Data and software underlying the publication: Waiting for Forcot: Accelerating FORC Processing 100x using a Fast-Fourier-Transform Algorithm
Datacite citation style:
Berndt, Thomas; Chang, L. (Liao) (2019): Data and software underlying the publication: Waiting for Forcot: Accelerating FORC Processing 100x using a Fast-Fourier-Transform Algorithm. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:3964b8d9-8e5d-4c6e-849f-b6bc10834babOther citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
First-order reversal-curves (FORC) are a widely used tool to analyze magnetic mineralogy and domain states, but require extensive processing -- in particular smoothing -- to be plotted as FORC diagrams. Currently, smoothing is a computationally complex task involving repeated least-squares surface optimization routines, sometimes taking minutes to compute for high-resolution FORCs (leaving users with the feeling of ``waiting for Godot'', who never comes). Here we show how the same computation can be carried out much more efficiently in Fourier space and present a new FORC processing software, called Forcot. The new algorithm, combined with an improved user-interface enables users to create print-quality FORC diagrams within a few seconds. Processing times are shown to be reduced by factors from 2 to 100 depending on size and smoothing factor (SF) compared to existing FORC smoothing algorithms. Additionally, optimal SF can be determined directly from the noise spectrum in Fourier space and does not require repeated smoothing of diagrams as in previous programs. Finally, formatting of figures is done automatically by our software such that diagrams can be directly used for print.
- 2019-10-24 first online, published, posted
publisher4TU.Centre for Research Data
formatmedia types: application/octet-stream, application/x-dosexec, application/zip, image/png, text/markdown, text/plain, text/x-matlab
organizationsLaboratory of Orogenic Belts and Crustal Evolution, School of Earth and Space Sciences, Peking University, Beijing