预测玻璃模型中激活势垒与塑性起始统计

中文摘要 AI 辅助

最近引入的一个非谐平均场模型统一再现了广泛的低温玻璃现象——包括谐波非声子谱特性、线性微力学和强驱动弹塑性动力学——表明其底层能量景观本质上是玻璃态的。在此，我们将非线性模式框架应用于该模型，并推导出激活势垒渐近分布 $p(\Delta{U})\sim(\Delta{U})^{1/4}$ 和塑性起始所需外力 $p(f_{\rm c})\sim f_{\rm c}^{2/3}$ 的解析预测，以及它们的极值标度和渐近区域之外的 $\langle\Delta{U}\rangle$。这些预测预计同样适用于平均场模型和有限维玻璃。我们开发了高效算法来采样模型玻璃态势能景观中的极小值和鞍点，并定量确认了理论预测。这一进展得益于识别出一组对激活玻璃动力学具有物理相关性的集体自由度，这些自由度与理论预测一样，应适用于真实玻璃。

英文摘要

A recently introduced anharmonic mean-field model unifiedly reproduced a broad range of low-temperature glass phenomena --- including harmonic nonphononic spectral properties, linear micromechanics and strongly driven elasto-plastic dynamics --- indicating that its underlying energy landscape is intrinsically glassy. Here, we apply a nonlinear modes framework to the model and derive analytic predictions for the asymptotic distributions of activation barriers $p(Δ{U})\!\sim\!(Δ{U})^{1/4}$ and the external force needed for the onset of plasticity $p(f_{\rm c})\sim f_{\rm c}^{2/3}$, for their extreme-value scaling and for $\langleΔ{U}\rangle$ beyond the asymptotic regime. These predictions are expected to equally apply to the mean-field model and to finite-dimensional glasses. We develop efficient algorithms for sampling minima and saddles of the model's glassy potential energy landscape, and quantitatively confirm the theoretical predictions. This progress is enabled by identifying a subset of collective degrees of freedom that are physically relevant for activated glassy dynamics, which like the theoretical predictions should apply to realistic glasses.

发表机构

• Tohoku University（东北大学）
• University of Amsterdam（阿姆斯特丹大学）
• Weizmann Institute of Science（魏茨曼科学研究所）

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