We present an in situ visualization framework to capture comprehensive details of vortex dynamics in superconductor simulations. Vortices, which determine all electromagnetic properties of type-II superconductors, are extracted and tracked at the same time with GPU-based time-dependent Ginzburg-Landau superconductor simulations. The in situ workflow involves three parts: (1) a tightly coupled GPU-accelerated algorithm that detects primitives for ambiguity-free vortex tracking, (2) a loosely coupled task-parallel feature-tracking method, and (3) a web-based remote visualization tool for vortex dynamics analysis. Our design minimizes the data movement and storage, maximizes the resource utilization, and reduces the slowdown of the simulation. Our solution captures all vortex dynamics in the simulation, previously impossible with traditional post hoc methods. We also demonstrate in situ visualization cases that help scientists understand how vortices cut each other and recombine into new vortices, which are directly related to energy dissipation of superconducting materials.

We propose a method for the vortex extraction and tracking of superconducting magnetic flux vortices for both structured and unstructured mesh data. In the Ginzburg-Landau theory, magnetic flux vortices are well-defined features in a complex-valued order parameter field, and their dynamics determine electromagnetic properties in type-II superconductors. Our method represents each vortex line (a 1D curve embedded in 3D space) as a connected graph extracted from the discretized field in both space and time. For a time-varying discrete dataset, our vortex extraction and tracking method is as accurate as the data discretization. We then apply 3D visualization and 2D event diagrams to the extraction and tracking results to help scientists understand vortex dynamics and macroscale superconductor behavior in greater detail than previously possible.