Simulation ensembles are a common tool in physics for understanding how a model outcome depends on input parameters. We analyze an active particle system, where each particle can use energy from its surroundings to propel itself. A multi-dimensional feature vector containing all particles' motion information can describe the whole system at each time step. The system's behavior strongly depends on input parameters like the propulsion mechanism of the particles. To understand how the time-varying behavior depends on the input parameters, it is necessary to introduce new measures to quantify the difference of the dynamics of the ensemble members. We propose a tool that supports the interactive visual analysis of time-varying feature-vector ensembles. A core component of our tool allows for the interactive definition and refinement of new measures that can then be used to understand the system's behavior and compare the ensemble members. Different visualizations support the user in finding a characteristic measure for the system. By visualizing the user-defined measure, the user can then investigate the parameter dependencies and gain insights into the relationship between input parameters and simulation output.
翻译:模拟聚合物是物理学中了解模型结果如何依赖输入参数的一个常见工具。 我们分析一个活性粒子系统, 每个粒子可以从周围利用能量来推进自己。 一个包含所有粒子运动信息的多维特性矢量可以描述整个系统每个时间步骤。 这个系统的行为在很大程度上取决于输入参数, 比如粒子的推进机制 。 要理解时间变化行为如何取决于输入参数, 有必要引入新措施, 量化共性成员动态的差异 。 我们提出了一个工具, 支持对时间变化特性聚合物进行互动的视觉分析。 我们工具的一个核心组件允许对新的测量进行互动定义和完善, 然后用来理解系统的行为并比较共性成员。 不同的视觉化支持用户为系统找到一个特征测量。 通过直观用户定义的测量, 用户可以对参数依赖性和模拟输出结果之间的关系进行调查并获得洞察力 。