arXiv subjects

Yufei Zhao

Publications and source records attributed to Yufei Zhao.

At least 37 records · Page 2Linked to original sources

arXiv2026

Cramér-Rao Bound Minimization for Flexible Intelligent Metasurface-Enabled ISAC Systems

Integrated sensing and communication (ISAC) have been widely recognized as a key enabler for future wireless networks, where the Cramér-Rao bound (CRB) plays a central role in quantifying sensing accuracy.In this paper, we present the first study on CRB minimization in flexible intelligent metasurface (FIM)-enabled ISAC systems.Specifically, we first derive an average CRB expression that explicitly depends on FIM surface shape and demonstrate that array reconfigurability can substantially reduce the CRB, thereby significantly enhancing sensing performance.Moreover, to tackle the challenging CRB minimization problem, we adopt average Fisher information maximization as a surrogate objective and use the Gauss-Hermite quadrature method to obtain an explicit approximation of the objective function.The resulting problem is then decoupled into three subproblem, i.e., beamforming optimization and transmit/receive FIM surface shape optimization.For beamforming optimization, we employ the Schur complement and penalty-based semi-definite relaxation (SDR) technique to solve it.Furthermore, we propose a fixed-point equation method and a projected gradient algorithm to optimize the surface shapes of the receive and transmit FIMs, respectively.Simulation results demonstrate that, compared to rigid arrays, surface shaping of both transmit and receive FIMs can significantly reduce the average sensing CRB while maintaining communication quality, and remains effective even in multi-target scenarios.

cs.IT↗

arXiv2026

Efficient Beamforming for Discrete SIM-Aided Multiuser Systems Under Statistical CSI

Stacked Intelligent Metasurfaces (SIM) have emerged as a revolutionary architecture for next-generation wireless communications, offering wave-domain signal processing capabilities with significantly reduced hardware complexity compared to conventional systems. However, most existing SIM research assumes continuous phase shifts and perfect instantaneous channel state information (CSI), which are impractical due to hardware discrete phase shift constraints and prohibitive pilot overhead. This paper presents a joint power allocation and discrete phase shift optimization framework for SIM-aided multiuser multiple-input single-output(MISO) downlink systems under statistical CSI. We formulate the achievable sum rate maximization problem considering practical discrete phase constraints and derive a closed-form expression for the average achievable rate under statistical CSI. To tackle the resulting non-convex optimization problem, we decouple the problem by using the weighted minimum mean square error (WMMSE) algorithm and alternating optimization (AO). Subsequently, we utilize the Lagrangian multiplier method and alternating direction method of multipliers (ADMM) to obtain closed-form iterative solutions. Our simulations demonstrate that the proposed algorithm reduces computational complexity by a factor of 50 compared to semi-definite relaxation (SDR) methods, , while maintaining over 85% of the continuous phase shift performance with only 1-bit quantization, highlighting its feasibility for low-cost hardware systems.

cs.IT↗

arXiv2026

Rydberg Atomic Quantum Receivers for Classical Wireless Communications and Sensing: Their Models and Performance

The significant progress of quantum sensing technologies offer numerous radical solutions for measuring a multitude of physical quantities at an unprecedented precision. Among them, Rydberg atomic quantum receivers (RAQRs) emerge as an eminent solution for detecting the electric field of radio frequency (RF) signals, exhibiting great potential in assisting classical wireless communications and sensing. So far, most experimental studies have aimed for the proof of physical concepts to reveal its promise, while the practical signal model of RAQR-aided wireless communications and sensing remained under-explored. Furthermore, the performance of RAQR-based wireless receivers and their advantages over classical RF receivers have not been fully characterized. To fill these gaps, we introduce the RAQR to the wireless community by presenting an end-to-end reception scheme. We then develop a corresponding equivalent baseband signal model relying on a realistic reception flow. Our scheme and model provide explicit design guidance to RAQR-aided wireless systems. We next study the performance of RAQR-aided wireless systems based on our model, and compare them to classical RF receivers. The results show that Doppler broadening-free RAQRs are capable of achieving a substantial received signal-to-noise ratio (SNR) gain of over $27$ decibel (dB) and $40$ dB in the photon shot limit and standard quantum limit regimes, respectively.

eess.SP↗

arXiv2025

QMBench: A Research Level Benchmark for Quantum Materials Research

We introduce QMBench, a comprehensive benchmark designed to evaluate the capability of large language model agents in quantum materials research. This specialized benchmark assesses the model's ability to apply condensed matter physics knowledge and computational techniques such as density functional theory to solve research problems in quantum materials science. QMBench encompasses different domains of the quantum material research, including structural properties, electronic properties, thermodynamic and other properties, symmetry principle and computational methodologies. By providing a standardized evaluation framework, QMBench aims to accelerate the development of an AI scientist capable of making creative contributions to quantum materials research. We expect QMBench to be developed and constantly improved by the research community.

cond-mat.mtrl-sci↗

arXiv2025

Enhanced Information Security via Wave-Field Selectivity and Structured Wavefront Manipulation

In this paper, we propose a novel secure wireless transmission architecture that enables the co-existence of spatial field modulation (SFM) and digital bandpass modulation (DBM), utilizing multi-mode vortex waves and programmable meta-surfaces (PMS). Distinct from conventional joint modulation schemes, our approach establishes two logically independent transmission channels--SFM and DBM--thereby eliminating the need for joint signal design or time synchronization. Specifically, the orthogonality of vortex wave modes is exploited to construct a high-capacity multi-mode DBM channel, in which each mode carries modulated symbols independently. As the composite waveform passes through the PMS, energy from different vortex modes is spatially focused onto distinct positions, dynamically determined by the PMS configuration. This spatial mapping forms a unique lookup table that encodes additional information in the electro-magnetic (EM) field distribution, effectively enabling a second, concurrent SFM channel. To enhance physical-layer security, the DBM channel transmits encrypted symbols transformed via dynamic symbol-domain mapping, while the corresponding mapping relations--or key information--are carried by the SFM channel. This lightweight dual-channel encryption strategy provides strong confidentiality without requiring complex joint decoding. To validate the feasibility of the proposed architecture, we design and implement a proof-of-concept prototype system, and conduct experimental demonstrations under real-world wireless communication conditions. The experimental results confirm the effectiveness of the co-existent DBM-SFM design in achieving reliable and secure transmission. The proposed architecture offers a scalable, low-complexity, and secure transmission solution for future IoT networks, especially in scenarios demanding both spectral efficiency and physical-layer confidentiality.

eess.SP↗

arXiv2025

Spatiotemporal Pyramid Flow Matching for Climate Emulation

Generative models have the potential to transform the way we emulate Earth's changing climate. Previous generative approaches rely on weather-scale autoregression for climate emulation, but this is inherently slow for long climate horizons and has yet to demonstrate stable rollouts under nonstationary forcings. Here, we introduce Spatiotemporal Pyramid Flows (SPF), a new class of flow matching approaches that model data hierarchically across spatial and temporal scales. Inspired by cascaded video models, SPF partitions the generative trajectory into a spatiotemporal pyramid, progressively increasing spatial resolution to reduce computation and coupling each stage with an associated timescale to enable direct sampling at any temporal level in the pyramid. This design, together with conditioning each stage on prescribed physical forcings (e.g., greenhouse gases or aerosols), enables efficient, parallel climate emulation at multiple timescales. On ClimateBench, SPF outperforms strong flow matching baselines and pre-trained models at yearly and monthly timescales while offering fast sampling, especially at coarser temporal levels. To scale SPF, we curate ClimateSuite, the largest collection of Earth system simulations to date, comprising over 33,000 simulation-years across ten climate models and the first dataset to include simulations of climate interventions. We find that the scaled SPF model demonstrates good generalization to held-out scenarios across climate models. Together, SPF and ClimateSuite provide a foundation for accurate, efficient, probabilistic climate emulation across temporal scales and realistic future scenarios. Data and code is publicly available at https://github.com/stanfordmlgroup/spf .

cs.CV↗

arXiv2025

Network-Centric Anomaly Filtering and Spoofer localization for 5G-NR Localization in LAWNs

This paper investigates security vulnerabilities and countermeasures for the 3rd Generation Partnership Project (3GPP) Fifth Generation New Radio (5G-NR) Time Difference of Arrival (TDoA)-based unmanned aerial vehicle (UAV) localization in low-altitude urban environments. We first optimize node selection strategies under Air to Ground (A2G) channel conditions, proving that optimal selection depends on UAV altitude and deployment density, and propose lightweight User Equipment (UE)-assisted approaches that reduce overhead while enhancing accuracy. Next, we then expose critical security vulnerabilities by introducing merged-peak spoofing attacks where rogue UAVs transmit multiple 5G-NR Positioning Reference Signalss (PRSs) that merge with legitimate signals, bypassing existing detection methods. Through theoretical modeling and sensitivity analysis, we quantify how synchronization quality and geometric factors determine spoofing success probability, thereby revealing fundamental weaknesses in current 3GPP positioning frameworks. To address these vulnerabilities, we design a network-centric anomaly detection framework at the Localization Management Function (LMF) using 3GPP-specified parameters, coupled with recursive gradient descent-based robust localization that filters anomalous data while estimating UAV position. Our unified framework simultaneously provides robust victim localization and spoofer localization, enabling active attacker attribution beyond passive defense. Extensive simulations validate the effectiveness of our optimization and security mechanisms for 3GPP-compliant UAV positioning.

eess.SP↗

arXiv2025

Large Language Models for Few-Shot Named Entity Recognition

Named entity recognition (NER) is a fundamental task in numerous downstream applications. Recently, researchers have employed pre-trained language models (PLMs) and large language models (LLMs) to address this task. However, fully leveraging the capabilities of PLMs and LLMs with minimal human effort remains challenging. In this paper, we propose GPT4NER, a method that prompts LLMs to resolve the few-shot NER task. GPT4NER constructs effective prompts using three key components: entity definition, few-shot examples, and chain-of-thought. By prompting LLMs with these effective prompts, GPT4NER transforms few-shot NER, which is traditionally considered as a sequence-labeling problem, into a sequence-generation problem. We conduct experiments on two benchmark datasets, CoNLL2003 and OntoNotes5.0, and compare the performance of GPT4NER to representative state-of-the-art models in both few-shot and fully supervised settings. Experimental results demonstrate that GPT4NER achieves the $F_1$ of 83.15\% on CoNLL2003 and 70.37\% on OntoNotes5.0, significantly outperforming few-shot baselines by an average margin of 7 points. Compared to fully-supervised baselines, GPT4NER achieves 87.9\% of their best performance on CoNLL2003 and 76.4\% of their best performance on OntoNotes5.0. We also utilize a relaxed-match metric for evaluation and report performance in the sub-task of named entity extraction (NEE), and experiments demonstrate their usefulness to help better understand model behaviors in the NER task.

cs.CL↗

arXiv2025

Nonlinear Transport Signatures of Hidden Symmetry Breaking in a Weyl Altermagnet

Phase transitions in solids are often accompanied by structural changes, but subtle lattice distortions can remain hidden from conventional crystallographic probes, hindering the identification of the correct order parameters. A case in point is Ca$_3$Ru$_2$O$_7$, a correlated polar ruthenate with well-characterized phase transitions, whose ground state structure has recently become a subject of debate. This uncertainty stems from extremely small atomic displacements ($\sim$0.001 Å) between competing phases, beyond the resolution of X-ray diffraction, neutron scattering, or optical second-harmonic generation. In this work, we propose a method to detect hidden symmetry breaking by leveraging nonlinear transport induced by quantum geometry. We show that Ca$_3$Ru$_2$O$_7$ is a Weyl chain semimetal in both phases. The low-symmetry phase, classified as an altermagnet by symmetry, features distorted topological surface states that are asymmetric along the polar ($b$) axis. However, the nonrelativistic spin splitting is too weak ($\sim$0.1 meV) to be resolved directly, regarding the altermagnetism. In contrast, Weyl chains generate a large quantum metric at the Fermi surface, leading to nonlinear conductivities that are orders of magnitude stronger in the low-symmetry phase. A longitudinal nonlinear conductivity along the polar axis emerges exclusively in this phase, providing a sensitive probe to qualitatively distinguish it from the high-symmetry structure and demonstrate the emergence of altermangetism, which is confirmed by a recent experiment. Our work establishes a route for identifying hidden symmetry breaking in complex quantum materials through the interplay of crystal symmetry, topology and nonlinear quantum transport.

cond-mat.mtrl-sci↗

arXiv2025

Probing Hidden Symmetry and Altermagnetism with Sub-Picometer Sensitivity via Nonlinear Transport

X-ray and neutron diffraction are foundational tools for determining crystal structures, but their resolution limits can lead to misassignments, especially in materials with subtle distortions or competing phases. Here, we demonstrate the use of nonlinear transport as a complementary approach to uncover hidden crystal symmetries, using the strongly correlated Ca$_3$Ru$_2$O$_7$ as a case study. Below 48 K (T$_S$), where the magnetic moments of the antiferromagnetic phase reorient from the a- to the b-axis, leading to a pseudogap opening, our measurements, with support of DFT, reveal a previously overlooked lower-symmetry phase. This is manifested by the emergence of longitudinal nonlinear resistance (NLR) along the b-axis below T$_S$, providing direct evidence of combined translational and time-reversal symmetry breaking. This response also suggests a transformation from a conventional antiferromagnet into an altermagnet. The lower-symmetry phase arises from a subtle lattice distortion (~0.1 pm) associated with the magnetic transition at T$_S$, below the detection limit of conventional diffraction. Moreover, this NLR below T$_S$ is accompanied by a nonlinear Hall effect, both of which are enhanced by the large quantum metric associated with Weyl chains near the Fermi surface. Our findings demonstrate nonlinear transport as a sensitive probe of hidden symmetry breaking and altermagnetism, complementing and extending beyond the reach of traditional diffraction and spectroscopic techniques.

cond-mat.str-el↗

arXiv2025

Introducing Meta-Fiber into Stacked Intelligent Metasurfaces for MIMO Communications: A Low-Complexity Design with only Two Layers

Stacked intelligent metasurfaces (SIMs), which integrate multiple programmable metasurface layers, have recently emerged as a promising technology for advanced wave-domain signal processing. SIMs benefit from flexible spatial degree-of-freedom (DoF) while reducing the requirement for costly radio-frequency (RF) chains. However, current state-of-the-art SIM designs face challenges such as complex phase shift optimization and energy attenuation from multiple layers. To address these aspects, we propose incorporating meta-fibers into SIMs, with the aim of reducing the number of layers and enhancing the energy efficiency. First, we introduce a meta-fiber-connected 2-layer SIM that exhibits the same flexible signal processing capabilities as conventional multi-layer structures, and explains the operating principle. Subsequently, we formulate and solve the optimization problem of minimizing the mean square error (MSE) between the SIM channel and the desired channel matrices. Specifically, by designing the phase shifts of the meta-atoms associated with the transmitting-SIM and receiving-SIM, a non-interference system with parallel subchannels is established. In order to reduce the computational complexity, a closed-form expression for each phase shift at each iteration of an alternating optimization (AO) algorithm is proposed. We show that the proposed algorithm is applicable to conventional multi-layer SIMs. The channel capacity bound and computational complexity are analyzed to provide design insights. Finally, numerical results are illustrated, demonstrating that the proposed two-layer SIM with meta-fiber achieves over a 25% improvement in channel capacity while reducing the total number of meta-atoms by 59% as compared with a conventional seven-layer SIM.

cs.IT↗

arXiv2025

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models

Rotations have become essential to state-of-the-art quantization pipelines for large language models (LLMs) by effectively smoothing outliers in weights and activations. However, further optimizing the rotation parameters offers only limited performance gains and introduces significant training overhead: due to rotation parameter sharing, full-model must be loaded simultaneously to enable backpropagation, resulting in substantial memory consumption and limited practical utility. In this work, we identify two fundamental limitations of current rotational quantization methods: (i) rotation fails to align channel means, resulting in wider quantization bounds and increased rounding errors; and (ii) rotation makes the activation distribution more Gaussian-like, increasing energy loss caused by clipping errors. To address these issues, we introduce \textbf{BASE-Q}, a simple yet powerful approach that combines bias correction and asymmetric scaling to effectively reduce rounding and clipping errors. Furthermore, BASE-Q enables blockwise optimization, eliminating the need for memory-intensive full-model backpropagation. Extensive experiments on various LLMs and benchmarks demonstrate the effectiveness of BASE-Q, narrowing the accuracy gap to full-precision models by 50.5\%, 42.9\%, and 29.2\% compared to QuaRot, SpinQuant, and OSTQuant, respectively. The code will be released soon.

cs.LG↗

arXiv2025

Room temperature quantum metric effect in TbMn6Sn6

Quantum geometry, including Berry curvature and the quantum metric, of the electronic Bloch bands has been studied via nonlinear responses in topological materials. Naturally, these material systems with intrinsic strong nonlinear responses also form the key component in nonlinear electronic devices. However, the previous reported quantum geometry effects are mainly observed at cryogenic temperatures, hindering their application in practical devices. Here we report the tuneable strong room-temperature second-harmonic transport response in a quantum magnet, TbMn6Sn6, which is governed by the quantum metric and can be tuned with applied magnetic fields. We show that around room temperature, which is close to the spontaneous spin-reorientation transition, the magnetic configurations, and therefore the related symmetry breaking phases, are easily controlled via magnetic fields. Our results also show that manipulation of the symmetries of the magnetic structure presents an effective route to tuneable quantum-geometry-based devices.

cond-mat.mtrl-sci↗

arXiv2025

Discovery of transient topological crystalline order in optically driven SnSe

Ultrafast optical excitation provides a powerful route for accessing emergent quantum phases far from equilibrium, enabling transient light-induced phenomena such as magnetism, ferroelectricity, and superconductivity. However, extending this approach to induce topological phases, especially in conventional semiconductors, remains challenging. Here, we report the observation of a thermally inaccessible, transient topological crystalline order in the layered semiconductor SnSe, a trivial insulator with a sizable (~ 0.8 eV) band gap, induced by femtosecond above-gap excitation. Time- and angle-resolved photoemission spectroscopy directly reveals the sub-picosecond emergence of Dirac-like linear dispersions within the band gap. Their features, including a high Fermi velocity (~ 2.5x10^5 m/s), multiple Dirac points away from high-symmetry momenta, and independence from probe photon energy, are consistent with mirror-symmetry-protected surface states of a topological crystalline insulator. The observed spectral dynamics, combined with density functional theory calculations, indicate that the femtosecond excitation transiently increases lattice symmetry, enabling topological crystalline order to emerge. Our discovery opens new avenues for ultrafast optical control of topological quantum phases in semiconductors, with potential applications in quantum and spintronic devices.

cond-mat.mtrl-sci↗

arXiv2025

Uniform sets with few progressions via colorings

Ruzsa asked whether there exist Fourier-uniform subsets of $\mathbb Z/N\mathbb Z$ with density $α$ and 4-term arithmetic progression (4-AP) density at most $α^C$, for arbitrarily large $C$. Gowers constructed Fourier uniform sets with density $α$ and 4-AP density at most $α^{4+c}$ for some small constant $c>0$. We show that an affirmative answer to Ruzsa's question would follow from the existence of an $N^{o(1)}$-coloring of $[N]$ without symmetrically colored 4-APs. For a broad and natural class of constructions of Fourier-uniform subsets of $\mathbb Z/N\mathbb Z$, we show that Ruzsa's question is equivalent to our arithmetic Ramsey question. We prove analogous results for all even-length APs. For each odd $k\geq 5$, we show that there exist $U^{k-2}$-uniform subsets of $\mathbb Z/N\mathbb Z$ with density $α$ and $k$-AP density at most $α^{c_k \log(1/α)}$. We also prove generalizations to arbitrary one-dimensional patterns.

math.CO↗

arXiv2025

Compact Varactor-Integrated RIS for Wideband and Continuously Tunable Beamforming

This letter presents a novel Reconfigurable Intelligent Surface (RIS) that features a low-profile structure, wide operating bandwidth, and continuous phase control. By incorporating a middle patch layer without introducing an additional air gap, the proposed design maintains a thin form factor, while achieving a smooth 310° phase shift over 10\% bandwidth at 6.1 GHz with excellent reflection. A fabricated 10*10 RIS array exhibits stable performance, enabling precise beam control across a 600 MHz bandwidth. These results highlight the potential of the proposed low-profile, wideband RIS with continuous phase tuning for next-generation wireless communication systems.

eess.SP↗

arXiv2025

Focusing Metasurfaces of (Un)equal Power Allocations for Wireless Power Transfer

Focusing metasurfaces (MTSs) tailored for different power allocations in wireless power transfer (WPT) system are proposed in this letter. The designed metasurface unit cells ensure that the phase shift can cover over a 2π span with high transmittance. Based on near-field focusing theory, an adapted formula is employed to guide the phase distribution for compensating incident waves. Three MTSs, each with dimensions of 190*190 mm and comprising 19*19 unit cells, are constructed to achieve dual-polarized two foci with 1:1, 2:1, and 3:1 power allocations, yielding maximum focusing efficiencies of 71.6%, 65.2%, and 57.5%, respectively. The first two MTSs are fabricated and tested, demonstrating minimal -3 dB depth of focus (DOF). Results are aligned with theoretical predictions. These designs aim to facilitate power transfer to different systems based on their specific requirements in an internet of things (IoT) environment.

eess.SP↗

arXiv2025

Surface-Dominated Quantum Metric-Induced Nonlinear Transport in the Layered Antiferromagnet CrSBr

The van der Waals (vdW) antiferromagnet CrSBr has recently garnered significant attention due to its air stability, high magnetic transition temperature, and semiconducting properties. We investigate its nonlinear transport properties and identify a quantum metric dipole-induced nonlinear anomalous Hall effect and nonlinear longitudinal resistivity, which switch sign upon reversing the Néel vector. The significant quantum metric dipole originates from Dirac nodal lines near the conduction band edge within the experimentally achievable doping range. Known the weak interlayer coupling, it is unexpected that the nonlinear conductivities do not scale with sample thickness but are dominantly contributed by surface layers. In the electron-doped region, the top layer dominates the response while the top three layers contribute the most in the hole-doped region. Our results establish topological nodal lines as a guiding principle to design high-performance nonlinear quantum materials and suggest that surface-sensitive transport devices will provide new avenues for nonlinear electronic applications.

cond-mat.mes-hall↗