School of Physics, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
Chaos. 2019 May;29(5):053101. doi: 10.1063/1.5086936.
The motion of and interaction between phase singularities that lie at the centers of spiral waves capture many qualitative and, in some cases, quantitative features of complex dynamics in excitable systems. Being able to accurately reconstruct their position is thus quite important, even if the data are noisy and sparse, as in electrophysiology studies of cardiac arrhythmias, for instance. A recently proposed global topological approach [Marcotte and Grigoriev, Chaos 27, 093936 (2017)] promises to meaningfully improve the quality of the reconstruction compared with traditional, local approaches. Indeed, we found that this approach is capable of handling noise levels exceeding the range of the signal with minimal loss of accuracy. Moreover, it also works successfully with data sampled on sparse grids with spacing comparable to the mean separation between the phase singularities for complex patterns featuring multiple interacting spiral waves.
位于螺旋波中心的相位奇点的运动和相互作用捕获了兴奋系统中复杂动力学的许多定性特征,在某些情况下,还捕获了定量特征。因此,即使数据存在噪声和稀疏,例如在心律失常的电生理学研究中,准确地重建它们的位置也非常重要。最近提出的全局拓扑方法[Marcotte 和 Grigoriev,Chaos 27,093936(2017)]有望与传统的局部方法相比,显著提高重建的质量。事实上,我们发现该方法能够处理噪声水平超过信号范围的情况,而几乎不会降低准确性。此外,它还可以成功处理稀疏网格上的数据采样,这些数据的间距与具有多个相互作用的螺旋波的复杂模式的相位奇点之间的平均间隔相当。