arXiv subjects

Xinwei Li

Publications and source records attributed to Xinwei Li.

At least 19 recordsLinked to original sources

arXiv2026

Observing Bell Inequality Violation Beyond the Qubit Bound in a Spinor Bose--Einstein Condensate

Correlations allowed by quantum mechanics can defy any classical explanation, with Bell nonlocality standing as their most profound and operationally powerful manifestation. While nonlocality has been demonstrated across a wide range of platforms, in many-body systems it has remained limited to ensembles of qubits, leaving the observation of higher-dimensional multipartite Bell correlations an open challenge. Here we report the observation of qutrit Bell correlations in a spin-1 $^{87}$Rb Bose-Einstein condensate via the violation of a Bell witness based on collective spin observables only. Exploiting spin-exchange collisions in an ensemble of $N \simeq 3.1 \times 10^{4}$ atoms, we generate spin-nematic squeezing of $-11.8(7)$ dB and observe a violation that surpasses the minimum bound achievable by a collection of $N$ qubits, providing direct evidence of genuine multipartite qutrit Bell correlations. Our results establish spinor Bose-Einstein condensates as a viable platform for investigating high-dimensional Bell correlations in the many-body regime, and demonstrate that coarse-grained collective measurements suffice to certify the dimensionality of quantum correlations at macroscopic scales.

quant-ph↗

arXiv2026

Deep adaptive design with an evidential bias criterion

Bayesian optimal experimental design (BOED) aims to collect informative data by optimizing an expected utility reflecting the goals of an experiment. However, this optimization is computationally challenging for common utilities and complex models. This is especially so for sequential or adaptive designs, where design and data collection alternate, so that feedback from already observed data must be taken into account. Most existing BOED research employs information gain as the utility, leading to the expected information gain (EIG) criterion. While EIG is widely useful, it may not always adequately reflect experimental goals. EIG can be viewed as rewarding experiments that produce large positive evidence for the truth on average, but it does not directly control the risk of an experiment producing misleading evidence. Here we consider an alternative criterion, which we call bias against (BA), that prioritizes such control. To address computational challenges when applying this criterion for adaptive design, we consider a policy-based deep adaptive design framework, which has previously been used for the EIG criterion. Minimizing a tractable upper bound on the BA objective is equivalent to maximizing a variance-penalized EIG criterion, and we optimize the latter by approximating it by Monte Carlo and learning design policies using stochastic gradient methods. The differences between BA and EIG designs are demonstrated in several examples including the adaptive design of a complex discrete choice experiment.

stat.ME↗

arXiv2026

MVFM-3DAD: Multi-view Flow Matching for 3D Anomaly Detection via Density Proxy Estimation

In 3D anomaly detection (3DAD), most existing methods rely on Memory bank retrieval or reconstruction. However, memory-based methods are constrained by the coverage of stored normal features, while reconstruction-based methods may learn identity shortcuts that also reconstruct anomalous inputs well. These limitations motivate a density-oriented approach that evaluates whether a test sample follows the learned normal distribution. To this end, we propose MVFM-3DAD, a flow-based framework that reframes 3DAD as density proxy estimation over the normal data distribution. MVFM-3DAD introduces a Bidirectional Geometric Projector (BGP), whose forward process converts irregular point clouds into structured multi-view representations. The Flow-guided Density Proxy Estimator (FDPE) estimates a reference density for each view feature, after which the backward process of BGP maps these multi-view density estimates to their corresponding 3D points. Building on it, anomalous features can be identified by their terminal normality. Unlike conventional flow-based likelihood estimation, our formulation requires neither input reconstruction nor explicit Jacobian evaluation, yielding a simple and efficient anomaly-scoring mechanism. Extensive experiments show that MVFM-3DAD outperforms the strongest competing methods on Real3D-AD and MVTec3D-AD. Code is available at https://github.com/lil-wayne-0319/MV3D-AD

cs.GR↗

arXiv2026

Ferroelectric brightening of spin forbidden dark excitons in a WSe2/hybrid perovskite heterostructure

Long-lived dark excitons in monolayer WSe2 present promising candidates for carrying spin and valley information, but their optical access and spin manipulation have conventionally required the use of strong external magnetic fields. Here, using a ferroelectric hybrid perovskite heterostructure, we leverage the ferroelectric proximity effect to break the WSe2's in-plane rotational symmetry and brighten the spin-forbidden dark excitons under zero magnetic field conditions. Furthermore, we show that the twist angle between the WSe2 and perovskite crystals controls the ferroelectric coupling strength and valley-contrasting polarization. Our proposed mechanism, supported by a four-band tight-binding model, suggests that the ferroelectric proximity effect induces an asymmetric intersublattice interaction, generating an effective in-plane spin-orbit coupling (SOC) field that rotates spin/valley polarization and brightens dark excitons. Our work establishes ferroelectric proximity coupling as an electrically reconfigurable, magnetic-field-free strategy for spin exciton control in two-dimensional semiconductors.

cond-mat.mtrl-sci↗

arXiv2026

Vectorized Generalized Nearest Neighbor Decoding for In-block Memory Channel

This work extends the generalized nearest neighbor decoding (GNND), originally developed as a receiver architecture for memoryless channels, to a vectorized GNND (Vec-GNND) suitable for in-block memory (IBM) channels. Leveraging the generalized mutual information (GMI) as an operational lower bound on the mismatch capacity, an analytical characterization of the optimal Vec-GNND is obtained for general IBM channels with Gaussian codebooks. The formalism further provides closed-form optimality conditions and achievable GMIs for restricted variants of the receiver architecture. Furthermore, we formulate a GMI-based joint design viewpoint for Gaussian codebook covariance and decoding metrics. Since the metric optimization admits a closed-form solution for each fixed covariance, the joint design is reduced to an input-covariance optimization problem; for the diagonal covariance family, we derive first-order self-consistent optimality conditions. Numerical evaluations on block noncoherent additive white Gaussian noise channels and phase noise channels demonstrate consistent performance gains over conventional scaling-based baselines, highlighting the substantial advantages and potential relevance of the proposed Vec-GNND in realistic communication scenarios.

cs.IT↗

arXiv2026

Rotational anisotropy Raman spectrometer for high-sensitivity crystallographic symmetry analysis

Raman spectroscopy stands as a cornerstone technique for probing collective excitations and emergent quantum phases in solids. While polarization-resolved Raman scattering has been widely used to extract symmetry information of eigenmodes, its conventional geometry suffers from significant limitations: it accesses only a subset of Raman tensor elements, enforces {\pi}-periodic intensity patterns that obscure intrinsic crystalline symmetries, and lacks sensitivity to wavevector-dependent anisotropy. To overcome these constraints, here we introduce rotational-anisotropy Raman spectroscopy (RA-Raman). By measuring scattering intensity during full azimuthal rotation of the optical scattering plane at oblique incidence, this geometry enables complete reconstruction of the Raman tensor and reveals rich rotational anisotropy patterns essential for accessing subtle symmetry information elusive to conventional methods. We developed a prototype instrument to validate this approach experimentally. For centrosymmetric crystals, RA-Raman unambiguously identifies phonon symmetry representations and determines crystallographic axes. In noncentrosymmetric crystals, it resolves directional anisotropy and angular dispersion of phonon-polaritons, enabling quantitative determination of the Faust-Henry coefficient and the separation of deformation-potential and electro-optic scattering contributions. By demonstrating unprecedented symmetry-resolving power in standard benchmark crystals, we establish RA-Raman as a powerful tool with far-reaching potential to discover and characterize symmetry-breaking phases and topological excitations in quantum materials.

cond-mat.mtrl-sci↗

arXiv2025

Segmental Attention Decoding With Long Form Acoustic Encodings

We address the fundamental incompatibility of attention-based encoder-decoder (AED) models with long-form acoustic encodings. AED models trained on segmented utterances learn to encode absolute frame positions by exploiting limited acoustic context beyond segment boundaries, but fail to generalize when decoding long-form segments where these cues vanish. The model loses ability to order acoustic encodings due to permutation invariance of keys and values in cross-attention. We propose four modifications: (1) injecting explicit absolute positional encodings into cross-attention for each decoded segment, (2) long-form training with extended acoustic context to eliminate implicit absolute position encoding, (3) segment concatenation to cover diverse segmentations needed during training, and (4) semantic segmentation to align AED-decoded segments with training segments. We show these modifications close the accuracy gap between continuous and segmented acoustic encodings, enabling auto-regressive use of the attention decoder.

eess.AS↗

arXiv2025

Ultrafast cooperative electronic, structural, and magnetic switching in an altermagnet

Femtosecond laser control of antiferromagnetic order is a cornerstone for future memory and logic devices operating at terahertz clock rates. The advent of altermagnets -- antiferromagnets with unconventional spin-group symmetries -- creates new opportunities in this evolving field. Here, we demonstrate ultrafast laser-induced switching in altermagnetic $\alpha$-MnTe that orchestrates the concerted dynamics of charge, lattice, and spin degrees of freedom. Time-resolved reflectivity and birefringence measurements reveal that the transient melting of spin order is accompanied by pronounced structural and electronic instabilities, as evidenced by phonon nonlinearity and accelerated band gap shrinkage. Theoretical modeling highlights the key roles of robust magnetic correlations and spin-charge coupling pathways intrinsic to this altermagnet.

cond-mat.str-el↗

arXiv2025

Quantum Transport in Ultrahigh-Conductivity Carbon Nanotube Fibers

We investigate quantum transport in aligned carbon nanotube (CNT) fibers fabricated via solution spinning, focusing on the roles of structural dimensionality and quantum interference effects. The fibers exhibit metallic behavior at high temperatures, with conductivity increasing monotonically as the temperature decreases from room temperature to approximately 36 K. Below this temperature, the conductivity gradually decreases with further cooling, signaling the onset of quantum conductance corrections associated with localization effects. Magnetoconductance measurements in both parallel and perpendicular magnetic fields exhibit pronounced positive corrections at low temperatures, consistent with weak localization (WL). To determine the effective dimensionality of electron transport, we analyzed the data using WL models in 1D, 2D, and 3D geometries. We found that while the 2D model can reproduce the field dependence, it lacks physical meaning in the context of our fiber architecture and requires an unphysical scaling factor to match the experimental magnitude. By contrast, we developed a hybrid 3D+1D WL framework that quantitatively captures both the field and temperature dependences using realistic coherence lengths and a temperature-dependent crossover parameter. Although this combined model also employs a scaling factor for magnitude correction, it yields a satisfactory fit, reflecting the hierarchical structure of CNT fibers in which transport occurs through quasi-1D bundles embedded in a 3D network. Our results establish a physically grounded model of phase-coherent transport in macroscopic CNT assemblies, providing insights into enhancing conductivity for flexible, lightweight power transmission applications.

cond-mat.mes-hall↗

arXiv2025

An Optimal Transport-Based Method for Computing LM Rate and Its Convergence Analysis

The mismatch capacity characterizes the highest information rate of the channel under a prescribed decoding metric and serves as a critical performance indicator in numerous practical communication scenarios. Compared to the commonly used Generalized Mutual Information (GMI), the Lower bound on the Mismatch capacity (LM rate) generally provides a tighter lower bound on the mismatch capacity. However, the efficient computation of the LM rate is significantly more challenging than that of the GMI, particularly as the size of the channel input alphabet increases. This growth in complexity renders standard numerical methods (e.g., interior point methods) computationally intensive and, in some cases, impractical. In this work, we reformulate the computation of the LM rate as a special instance of the optimal transport (OT) problem with an additional constraint. Building on this formulation, we develop a novel numerical algorithm based on the Sinkhorn algorithm, which is well known for its efficiency in solving entropy regularized optimization problems. We further provide the convergence analysis of the proposed algorithm, revealing that the algorithm has a sub-linear convergence rate. Numerical experiments demonstrate the feasibility and efficiency of the proposed algorithm for the computation of the LM rate.

cs.IT↗

arXiv2025

Time-hidden magnetic order in a multi-orbital Mott insulator

Photo-excited quantum materials can be driven into thermally inaccessible metastable states that exhibit structural, charge, spin, topological and superconducting orders. Metastable states typically emerge on timescales set by the intrinsic electronic and phononic energy scales, ranging from femtoseconds to picoseconds, and can persist for weeks. Therefore, studies have primarily focused on ultrafast or quasi-static limits, leaving the intermediate time window less explored. Here we reveal a metastable state with broken glide-plane symmetry in photo-doped Ca$_2$RuO$_4$ using time-resolved optical second-harmonic generation and birefringence measurements. We find that the metastable state appears long after intralayer antiferromagnetic order has melted and photo-carriers have recombined. Its properties are distinct from all known states in the equilibrium phase diagram and are consistent with intralayer ferromagnetic order. Furthermore, model Hamiltonian calculations reveal that a non-thermal trajectory to this state can be accessed via photo-doping. Our results expand the search space for out-of-equilibrium electronic matter to metastable states emerging at intermediate timescales.

cond-mat.str-el↗

arXiv2025

The Role of Excitatory Parvalbumin-positive Neurons in the Tectofugal Pathway of Pigeon (Columba livia) Hierarchical Visual Processing

The visual systems of birds and mammals exhibit remarkable organizational similarities: the dorsal ventricular ridge (DVR) demonstrates a columnar microcircuitry that parallels the cortical architecture observed in mammals. However, the specific neuronal subtypes involved and their functional roles in pigeon hierarchical visual processing remain unclear. This study investigates the role of excitatory parvalbumin (PV+) neurons within the Ento-MVL (entoallium-mesopallium venterolaterale) circuit of pigeons underlying hierarchical moving target recognition. Electrophysiological recordings and immunofluorescence staining reveal that excitatory PV+ neurons originating from the entopallial internal (Ei) predominantly modulate MVL responses to varying visual stimuli. Using a heterochronous-speed recurrent neural network (HS-RNN) model, we further validated these dynamics, replicating the rapid adaptation of the Ento-MVL circuit to moving visual targets. The findings suggest that the fast-spiking and excitatory properties of PV+ neurons enable rapid processing of motion-related information within the Ento-MVL circuit. Our results elucidate the functional role of excitatory PV+ neurons in hierarchical information processing under the columnar organization of the visual DVR and underscore the convergent neural processing strategies shared by avian and mammalian visual systems.

q-bio.NC↗

arXiv2025

Improving adiabatic quantum factorization via chopped random-basis optimization

Integer factorization remains a significant challenge for classical computers and is fundamental to the security of RSA encryption. Adiabatic quantum algorithms present a promising solution, yet their practical implementation is limited by the short coherence times of current NISQ devices and quantum simulators. In this work, we apply the chopped random-basis (CRAB) optimization technique to enhance adiabatic quantum factorization algorithms. We demonstrate the effectiveness of CRAB by applying it to factor the integers ranging from 21 to 2479, achieving significantly improved fidelity of the target state when the evolution time exceeds the quantum speed limit. Notably, this performance improvement shows resilience in the presence of dephasing noise, highlighting CRAB's practical utility in noisy quantum systems. Our findings suggest that CRAB optimization can serve as a powerful tool for advancing adiabatic quantum algorithms, with broader implications for quantum information processing tasks.

quant-ph↗

arXiv2025

Multisetting protocol for Bell correlated states detection with spin-$f$ systems

We propose a multisetting protocol for the detection of two-body Bell correlations, and apply it to spin-nematic squeezed states realized in $f$ pairs of SU(2) subsystems within spin-$f$ atomic Bose-Einstein condensates. Experimental data for $f=1$, alongside with numerical simulations using the truncated Wigner method for $f=1,\,2,\,3$, demonstrate the effectiveness of the proposed protocol. Our findings extend the reach of multisetting Bell tests in ultracold atomic system, paving the way for extended quantum information processing in high-spin ensemble platforms.

cond-mat.quant-gas↗

arXiv2025

A Hubbard exciton fluid in a photo-doped antiferromagnetic Mott insulator

The undoped antiferromagnetic Mott insulator naturally has one charge carrier per lattice site. When it is doped with additional carriers, they are unstable to spin fluctuation-mediated Cooper pairing as well as other unconventional types of charge, spin, and orbital current ordering. Photo-excitation can produce charge carriers in the form of empty (holons) and doubly occupied (doublons) sites that may also exhibit charge instabilities. There is evidence that antiferromagnetic correlations enhance attractive interactions between holons and doublons, which can then form bound pairs known as Hubbard excitons, and that these might self-organize into an insulating Hubbard exciton fluid. However, this out-of-equilibrium phenomenon has not been detected experimentally. Here, we report the transient formation of a Hubbard exciton fluid in the antiferromagnetic Mott insulator Sr$_{2}$IrO$_{4}$ using ultrafast terahertz conductivity. Following photo-excitation, we observe rapid spectral weight transfer from a Drude metallic response to an insulating response. The latter is characterized by a finite energy peak originating from intra-excitonic transitions, whose assignment is corroborated by our numerical simulations of an extended Hubbard model. The lifetime of the peak is short, approximately one picosecond, and scales exponentially with Mott gap size, implying extremely strong coupling to magnon modes.

cond-mat.str-el↗

arXiv2025

Observation of excitons bound by antiferromagnetic correlations

Two-dimensional Mott insulators host antiferromagnetic (AFM) correlations that are predicted to enhance the attractive interaction between empty (holons) and doubly occupied (doublons) sites, creating a novel pathway for exciton formation. However, experimental confirmation of this spin-mediated binding mechanism remains elusive. Leveraging the distinct magnetic critical properties of the Mott antiferromagnets Sr$_2$IrO$_4$ and Sr$_3$Ir$_2$O$_7$, we show using time-resolved THz spectroscopy that excitons only exist at temperatures below where short-range AFM correlation develops. The excitons remain stable up to photodoping densities approaching the predicted excitonic Mott insulator-to-metal transition, revealing a unique robustness against screening. Our results establish the viability of spin-bound excitons and introduce opportunities for excitonic control through magnetic degrees of freedom.

cond-mat.str-el↗

arXiv2025

Single-Cell Trajectory Reconstruction Reveals Migration Potential of Cell Populations

Cell migration, which is strictly regulated by intracellular and extracellular cues, is crucial for normal physiological processes and the progression of certain diseases. However, there is a lack of an efficient approach to analyze super-statistical and time-varying characteristics of cell migration based on single trajectories. Here, we propose an approach to reconstruct single-cell trajectories, which incorporates wavelet transform, power spectrum of an OU-process, and fits of the power spectrum to analyze statistical and time-varying properties of customized target-finding and migration metrics. Our results reveal diverse relationships between motility parameters and dynamic metrics, especially the existence of an optimal parameter range. Moreover, the analysis reveals that the loss of Arpin protein enhances the migration potential of D. discoideum, and a previously reported result that the rescued amoeba is distinguishable from the wild-type amoeba. Significantly, time-varying dynamic metrics emerge periodic phenomena under the influence of irregularly changing parameters, which correlates with migration potential. Our analysis suggests that the approach provides a powerful tool for estimating time-dependent migration potential and statistical features of single-cell trajectories, enabling a better understanding of the relationship between intracellular proteins and cellular behaviors. This also provides more insights on the migration dynamics of single cells and cell populations.

physics.bio-ph↗

arXiv2025

Optical signatures of noncentrosymmetric structural distortion in altermagnetic MnTe

The hexagonal MnTe is a prime material candidate for altermagnets, an emerging class of magnetic compounds characterized by the nontrivial interplay of antiparallel spin arrangements with their underlying crystal structures. Recognizing precise knowledge of crystal symmetry as the cornerstone of the spin-group classification scheme, we report here a native inversion-symmetry-breaking structural distortion in this compound that has previously been overlooked. Through optical polarimetry experiments and first-principle calculations, we show that MnTe belongs to the noncentrosymmetric $D_{3h}$ group, effectively resolving key inconsistencies in the earlier interpretations of Raman spectroscopy data. Our finding impacts the symmetry analysis of MnTe within the altermagnetic class and sheds light on the mechanism of its magneto-controllable N\'eel order.

cond-mat.mtrl-sci↗