Contact tracing Inspired Efficient Computation by Energy Tracing
Wending Mai, Ronald P. Jenkins, Yifan Chen, and Douglas H. Werner

TL;DR
This paper introduces an energy tracing-based method inspired by epidemic contact tracing to improve computational efficiency in electromagnetics by focusing resources on energy-active regions, demonstrating high efficiency and accuracy.
Contribution
The paper presents a novel energy tracing approach for electromagnetics that adaptively decomposes the domain, reducing unnecessary computations and potentially benefiting other physics simulations.
Findings
High efficiency in electromagnetics problems
Maintains good accuracy with adaptive domain decomposition
Potential applicability to other computational physics
Abstract
Inspired by the epidemic contact tracing technique, we propose a method to efficiently solve electromagnetics by tracing the energy distribution. The computational domain is adaptively decomposed, and the available computational resources are focused on those energy-active (infections) and their adjacent (exposed) domains, while avoiding the unnecessary computation of energy-null (unexposed) domains. As an example, we employ this method to solve several optics problems. The proposed method shows high efficiency while maintaining a good accuracy. The energy tracing method is based on the causality principle, and therefore is potentially transformative into other computational physics and associated algorithms.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNeural Networks and Reservoir Computing · Privacy-Preserving Technologies in Data
