arXiv subjects

Dongxue Liu

Publications and source records attributed to Dongxue Liu.

6 recordsLinked to original sources

arXiv2026

On the degradation of hot spot performance due to mid-to-high-mode hydrodynamic instabilities

In an ignited design of inertial confinement fusion, the role of mid-to-high-mode hydrodynamic instabilities in degrading hot-spot performance, beyond reducing temperature, remains unclear. To address this, we propose an isobaric criterion to assess the isobaric assumption that forms the theoretical basis of the hot spot. The most dangerous mode l = 12 is determined through a balance between perturbation growth and ablation stabilization induced by thermal conduction. Thermal conduction outperforms convection when the Peclet number is much less than 1. Therefore, for mid-to-high modes, thermal conduction makes the hot spot isobaric before the outer mass inflow restores the lost heat. Consequently, neglecting thermal conduction overestimates pressure and underestimates volume. These results enhance our understanding of mid-to-high modes in degrading hot-spot performance, and suggest that thermal conduction losses may reduce performance even if perturbations are nearly stabilized by ablation.

physics.flu-dyn↗

arXiv2026

A theoretical model for quantifying the imprinting sensitivity of direct-drive inertial confinement fusion implosions

To quantify the sensitivity of diverse implosion designs to laser imprinting, we developed an equivalent perturbation model that maps laser imprinting as the initial target surface perturbation. By incorporating imperfections in target fabrication and thermal smoothing in the plasma, the model shows a reduced implosion sensitivity to laser imprinting, extending the analysis beyond geometric irradiation. The imprinting sensitivity threshold is defined as $\frac{\delta h_{\text{proxy}}}{\delta h_{\text{tar}}(0)} = 0.1$, where $\delta h_{\text{proxy}}$ is the imprinting amplitude and $\delta h_{\text{tar}}(0)$ is the initial target perturbation amplitude. Radiation-hydrodynamics simulations confirm that when $\frac{\delta h_{\text{proxy}}}{\delta h_{\text{tar}(0)}} \leq 0.1$, variations in nonlinear onset time and adiabat remain within 12\% of that with $\delta h_{\text{tar}}(0)$ alone. Moreover, the imprinting sensitivity is supported by OMEGA experiments. Overall, for linear perturbations of medium-to-high modes in direct-drive, the model enhances our physical understanding of how laser and target perturbations evolve and serves as a simplified tool to optimize implosion performance.

physics.plasm-ph↗

arXiv2026

ERNIE 5.0 Technical Report

In this report, we introduce ERNIE 5.0, a natively autoregressive foundation model desinged for unified multimodal understanding and generation across text, image, video, and audio. All modalities are trained from scratch under a unified next-group-of-tokens prediction objective, based on an ultra-sparse mixture-of-experts (MoE) architecture with modality-agnostic expert routing. To address practical challenges in large-scale deployment under diverse resource constraints, ERNIE 5.0 adopts a novel elastic training paradigm. Within a single pre-training run, the model learns a family of sub-models with varying depths, expert capacities, and routing sparsity, enabling flexible trade-offs among performance, model size, and inference latency in memory- or time-constrained scenarios. Moreover, we systematically address the challenges of scaling reinforcement learning to unified foundation models, thereby guaranteeing efficient and stable post-training under ultra-sparse MoE architectures and diverse multimodal settings. Extensive experiments demonstrate that ERNIE 5.0 achieves strong and balanced performance across multiple modalities. To the best of our knowledge, among publicly disclosed models, ERNIE 5.0 represents the first production-scale realization of a trillion-parameter unified autoregressive model that supports both multimodal understanding and generation. To facilitate further research, we present detailed visualizations of modality-agnostic expert routing in the unified model, alongside comprehensive empirical analysis of elastic training, aiming to offer profound insights to the community.

cs.CL↗

arXiv2024

SolarDesign: An Online Photovoltaic Device Simulation and Design Platform

SolarDesign (https://solardesign.cn/) is an online photovoltaic device simulation and design platform that provides engineering modeling analysis for crystalline silicon solar cells, as well as emerging high-efficiency solar cells such as organic, perovskite, and tandem cells. The platform offers user-updatable libraries of basic photovoltaic materials and devices, device-level multi-physics simulations involving optical-electrical-thermal interactions, and circuit-level compact model simulations based on detailed balance theory. Employing internationally advanced numerical methods, the platform accurately, rapidly, and efficiently solves optical absorption, electrical transport, and compact circuit models. It achieves multi-level photovoltaic simulation technology from ``materials to devices to circuits'' with fully independent intellectual property rights. Compared to commercial software, the platform achieves high accuracy and improves speed by more than an order of magnitude. Additionally, it can simulate unique electrical transport processes in emerging solar cells, such as quantum tunneling, exciton dissociation, and ion migration.

physics.optics↗

arXiv2024

A one-dimensional mixing model for the impact of ablative Rayleigh-Taylor instability on compression dynamics

A one-dimensional mixing model, incorporating the effects of laser ablation and initial perturbations, is developed to study the influence of ablative Rayleigh-Taylor instability on compression dynamics. The length of the mixing region is determined with the buoyancy-drag model[arXiv:2411.12392v2 (2024)]. The mixing effect on laser ablation is mainly described with an additional heat source which depends on turbulent kinetic energy and initial perturbation level through a free multiplier. The model is integrated into a one-dimensional radiation hydrodynamics code and validated against two-dimensional planar simulations. The further application of our model to spherical implosion simulations reveals that the model can give reasonable predictions of implosion degradation due to mixing, such as lowered shell compression, reduced stagnation pressure, and decreased areal density, etc. It is found that the time interval between the convergence of the main shock and stagnation may offer an estimate of mixing level in single-shot experiments.

physics.flu-dyn↗

arXiv2024

A buoyancy-drag model with a time-varying drag coefficient for evaluating bubble front penetration depth

To evaluate and control bubble front penetration depth ${{h}_{B}}$ induced by ablative Rayleigh-Taylor instability (ARTI) from a weakly nonlinear phase to a self-similar phase, we first propose an improved buoyancy-drag (BD) model with a time-varying drag coefficient. The coefficient incorporates the influence of multiple physical mechanisms, including non-steady ablation, preheating, and other mechanisms during this phase. The model is validated through simulations under various conditions, demonstrating improved accuracy compared to the classical BD model and the self-similar growth. Furthermore, the model suggests controlling ${{h}_{B}}$ by suppressing the "most dangerous mode", which is influenced by initial perturbations and ablative acceleration history, thus offering novel insights for target manufacturing and pulse optimization near the ignition threshold.

physics.flu-dyn↗