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Română(RO) SupraTITO: Transferable Generative Molecular Dynamics for Supramolecular Systems

生成模型加速跨时间尺度的分子动力学模拟

研究人员开发了新的生成分子动力学框架,显著加速了分子过程的模拟。SupraTITO框架在其中一篇论文中进行了详细介绍,它使用基于序列和拓扑的可迁移隐式传递算子,能够比传统方法传播更长时间间隔的构型。另一项研究介绍了一种深度生成建模方法,将分子动力学采样速度提高了四个数量级,能够定量表征平衡系综和动力学弛豫过程。这两种方法都展示了跨不同化学组成和系统尺寸的泛化能力,在不牺牲原子细节的情况下扩展了可访问的分子运动范围。 AI

影响 生成分子动力学领域的这些进展可能显著加速化学和生物物理领域的研究,从而更深入地理解分子过程。

排序理由 两篇arXiv论文详细介绍了生成分子动力学的新研究。

在 arXiv cs.LG 阅读 →

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生成模型加速跨时间尺度的分子动力学模拟

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两篇arXiv论文详细介绍了生成分子动力学的新研究。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 Română(RO) · Weilong Chen, Nuno Costa, Julija Zavadlav ·

    SupraTITO:用于超分子体系的可转移生成分子动力学

    arXiv:2610.01381v1 Announce Type: cross Abstract: Peptide sequence governs both the structures formed through supramolecular assembly and the dynamics by which they emerge, but predicting either requires resolving slow collective processes among many interacting molecules. Molecu…

  2. arXiv stat.ML TIER_1 English(EN) · Juan Viguera Diez, Mathias Schreiner, Simon Olsson ·

    可迁移生成模型连接飞秒到纳秒时间步分子动力学

    arXiv:2510.07589v2 Announce Type: replace-cross Abstract: Understanding molecular structure, dynamics, and reactivity requires bridging processes that occur across widely separated time scales. Conventional molecular dynamics simulations provide atomistic resolution, but their fe…