论文标题
扩散和同步动力学揭示了空间隔离的多尺度模式
Diffusion and synchronization dynamics reveal the multi-scale patterns of spatial segregation
论文作者
论文摘要
城市系统的特征是具有异质特征的人群，其空间分布对于了解预期寿命或教育水平的不平等至关重要。关于空间隔离指标的传统研究通常集中在首次邻近的相关性上，但无法捕获复杂的多尺度模式。在这项工作中，我们旨在通过扩散和同步动力学来表征社会经济特征的空间分布异质性。特别是，我们利用需要达到同步的时间作为社会经济特征的空间异质性的代理，例如收入。我们对美国城市中16个收入类别的分析表明，最受剥夺和富裕的公民的空间分布导致更高的扩散和同步时间。通过衡量邻里到达全球阶段所需的时间，我们可以检测到那些遭受较陡的隔离的人。总体而言，目前的手稿例证了如何使用扩散和同步动力学来评估存在节点信息的异质性。
Urban systems are characterized by populations with heterogeneous characteristics, and whose spatial distribution is crucial to understand inequalities in life expectancy or education level. Traditional studies on spatial segregation indicators focus often on first-neighbour correlations but fail to capture complex multi-scale patterns. In this work, we aim at characterizing the spatial distribution heterogeneity of socioeconomic features through diffusion and synchronization dynamics. In particular, we use the time needed to reach the synchronization as a proxy for the spatial heterogeneity of a socioeconomic feature, as for example, the income. Our analysis for 16~income categories in cities from the United States reveals that the spatial distribution of the most deprived and affluent citizens leads to higher diffusion and synchronization times. By measuring the time needed for a neighborhood to reach the global phase we are able to detect those that suffer from a steeper segregation. Overall, the present manuscript exemplifies how diffusion and synchronization dynamics can be used to assess the heterogeneity in the presence of node information.
