Attractor Reconstruction from Experimental Data

以马里兰大学为中心的一组研究人员将参与混沌动力系统的数学和物理研究，特别是通过嵌入方法重建吸引子的基础问题，以及通过嵌入方法恢复动力学，这对于使该方法对实验数据有用至关重要。其他有待研究的领域是混沌瞬态和计算机生成的非线性过程轨迹的严格验证。重点将放在计算机算法的发展，用于分析实验数据。混沌和混沌行为的研究在过去的十年中引起了人们的关注，并且有大量的机会在理论家和实验家之间进行令人兴奋的互动，以便将新的理论认识转移到实验室。

A group of researchers centered at the University of Maryland will be involved in mathematical and physical research on chaotic dynamical systems, including in particular foundational questions of attractor reconstruction through embedding methods, and the recovery of the dynamics through the embedding method, which is critical to making the approach useful for experimental data. Other areas to be investigated are chaotic transients and the rigorous verification of computer- generated trajectories of nonlinear processes. The focus will be on development of computer algorithms for the analysis of data from experiments. The study of chaos and chaotic behavior has attracted attention over the past decade, and there are substantial opportunities for exciting interactions between theoreticians and experimentalists, so that new theoretical understanding can be transferred to the laboratory.