arXiv subjects

Yuzhu Wang

Publications and source records attributed to Yuzhu Wang.

At least 37 records · Page 2Linked to original sources

arXiv2026

Optical signatures of -1/3 fractional quantum anomalous Hall state in twisted MoTe2

The discovery of fractional charge excitations in new platforms offers crucial insights into strongly correlated quantum phases. While a range of fractional quantum anomalous Hall (FQAH) states have recently been observed in two-dimensional twisted moire systems, the theoretically anticipated filling factor v = -1/3 FQAH state has remained elusive, with debates centering on its nature of charge density wave or a topological Chern insulator. Here, we report the optical detection of a v = -1/3 FQAH state in twisted MoTe2 bilayers. Using photoluminescence (PL) and reflective magnetic circular dichroism (RMCD) techniques, we identify ferromagnetic states at filling factors v = -1, -2/3, and -1/3, all tunable by a vertical electric field. The corresponding Curie temperatures are approximately 11 K, 3.5 K, and 2.4 K, respectively. The -1/3 state emerges over a narrower electric field range and a lower temperature compared to the integer and other fractional states, indicating its fragile nature that may lead to its absence in previous reports. Notably, the PL spectra at v = -1/3 disperse as the out-of-plane magnetic field increases, consistent with a nontrivial topological origin. Theoretical calculations based on the exact diagonalization method further support the interpretation of this topologically non-trivial state.

cond-mat.mes-hall↗

arXiv2026

Low Mach number limit and optimal time decay rates of the compressible Navier-Stokes-transport system in critical Besov spaces

In this paper, we investigate the Navier-Stokes-Transport (NST) system in the framework of Besov spaces. This system contains of a compressible Navier-Stokes system for the density and momentum of a fluid, and a transport equation for the potential temperature of the fluid. In stark contrast to the well-known Navier-Stokes-Fourier (NSF) system where the temperature satisfies a parabolic type equation providing dissipative effect for the temperature and the density, the temperature in our NST system enjoys a transport equation which precludes a dissipative mechanism for the density, leading to significant different effects to the whole system. We first establish the global well-posedness of strong solutions to the compressible NST system in critical Besov spaces over $\mathbb{R}^d$ with $d \geq 2$. Furthermore, by introducing the Mach number $\varepsilon > 0$, we rigorously prove the low Mach number limit as $\varepsilon \to 0$, showing that the solutions converge to that of the incompressible inhomogeneous Navier-Stokes system. This singular limit holds globally in time, even for {\it ill-prepared} initial data. To address the challenge posed by the lack of dissipation on the density and temperature, we develop a refined energy analysis and establish optimal time decay rates for strong solutions in $\mathbb{R}^d$ with $d \geq 3$. Notably, the density remains uniformly bounded in time, displaying asymptotic behavior fundamentally distinct from that in the NSF system, where the density possesses a dissipative structure via the momentum and temperature equations and exhibits temporal decay.

math.AP↗

arXiv2026

High-pressure structural and lattice-dynamics study of Yttria-Stabilized Zirconia

The structural evolution of two selected compositions of Yttria-Stabilized Zirconia (YSZ), with 3mol% (3YSZ) and 8mol% (8YSZ) of Y2O3, have been investigated under pressure using in-situ synchrotron X-ray diffraction (XRD) and Raman spectroscopy in a diamond anvil cell up to 40 GPa (at room temperature).The close crystallographic relation between the observed structures and the relatively large difference in the atomic numbers of Y/Zr and O, imposes the simultaneous study using both techniques, aiming to fully elucidate the structural evolution under pressure. The results, by combining both techniques, reveal that for both 3YSZ and 8YSZ, pressure promotes higher-symmetry structures. Under initial compression, the minority at ambient conditions monoclinic phase (m-phase) gradually transforms towards t-phase, a transition that is concluded for both 3YSZ/8YSZ at ~10 GPa. At higher pressures, the solely remaining t-phase of 3YSZ transforms to the t'', that in turns transforms to the c-phase above 28 GPa. Likewise, for 8YSZ the coexistence of t- and t''-phases continue up to 31 GPa, where both transforms towards c-phase, that remains stable up to the highest pressure of this study. Upon pressure release, all observed transitions are fully reversible with negligible hysteresis, with the exception of the practical disappearance of the monoclinic phase at ambient conditions. Our study underscores the significance of simultaneously performing and analyzing the results of both XRD and Raman spectroscopy studies in relevant crystallographic systems. Moreover, it provides a route towards a ``structural purification'' of YSZ through the elimination of the m-phase aiming to improve material properties.

cond-mat.mtrl-sci↗

arXiv2025

Dynamics of Anyon Clusters in Fractional Quantum Hall Fluids

In fractional quantum Hall fluids, the quasiparticle excitations are anyons with fractional charges and statistics. Effective interactions among the anyons can be induced by either model or realistic electron-electron (e-e) interactions. Without losing the generality, we investigate such phenomena for the Laughlin 1/3 and Moore-Read (MR) non-Abelian phases. Anyons display rich internal dynamics in both cases that will lead to interesting experimental consequences. In particular, bound states of two Laughlin anyons are preferred under short-range e-e interactions, leading to 2e/3 -- instead of e/3 -- effective charge carriers at low temperatures, which have been seen in several experiments. MR phases host two topologically distinct fusion channels: 1 and psi. The different effective interactions of e/4 anyons in the two sectors suggest the vanishing of the degeneracy of fusion channels when the e-e interaction is no longer its model Hamiltonian, in which case different bound states could also appear. This indicates the possibility of energetically manipulating the two types of anyons by tuning the bare e-e interactions. We point out that the results of recently developed high-resolution STM measurements will be affected by the effective anyon interactions, where anyons are clustered together after the tunneling of electrons. The low-lying parts of the local density of states affected by various anyon clusters are simulated for both Abelian and non-Abelian systems with (screened) Coulomb interactions.

cond-mat.str-el↗

arXiv2025

Non-universal Thermal Hall Responses in Fractional Quantum Hall Droplets

We analytically compute the thermal Hall conductance (THC) of fractional quantum Hall droplets under realistic conditions that go beyond the idealized linear edge theory with conformal symmetry. Specifically, we consider finite-size effects at low temperature, nonzero self-energies of quasiholes, and general edge dispersions. We derive measurable corrections in THC that are consistent with the experimental observables. Although the quantized THC is commonly regarded as a topological invariant that is independent of edge confinement, our results show that this quantization remains robust only for arbitrary edge dispersion in the thermodynamic limit. Furthermore, the THC contributed by Abelian modes can become extremely sensitive to finite-size effects and irregular confining potentials in any realistic experimental system. In contrast, non-Abelian modes show robust THC signatures under perturbations, indicating an intrinsic stability of non-Abelian anyons.

cond-mat.mes-hall↗

arXiv2025

Optical Switching of Moiré Chern Ferromagnet

Optical manipulation of quantum matter offers a non-contact, high-precision and fast control. Fractional Chern ferromagnet states in moiré superlattices are promising for topological quantum computing, but an effective optical control protocol has remained elusive. Here, we demonstrate robust optical switching of integer and fractional Chern ferromagnets in twisted MoTe2 bilayers using circularly polarized light. Highly efficient optical manipulation of spin orientations in the topological ferromagnet regime is realized at zero field using a pump light power as low as 28 nanowatts per square micrometer. Utilizing this optically induced transition, we also demonstrate magnetic bistate cycling and spatially resolved writing of ferromagnetic domain walls. This work establishes a reliable and efficient optical control scheme for moiré Chern ferromagnets, paving the way for dissipationless spintronics and quantized Chern junction devices.

cond-mat.mes-hall↗

arXiv2025

Attention to the Burstiness in Visual Prompt Tuning!

Visual Prompt Tuning (VPT) is a parameter-efficient fune-tuning technique that adapts a pre-trained vision Transformer (ViT) by learning a small set of parameters in the input space, known as prompts. In VPT, we uncover ``burstiness'' in the values arising from the interaction of image patch embeddings, and the key and query projectors within Transformer's self-attention module. Furthermore, the values of patch embeddings and the key and query projectors exhibit Laplacian and hyper-Laplacian distribution, respectively. Intuitively, these non-Gaussian distributions pose challenges for learning prompts. To address this, we propose whitening these data, de-correlating them and equalizing their variance towards more Gaussian before learning prompts. We derive the whitening matrix over random image patch embeddings and ViT's key and query projectors, and multiply it with the prompt to be learned in a bilinear manner. Surprisingly, this method significantly accelerates prompt tuning and boosts accuracy, e.g., $>$25 accuracy points on the CUB dataset; interestingly, it learns ``bursty prompts''. Extending the bilinear model which is known to introduce burstiness, we present a compact, low-rank version by learning two smaller matrices whose multiplication yields the final prompts. We call the proposed methods Bilinear Prompt Tuning (BPT). Extensive experiments across multiple benchmark datasets demonstrate that BPT methods not only outperform various VPT methods but also reduce parameter count and computation overhead.

cs.CV↗

arXiv2025

Multi-Utterance Speech Separation and Association Trained on Short Segments

Current deep neural network (DNN) based speech separation faces a fundamental challenge -- while the models need to be trained on short segments due to computational constraints, real-world applications typically require processing significantly longer recordings with multiple utterances per speaker than seen during training. In this paper, we investigate how existing approaches perform in this challenging scenario and propose a frequency-temporal recurrent neural network (FTRNN) that effectively bridges this gap. Our FTRNN employs a full-band module to model frequency dependencies within each time frame and a sub-band module that models temporal patterns in each frequency band. Despite being trained on short fixed-length segments of 10 s, our model demonstrates robust separation when processing signals significantly longer than training segments (21-121 s) and preserves speaker association across utterance gaps exceeding those seen during training. Unlike the conventional segment-separation-stitch paradigm, our lightweight approach (0.9 M parameters) performs inference on long audio without segmentation, eliminating segment boundary distortions while simplifying deployment. Experimental results demonstrate the generalization ability of FTRNN for multi-utterance speech separation and speaker association.

eess.AS↗

arXiv2025

Attractor-Based Speech Separation of Multiple Utterances by Unknown Number of Speakers

This paper addresses the problem of single-channel speech separation, where the number of speakers is unknown, and each speaker may speak multiple utterances. We propose a speech separation model that simultaneously performs separation, dynamically estimates the number of speakers, and detects individual speaker activities by integrating an attractor module. The proposed system outperforms existing methods by introducing an attractor-based architecture that effectively combines local and global temporal modeling for multi-utterance scenarios. To evaluate the method in reverberant and noisy conditions, a multi-speaker multi-utterance dataset was synthesized by combining Librispeech speech signals with WHAM! noise signals. The results demonstrate that the proposed system accurately estimates the number of sources. The system effectively detects source activities and separates the corresponding utterances into correct outputs in both known and unknown source count scenarios.

eess.AS↗

arXiv2025

Dynamics and lifetime of geometric excitations in moiré systems

We show that spin-2 geometric excitations, known as graviton modes, generally exhibit vanishing lifetimes in lattice Chern bands, including in moiré systems. In contrast to the Landau levels, we first numerically demonstrate that the prominent graviton peaks in spectral functions diminish rapidly with increasing system sizes. We explore how the choice of interaction affects the strength of these peaks, with short-ranged interactions pushing the graviton mode far into the continuum of excitations, where it can be significantly scattered due to the increased density of states. We also analytically investigate the short lifetime of the graviton mode. In lattice systems, continuous rotational symmetry is broken, leading to highly anisotropic gapped excitations that mix different angular momentum or ``spins''. This is despite the surprising emergence of a ``guiding center" continuous rotational symmetry in the ground state, which is shared by the graviton mode. Consequently, the graviton mode in Chern bands can be strongly scattered by the anisotropic gapped excitations. However, the emergent rotational symmetry implies that gravitons can be robust in principle, and we propose experimental tuning strategies to lower the graviton mode energy below the continuum. We argue this is a necessary condition enabling the observation of graviton modes and geometric excitations in realistic moiré systems.

cond-mat.str-el↗

arXiv2025

Isotropic superconductivity in pressurized trilayer nickelate La4Ni3O10

Evidence of superconductivity (SC) has recently been reported in pressurized La3Ni2O7 and La4Ni3O10, providing a new platform to explore high-temperature superconductivity. However, while zero resistance state has been observed, experimental characterization of the superconducting properties of pressurized nickelates is still limited and experimentally challenging. Here, we present the first full temperature dependence of the upper critical field Hc2 measurement in La4Ni3O10 single crystal, achieved by combining high magnetic field and high-pressure techniques. Remarkably, the Hc2 of La4Ni3O10 is nearly isotropic, with the anisotropic parameter monotonically increasing from 1.4 near Tc to 1 at lower temperatures. By analyzing the Hc2 using the two-band model, we uncover that the anisotropic diffusivity of the bands, primarily originating from d(z2 ) and d(x2-y2 ) orbitals, is well compensated, resulting in an unusually isotropic superconducting state. These findings provide critical experimental evidence that underscores the significant role of the d(z2 ) orbital in enabling superconductivity in pressurized Ruddlesden-Popper nickelates.

cond-mat.supr-con↗

arXiv2025

Superconductivity of the hybrid Ruddlesden-Popper La5Ni3O11 single crystals under high pressure

The discovery of high-temperature superconductivity in La3Ni2O7 and La4Ni3O10 under high pressure indicates that the Ruddlesden-Popper (RP) phase nickelates Rn+1NinO3n+1 (R = rare earth) is a new material family for high-temperature superconductivity. Exploring the superconductivity of other RP or hybrid RP phase nickelates under high pressure has become an urgent and interesting issue. Here, we report a novel hybrid RP nickelate superconductor of La5Ni3O11. The hybrid RP nickelate La5Ni3O11 is formed by alternative stacking of La3Ni2O7 with n=2 and La2NiO4 with n=1 along the c axis. The transport and magnetic torque measurements indicate a density-wave transition at approximately 170 K near ambient pressure, which is highly similar to both La3Ni2O7 and La4Ni3O10. With increasing pressure, high-pressure transport measurements reveal that the density-wave transition temperature (TDW) continuously increases to approximately 210 K with increasing pressure up to 12 GPa before the appearance of pressure-induced superconductivity, and the density-wave transition abruptly fades out in a first-order manner at approximately 12 GPa. The optimal superconductivity with Tconset = 64 K and Tczero = 54 K is achieved at approximately 21 GPa. On the other hand, high-pressure X-ray diffraction experiments reveal a structural phase transition from an orthorhombic structure to a tetragonal structure at approximately 4.5 GPa. In contrast to La3Ni2O7 and La4Ni3O10, the pressure-induced structural transition has no significant effect on either the density-wave transition or the superconductivity, suggesting a minor role of lattice degree of freedom in La5Ni3O11. The present discovery extends the superconducting member in the RP nickelate family and sheds new light on the superconducting mechanism.

cond-mat.supr-con↗

arXiv2025

Prerequisite of superconductivity: SDW rather than tetragonal structure in double-layer La3Ni2O7-x

The pressure-induced high-temperature superconductivity(Tc) in nickelates La3Ni2O7-x has sparked significant interest to explore its superconductivity at ambient pressure.Lan+1NinO3n+1(n=2,3)adopts an orthorhombic structure with tilted NiO6 octahedra and undergoes a spin-density-wave(SDW) transition at ambient pressure, while the octahedral tilting and the SDW are suppressed by pressure, and high pressure induces a structural transition from orthorhombic to tetragonal, and the high-Tc superconductivity is achieved in the tetragonal structure. This tetragonal structure is widely believed to be crucial for the pressure-induced superconductivity. Whether the pressure-stabilized tetragonal structure is a prerequisite for achieving nickelate superconductivity at ambient pressure is under hot debate. Here, by post-annealing of the orthorhombic La3Ni2O7-x as grown microcrystals with noticeable oxygen defects in high oxygen pressure environment, tetragonal La3Ni2O6.96 single crystals are successfully obtained at ambient pressure. In contrast to the orthorhombic La3Ni2O7-x, the tetragonal La3Ni2O7-x exhibits metallic behavior without a SDW transition at ambient pressure. Moreover, no superconductivity is observed at high pressure up to ~ 70 GPa. On the other hand, by utilizing Helium as the pressure medium, we have revisited the superconducting structure in pressurized orthorhombic La3Ni2O6.93. Our results indicate that the orthorhombic structure is quite robust against pressure, and no structural transition from orthorhombic to tetragonal happens, and the superconductivity under high pressure is achieved in orthorhombic structure rather than tetragonal structure claimed previously. All these results suggest that tetragonal structure is not prerequisite for achieving superconductivity in La3Ni2O7-x.

cond-mat.supr-con↗

arXiv2024

Revisiting the Power of Prompt for Visual Tuning

Visual prompt tuning (VPT) is a promising solution incorporating learnable prompt tokens to customize pre-trained models for downstream tasks. However, VPT and its variants often encounter challenges like prompt initialization, prompt length, and subpar performance in self-supervised pretraining, hindering successful contextual adaptation. This study commences by exploring the correlation evolvement between prompts and patch tokens during proficient training. Inspired by the observation that the prompt tokens tend to share high mutual information with patch tokens, we propose initializing prompts with downstream token prototypes. The strategic initialization, a stand-in for the previous initialization, substantially improves performance in fine-tuning. To refine further, we optimize token construction with a streamlined pipeline that maintains excellent performance with almost no increase in computational expenses compared to VPT. Exhaustive experiments show our proposed approach outperforms existing methods by a remarkable margin. For instance, it surpasses full fine-tuning in 19 out of 24 tasks, using less than 0.4% of learnable parameters on the FGVC and VTAB-1K benchmarks. Notably, our method significantly advances the adaptation for self-supervised pretraining, achieving impressive task performance gains of at least 10% to 30%. Besides, the experimental results demonstrate the proposed SPT is robust to prompt lengths and scales well with model capacity and training data size. We finally provide an insightful exploration into the amount of target data facilitating the adaptation of pre-trained models to downstream tasks. The code is available at https://github.com/WangYZ1608/Self-Prompt-Tuning.

cs.CV↗

arXiv2023

Attention-Driven Multichannel Speech Enhancement in Moving Sound Source Scenarios

Current multichannel speech enhancement algorithms typically assume a stationary sound source, a common mismatch with reality that limits their performance in real-world scenarios. This paper focuses on attention-driven spatial filtering techniques designed for dynamic settings. Specifically, we study the application of linear and nonlinear attention-based methods for estimating time-varying spatial covariance matrices used to design the filters. We also investigate the direct estimation of spatial filters by attention-based methods without explicitly estimating spatial statistics. The clean speech clips from WSJ0 are employed for simulating speech signals of moving speakers in a reverberant environment. The experimental dataset is built by mixing the simulated speech signals with multichannel real noise from CHiME-3. Evaluation results show that the attention-driven approaches are robust and consistently outperform conventional spatial filtering approaches in both static and dynamic sound environments.

eess.AS↗

arXiv2023

Spin-statistics relation and the Abelian braiding phase for anyons in fractional quantum Hall effect

Quasihole excitations in fractional quantum Hall (FQH) systems exhibit fractional statistics and fractional spin, but how the spin-statistics relation emerges from many-body physics remains poorly understood. Here we prove a spin-statistics relation using only FQH wave functions, on both the sphere and disk geometry. In particular, the proof on the disk generalizes to all quasiholes in realistic systems, which have a finite size and could be deformed into arbitrary shapes. Different components of the quasihole spins are linked to different conformal Hilbert spaces (CHS), which are nullspaces of model Hamiltonians that host the respective FQH ground states and quasihole states. Understanding how the intrinsic spin of the quasiholes is linked to different CHS is crucial for the generalized spin-statistics relation that takes into account the effect of metric deformation. In terms of the experimental relevance, this enables us to study the effect of deformation and disorder that introduces an additional source of Berry curvature, an aspect of anyon braiding that has been largely neglected in previous literature.

cond-mat.mes-hall↗

arXiv2023

Improving Knowledge Distillation via Regularizing Feature Norm and Direction

Knowledge distillation (KD) exploits a large well-trained model (i.e., teacher) to train a small student model on the same dataset for the same task. Treating teacher features as knowledge, prevailing methods of knowledge distillation train student by aligning its features with the teacher's, e.g., by minimizing the KL-divergence between their logits or L2 distance between their intermediate features. While it is natural to believe that better alignment of student features to the teacher better distills teacher knowledge, simply forcing this alignment does not directly contribute to the student's performance, e.g., classification accuracy. In this work, we propose to align student features with class-mean of teacher features, where class-mean naturally serves as a strong classifier. To this end, we explore baseline techniques such as adopting the cosine distance based loss to encourage the similarity between student features and their corresponding class-means of the teacher. Moreover, we train the student to produce large-norm features, inspired by other lines of work (e.g., model pruning and domain adaptation), which find the large-norm features to be more significant. Finally, we propose a rather simple loss term (dubbed ND loss) to simultaneously (1) encourage student to produce large-\emph{norm} features, and (2) align the \emph{direction} of student features and teacher class-means. Experiments on standard benchmarks demonstrate that our explored techniques help existing KD methods achieve better performance, i.e., higher classification accuracy on ImageNet and CIFAR100 datasets, and higher detection precision on COCO dataset. Importantly, our proposed ND loss helps the most, leading to the state-of-the-art performance on these benchmarks. The source code is available at \url{https://github.com/WangYZ1608/Knowledge-Distillation-via-ND}.

cs.CV↗

arXiv2023

Geometric Fluctuation of Conformal Hilbert Spaces and Multiple Graviton Modes in Fractional Quantum Hall Effect

Neutral excitations in fractional quantum Hall (FQH) fluids define the incompressibility of topological phases, a species of which can show graviton-like behaviors and are thus called the graviton modes (GMs). Here, we develop the microscopic theory for multiple GMs in FQH fluids and show explicitly that they are associated with the geometric fluctuation of well-defined conformal Hilbert spaces (CHSs), which are hierarchical subspaces within a single Landau level, each with emergent conformal symmetry and continuously parameterized by a unimodular metric. This leads to several statements about the number and the merging/splitting of GMs, which are verified numerically with both model and realistic interactions. We also discuss how the microscopic theory can serve as the basis for the additional Haldane modes in the effective field theory description and their experimental relevance to realistic electron-electron interactions.

cond-mat.str-el↗