Molecular Dynamics (MD) simulations are ubiquitous in cutting-edge physio-chemical research. They provide critical insights into how a physical system evolves over time given a model of interatomic interactions. Understanding a system's evolution is key to selecting the best candidates for new drugs, materials for manufacturing, and countless other practical applications. With today's technology, these simulations can encompass millions of unit transitions between discrete molecular structures, spanning up to several milliseconds of real time. Attempting to perform a brute-force analysis with data-sets of this size is not only computationally impractical, but would not shed light on the physically-relevant features of the data. Moreover, there is a need to analyze simulation ensembles in order to compare similar processes in differing environments. These problems call for an approach that is analytically transparent, computationally efficient, and flexible enough to handle the variety found in materials based research. In order to address these problems, we introduce MolSieve, a progressive visual analytics system that enables the comparison of multiple long-duration simulations. Using MolSieve, analysts are able to quickly identify and compare regions of interest within immense simulations through its combination of control charts, data-reduction techniques, and highly informative visual components. A simple programming interface is provided which allows experts to fit MolSieve to their needs. To demonstrate the efficacy of our approach, we present two case studies of MolSieve and report on findings from domain collaborators.

翻译：摘要：分子动力学（MD）模拟在尖端物理化学研究中应用广泛。通过模拟原子间相互作用的模型，这些模拟揭示了物理系统随时间演化的关键机制。理解系统演化是筛选新药候选分子、制造材料及其他大量实际应用的基础。现代技术使得这些模拟能够涵盖离散分子结构间的数百万次单元跃迁，时间跨度可达数毫秒实时。对此类规模的数据集进行暴力分析不仅计算上不切实际，更无法揭示数据的物理相关特征。此外，还需对模拟集合进行对比分析，以比较不同环境中相似过程的差异。这些问题要求一种兼具分析透明性、计算高效性且能灵活处理材料研究中多样性的方法。为此，我们提出了MolSieve——一种支持多次长时模拟对比的渐进式可视化分析系统。通过结合控制图、数据降维技术及高信息密度可视化组件，MolSieve使分析人员能够快速识别并比较庞大模拟中的感兴趣区域。系统提供简洁的编程接口，便于专家根据需求定制适配。通过两个案例研究及领域合作者的反馈，我们验证了该方法的有效性。