arXiv subjects

Wenwen Zhao

Publications and source records attributed to Wenwen Zhao.

9 recordsLinked to original sources

arXiv2026

Strain-Induced Relaxor Multiferroicity at Room Temperature in Hexaferrite BaFe12O19 Thin Films

Multiferroic materials that combine magnetic and electric order at room temperature are rare. Here, we demonstrate strain-induced room-temperature polar order in the ferrimagnetic hexaferrite BaFe12O19. First-principles calculations reveal a strain-tunable energy landscape with multiple competing dipolar configurations and predict that compressive strain favors polar distortions. Using an isostructural Sr1.03Ga10.81Mg0.58Zr0.58O19 substrate, we grow coherently strained BaFe12O19 films with 1.1% in-plane biaxial compression. Second-harmonic generation measurements demonstrate inversion-symmetry breaking and establish a strain-stabilized polar phase that persists to at least 1000 K. Multislice electron ptychography directly reveals enhanced off-centering of Fe3+ ions within the trigonal-bipyramidal sites of the strained films and spatially varying local polarization, demonstrating the formation of polar nanoregions. Path-integral Monte Carlo simulations further show that compressive strain suppresses quantum fluctuations and stabilizes these local polar distortions. Together, these results establish strain-engineered BaFe12O19 as a room-temperature relaxor multiferroic, in which robust ferrimagnetism coexists with nanoscale polar order. Our work demonstrates a route for transforming an incipient ferroelectric ferrimagnetic into a polar magnetic material through epitaxial strain.

cond-mat.mtrl-sci↗

arXiv2026

Loss Mechanisms in Cryogenic Microwave Epitaxial AlN Resonators

Epitaxial aluminum nitride (AlN) thin-film bulk acoustic resonators (FBARs) enable low loss filtering for future 6G systems. They also provide a compact approach for qubit sensing at cryogenic temperatures. However, these devices are rarely characterized systematically from room temperature to cryogenic temperatures, and the mechanisms that limit their cryogenic performance remain unclear. In this work, we study a 15.6 GHz epitaxial AlN FBAR from room temperature to cryogenic temperatures to identify losses from the AlN film and those introduced by the electrodes, anchors, and other device layers. Small signal RF measurements from 294 K down to 6.5 K show an increase in the raw Qmax from 363 to 1589. A temperature dependent model that includes phonon phonon scattering, thermoelastic damping, dielectric loss, electrical loss, and anchor loss helps explain the measured Q(T) trend and identifies a transition from the Landau Rumer to the Akhiezer regime near 270 K. The model indicates that acoustic energy leakage through the anchors limits Q at cryogenic temperatures, while electrical loss dominates at higher temperatures. These results point to two routes toward higher cryogenic Q: better acoustic isolation of the anchors and lower loss electrodes, including superconducting electrodes. Improved anchor design benefits both high frequency 6G filters and cryogenic quantum microwave circuits, while superconducting electrodes are particularly useful for cryogenic operation.

cond-mat.mes-hall↗

arXiv2026

EP-GRPO: Entropy-Progress Aligned Group Relative Policy Optimization with Implicit Process Guidance

Reinforcement learning with verifiable rewards (RLVR), particularly Group Relative Policy Optimization (GRPO), has advanced LLM reasoning. However, GRPO suffers from three credit assignment failures: uniform token-level granularity that ignores heterogeneous informational value, uniform polarity that penalizes correct steps and rewards incorrect ones, and zero-variance collapse that erases outcome-driven gradients. We systematically quantify these failures, revealing highly non-uniform token informativeness, widespread step-level polarity misalignment, and substantial training waste. To address these limitations, we propose Entropy-Progress Aligned GRPO (EP-GRPO), a framework that mines the model's intrinsic information flow for dense, self-supervised guidance. EP-GRPO integrates entropy-gated modulation to prioritize high entropy decision pivots, implicit process signals from policy divergence anchored to outcome advantages for directional token-level feedback without external reward models, and cumulative entropy mapping that enables progress-aligned advantage normalization, naturally maintaining gradient flow under zero reward variance. Extensive experiments on mathematical reasoning benchmarks demonstrate that EP-GRPO achieves superior accuracy and efficiency compared to GRPO and its variants. The code will be available.

cs.LG↗

arXiv2026

ERPO: Token-Level Entropy-Regulated Policy Optimization for Large Reasoning Models

Reinforcement learning from verifiable rewards has significantly advanced the reasoning capabilities of large language models. However, Group Relative Policy Optimization (GRPO) typically assigns a uniform, sequence-level advantage to all tokens, thereby overlooking the intrinsic information heterogeneity along reasoning chains. We show that this coarse-grained credit assignment leads to premature entropy collapse and encourages the model to generate redundant, low-quality reasoning paths. Through systematic empirical analysis, we identify Critical Decision Pivots (CDPs): transient high-entropy states where the policy's trajectory is most sensitive to perturbations. These pivots represent the "forks in the road" where effective multi-path exploration is most crucial yet often suppressed by uniform advantage signals. Building on these insights, we propose Entropy-Regulated Policy Optimization (ERPO), which transitions the optimization focus from coarse sequences to fine-grained token dynamics. ERPO introduces three synergistic components: (i) Entropy-aware Gating, which adaptively amplifies exploration at CDPs to facilitate diverse path discovery; (ii) Bucket-based Implicit Normalization, which mitigates difficulty bias by aligning token progress windows; and (iii) Result-anchored Advantage Synthesis, which re-weights token-level signals via outcome-driven anchors. Extensive experiments on competitive mathematical benchmarks demonstrate that ERPO significantly outperforms GRPO. Notably, ERPO not only boosts reasoning accuracy but also yields significantly more concise and robust derivation paths, while achieving performance comparable to large models with orders of magnitude more parameters.

cs.LG↗

arXiv2025

A multi-ansatz variational quantum solver for compressible flows

Simulating nonlinear partial differential equations (PDEs) such as the Navier--Stokes (NS) equations remains computationally intensive, especially when implicit time integration is used to capture multiscale flow dynamics. This work introduces a hybrid quantum--classical framework for solving the linear systems arising from such implicit schemes in compressible flow simulations. At its core is a variational quantum linear solver (VQLS) enhanced by a multi-ansatz tree architecture, designed to expand the accessible solution space and alleviate training issues such as barren plateaus. The proposed method is evaluated through one-dimensional shock tube simulations implemented on a quantum virtual machine. Results demonstrate that the solver accurately captures shock, rarefaction, and contact discontinuities across a range of test cases. Parametric studies further show that increasing the number of ansatz branches and applying domain decomposition improves convergence and stability, even under limited qubit resources. These findings suggest that multi-ansatz VQLS architectures offer a promising pathway for incorporating quantum computing into computational fluid dynamics (CFD), with compatibility for both current noisy intermediate-scale quantum (NISQ) hardware and future fault-tolerant devices.

physics.flu-dyn↗

arXiv2025

Simulating fluid vortex interactions on a superconducting quantum processor

Vortex interactions are commonly observed in atmospheric turbulence, plasma dynamics, and collective behaviors in biological systems. However, accurately simulating these complex interactions is highly challenging due to the need to capture fine-scale details over extended timescales, which places computational burdens on traditional methods. In this study, we introduce a quantum vortex method, reformulating the Navier--Stokes (NS) equations within a quantum mechanical framework to enable the simulation of multi-vortex interactions on a quantum computer. We construct the effective Hamiltonian for the vortex system and implement a spatiotemporal evolution circuit to simulate its dynamics over prolonged periods. By leveraging eight qubits on a superconducting quantum processor with gate fidelities of 99.97\% for single-qubit gates and 99.76\% for two-qubit gates, we successfully reproduce natural vortex interactions. This method bridges classical fluid dynamics and quantum computing, offering a novel computational platform for studying vortex dynamics. Our results demonstrate the potential of quantum computing to tackle longstanding challenges in fluid dynamics and broaden applications across both natural and engineering systems.

quant-ph↗

arXiv2025

Improper Ferroelectricity at the Monolayer Limit

Ultrathin ferroelectric films with out-of-plane polarization and high Curie temperatures are key to miniaturizing electronic devices. Most ferroelectrics employed in devices are proper ferroelectrics, where spontaneous polarization is the primary order parameter. Unfortunately, the Curie temperature of proper ferroelectrics is drastically reduced as the ferroelectric becomes thin; nearly all proper ferroelectrics need to be thicker than several unit cells. The absence of an ultrathin limit has been predicted, but not verified for improper ferroelectrics. These are ferroelectrics where the polarization emerges secondary to the primary order parameter, such as a structural distortion. Here we report improper ferroelectricity with an undiminished Curie temperature in a 0.75-unit-cell-thick hexagonal LuFeO3 (h-LuFeO3) film grown on a SrCo2Ru4O11 bottom electrode with an atomically engineered monolayer bridging layer. Our results demonstrate the absence of a critical thickness for improper ferroelectricity and provide a methodology for creating ultrathin improper ferroelectrics by stabilizing their primary order parameters.

cond-mat.mtrl-sci↗

arXiv2018

Numerical Investigation on Local Non-equilibrium Flows Using a Diatomic Nonlinear Constitutive Model

The linear Navier-Stokes-Fourier (NSF) constitutive relations are capable of simulating the near-continuum flows, but fail in description of those flows which are removed far away from local equilibrium. In this paper, a diatomic nonlinear model named as nonlinear coupled constitutive relations (NCCR), derived from Eu's generalized hydrodynamics and proposed by Myong, is presented as an alternative for simulating these hypersonic gas flows with a goal of recovering NSF's solutions in continuum regime and being superior in transition regime. To guarantee stable computation, a reliable and efficient coupled algorithm is proposed for this diatomic nonlinear constitutive model. Constitutive-curve analysis is carried out in detail to compare this coupled algorithm with Myong's previous algorithm. Local flow regions are investigated carefully in these hypersonic flows past a cone tip, a hollow cylinder-flare and a HTV-type vehicle. The convergent solutions of NCCR model are compared with NSF, DSMC calculations and experiment. It is demonstrated that the NCCR model works as efficiently as the NSF model in continuum regime, but more accurately compared with DSMC and experiment than NSF in non-equilibrium flows. The discrepancies of flow- field and surface parameters, imply a potential for remedying NSF's deficiency in local non-equilibrium regions.

physics.flu-dyn↗

arXiv2016

A new coupled computational method in conjunction with three-dimensional finite volume schemes for nonlinear coupled constitutive relations

Non-equilibrium effects play a vital role in high-speed and rarefied gas flows and the accurate simulation of these flow regimes are far beyond the capability of near-local-equilibrium Navier-Stokes-Fourier equations. Eu proposed generalized hydrodynamic equations which are consistent with the laws of irreversible thermodynamics to solve this problem. Based on Eu's generalized hydrodynamics equations, a computational model, namely the nonlinear coupled constitutive relations(NCCR),was developed by R.S.Myong and applied successfully to one-dimensional shock wave structure and two-dimensional rarefied flows. In this paper, finite volume schemes, including LU-SGS time advance scheme, MUSCL interpolation and AUSMPW+ scheme, are fistly adopted to investigate NCCR model's validity and potential in three-dimensional complex hypersonic rarefied gas flows. Moreover, in order to solve the computational stability problems in 3D complex flows,a modified solution is developed for the NCCR model. Finally, the modified solution is tested for a slip complex flow over a 3D hollow cylinder-flare configuration. The numerical results show that the NCCR model by the modified solution yields good solutions in better agreement with the DSMC results and experimential data than NSF equations, and imply NCCR model's great potential capability in further application.

physics.flu-dyn↗