• DOI:10.1109/TMAG.2017.2749618
• Corpus ID: 3448831

Lean Cohomology Computation for Electromagnetic Modeling

@article{Dlotko2018LeanCC,
  title={Lean Cohomology Computation for Electromagnetic Modeling},
  author={Pawel Dlotko and Bernard Kapidani and Ruben Specogna},
  journal={IEEE Transactions on Magnetics},
  year={2018},
  volume={54},
  pages={1-4}
}

• P. Dlotko, Bernard Kapidani, R. Specogna
• Published 1 March 2018
• Mathematics
• IEEE Transactions on Magnetics

Solving eddy current problems formulated by using a magnetic scalar potential in the insulator requires a topological pre-processing to find the so-called first cohomology basis of the insulating region, which may be very time-consuming for challenging industrially driven problems. The physics-inspired Dłotko–Specogna (DS) algorithm was shown to be superior to alternatives in performing such a topological pre-processing. Yet, the DS algorithm is particularly fast when it produces as output not a regular cohomology basis but a so-called lazy one, which contains the regular one but it keeps also some additional redundant elements. Having a regular basis may be advantageous over the lazy basis if a technique to produce it would take about the same time as the computation of a lazy basis. In the literature, such a technique is missing. This paper covers this gap by introducing modifications to the DS algorithm to compute a regular basis of the first cohomology group in practically the same time as the generation of a lazy cohomology basis. The speedup of this modified DS algorithm with respect to the best alternative reaches more than two orders of magnitudes on challenging benchmark problems. This demonstrates the potential impact of the proposed contribution in the low-frequency computational electromagnetics community and beyond.