physics.plasm-ph

arXiv:2409.11065v2 Announce Type: replace-cross Abstract: Digital research data management is increasingly integrated across universities and research institutions, addressing the handling of research data throughout its lifecycle according to the FAIR data principles (Findable, Accessible, Interoperable, Reusable). Recent emphasis on the semantic and interlinking aspects of research data, e.g., by using ontologies and knowledge graphs further enhances findability and reusability. This work presents a framework for creating and maintaining a knowledge graph specifically for low-temperature plasma (LTP) science and technology. The framework leverages a domain-specific ontology called Plasma-O, along with the VIVO software as a platform for semantic information management in LTP research. While some research fields are already prepared to use ontologies and knowledge graphs for information management, their application in LTP research is nascent. This work aims to bridge this gap by providing a framework that not only improves research data management but also fosters community participation in building the domain-specific ontology and knowledge graph based on the published materials. The results may also support other research fields in the practical use of knowledge graphs for semantic information management.

arXiv:2501.01523v1 Announce Type: new Abstract: We propose a method for interpolating divergence-free continuous magnetic fields via vector potential reconstruction using Hermite interpolation, which ensures high-order continuity for applications requiring adaptive, high-order ordinary differential equation (ODE) integrators, such as the Dormand-Prince method. The method provides C(m) continuity and achieves high-order accuracy, making it particularly suited for particle trajectory integration and Poincar\'e section analysis under optimal integration order and timestep adjustments. Through numerical experiments, we demonstrate that the Hermite interpolation method preserves volume and continuity, which are critical for conserving toroidal canonical momentum and magnetic moment in guiding center simulations, especially over long-term trajectory integration. Furthermore, we analyze the impact of insufficient derivative continuity on Runge-Kutta schemes and show how it degrades accuracy at low error tolerances, introducing discontinuity-induced truncation errors. Finally, we demonstrate performant Poincar\'e section analysis in two relevant settings of field data collocated from finite element meshes