconducting gap structure. Our results point to an $s$-wave pairing with a reversed sign between the hole pockets near the zone center in KFe$_{2}$As$_{2}$.

cond-mat.supr-con↗

arXiv2019

Intertwined dipolar and multipolar order in the triangular-lattice magnet TmMgGaO$_4$

A phase transition is often accompanied by the appearance of an order parameter and symmetry breaking. Certain magnetic materials exhibit exotic hidden-order phases, in which the order parameters are not directly accessible to conventional magnetic measurements. Thus, experimental identification and theoretical understanding of a hidden order are difficult. Here we combine neutron scattering and thermodynamic probes to study the newly discovered rare-earth triangular-lattice magnet TmMgGaO$_4$. Clear magnetic Bragg peaks at K points are observed in the elastic neutron diffraction measurements. More interesting, however, is the observation of sharp and highly dispersive spin excitations that cannot be explained by a magnetic dipolar order, but instead is the direct consequence of the underlying multipolar order that is "hidden" in the neutron diffraction experiments. We demonstrate that the observed unusual spin correlations and thermodynamics can be accurately described by a transverse field Ising model on the triangular lattice with an intertwined dipolar and ferro-multipolar order.

cond-mat.str-el↗

arXiv2019

Fractionalized excitations in the partially magnetized spin liquid candidate YbMgGaO4

Quantum spin liquids (QSLs) are exotic states of matter characterized by emergent gauge structures and fractionalized elementary excitations. The recently discovered triangular lattice antiferromagnet YbMgGaO$_4$ is a promising QSL candidate, and the nature of its ground state is still under debate. Here, we use neutron scattering to study the spin excitations in YbMgGaO$_4$ under various magnetic fields. Our data reveal a dispersive spin excitation continuum with clear upper and lower excitation edges under a weak magnetic field ($H=2.5$ T). Moreover, a spectral crossing emerges at the $Γ$ point at the Zeeman-split energy. The corresponding redistribution of the spectral weight and its field-dependent evolution are consistent with the theoretical prediction based on the inter-band and intra-band spinon particle-hole excitations associated with the Zeeman-split spinon bands, implying the presence of fractionalized excitations and spinon Fermi surfaces in the partially magnetized YbMgGaO$_4$.

cond-mat.str-el↗

arXiv2018

Coexistence of ferromagnetic and stripe-type antiferromagnetic spin fluctuations in YFe$_2$Ge$_2$

We report neutron scattering measurements of single-crystalline YFe$_2$Ge$_2$ in the normal state, which has the same crystal structure to the 122 family of iron pnictide superconductors. YFe$_2$Ge$_2$ does not exhibit long range magnetic order, but exhibits strong spin fluctuations. Like the iron pnictides, YFe$_2$Ge$_2$ displays anisotropic stripe-type antiferromagnetic spin fluctuations at ($π$, $0$, $π$). More interesting, however, is the observation of strong spin fluctuations at the in-plane ferromagnetic wavevector ($0$, $0$, $π$). These ferromagnetic spin fluctuations are isotropic in the ($H$, $K$) plane, whose intensity exceeds that of stripe spin fluctuations. Both the ferromagnetic and stripe spin fluctuations remain gapless down to the lowest measured energies. Our results naturally explain the absence of magnetic order in YFe$_2$Ge$_2$ and also imply that the ferromagnetic correlations may be a key ingredient for iron-based materials.

cond-mat.supr-con↗