arXiv:2512.17703cond-mat.str-elcond-mat.mtrl-sci2025-12被引 2

用神经网络量子蒙特卡洛方法重探高压氢的对称性破缺相,发现新稳定结构。

Revisiting the Broken Symmetry Phase of Solid Hydrogen: A Neural Network Variational Monte Carlo Study

  • 构建基于深度神经网络的量子蒙特卡洛框架,同时量子化处理电子与原子核。
  • 发现新型Cmcm对称性晶体结构,与实验压强-体积关系和衍射图样高度吻合。
  • 揭示传统密度泛函计算的局限性,强调需全量子多体方法研究高压氢。

高压固态氢的晶格结构仍是基础科学中的开放难题。尽管研究前沿已转向400 GPa以上的超高压相,我们发现130 GPa附近的对称性破缺相仍需重新审视,因其电子与核自由度存在复杂耦合。本文发展了一种基于深度神经网络波函数的第一性原理量子蒙特卡洛框架,在恒压系综下实现电子与原子核的完全量子化处理。计算揭示了一个未报道的对称性破缺相基态结构候选,具有Cmcm空间群对称性,并验证其在96个原子规模下的稳定性。该结构预测的压强-体积关系(方程态)与实验X射线衍射数据高度一致。进一步群论分析表明,该结构与现有拉曼及红外光谱数据兼容。关键的是,静态密度泛函计算显示,该结构在玻恩-奥本海默势能面上为动态不稳定的鞍点,证明必须采用完整的量子多体方法。这些结果为高压氢相图提供了新见解,并呼吁进一步实验验证。

原文摘要 · Abstract (English)

The crystal structure of high-pressure solid hydrogen remains a fundamental open problem. Although the research frontier has mostly shifted toward ultra-high pressure phases above 400 GPa, we show that even the broken symmetry phase observed around 130~GPa requires revisiting due to its intricate coupling of electronic and nuclear degrees of freedom. Here, we develop a first principle quantum Monte Carlo framework based on a deep neural network wave function that treats both electrons and nuclei quantum mechanically within the constant pressure ensemble. Our calculations reveal an unreported ground-state structure candidate for the broken symmetry phase with $Cmcm$ space group symmetry, and we test its stability up to 96 atoms. The predicted structure quantitatively matches the experimental equation of state and X-ray diffraction patterns. Furthermore, our group-theoretical analysis shows that the $Cmcm$ structure is compatible with existing Raman and infrared spectroscopic data. Crucially, static density functional theory calculation reveals the $Cmcm$ structure as a dynamically unstable saddle point on the Born-Oppenheimer potential energy surface, demonstrating that a full quantum many-body treatment of the problem is necessary. These results shed new light on the phase diagram of high-pressure hydrogen and call for further experimental verifications.

高压物理量子蒙特卡洛神经网络氢相图

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