An Improved Algorithm for Unmixing First-Order Reversal Curve Diagrams Using Principal Component Analysis

Harrison, Richard J. and Muraszko, Joy and Heslop, David and Lascu, Ioan and Muxworthy, Adrian R. and Roberts, Andrew P. (2018) An Improved Algorithm for Unmixing First-Order Reversal Curve Diagrams Using Principal Component Analysis. Geochemistry, Geophysics, Geosystems, 19 (5). pp. 1595-1610. ISSN 15252027 DOI https://doi.org/10.1029/2018GC007511

	Text Harrison_et_al-2018-Geochemistry%2C_Geophysics%2C_Geosystems.pdf - Published Version Download (2MB)
	Text ggge21560-sup-0001-2018GC007511-s01.docx - Supplemental Material Download (50kB)
	Archive ggge21560-sup-0002-2018GC007511-ds01.zip - Supplemental Material Download (483kB)
	Archive ggge21560-sup-0003-2018GC007511-ds02.zip - Supplemental Material Download (2MB)
	Archive ggge21560-sup-0004-2018GC007511-ds03.zip - Supplemental Material Download (2MB)
	Archive ggge21560-sup-0005-2018GC007511-ds04.zip - Supplemental Material Download (2MB)
	Archive ggge21560-sup-0006-2018GC007511-ds05.zip - Supplemental Material Download (1MB)

Abstract

First‐order reversal curve (FORC) diagrams of synthetic binary mixtures with single‐domain, vortex state, and multidomain end‐members (EMs) were analyzed using principal component analysis (FORC‐PCA). Mixing proportions derived from FORC‐PCA are shown to deviate systematically from the known weight percent of EMs, which is caused by the lack of reversible magnetization contributions to the FORC distribution. The error in the mixing proportions can be corrected by applying PCA to the raw FORCs, rather than to the processed FORC diagram, thereby capturing both reversible and irreversible contributions to the signal. Here we develop a new practical implementation of the FORC‐PCA method that enables quantitative unmixing to be performed routinely on suites of FORC diagrams with up to four distinct EMs. The method provides access not only to the processed FORC diagram of each EM, but also to reconstructed FORCs, which enables objective criteria to be defined that aid identification of physically realistic EMs. We illustrate FORC‐PCA with examples of quantitative unmixing of magnetic components that will have widespread applicability in paleomagnetism and environmental magnetism.

Item Type:	Article
Uncontrolled Keywords:	2018AREP; IA73
Subjects:	03 - Mineral Sciences
Divisions:	03 - Mineral Sciences 08 - Green Open Access
Journal or Publication Title:	Geochemistry, Geophysics, Geosystems
Volume:	19
Page Range:	pp. 1595-1610
Identification Number:	https://doi.org/10.1029/2018GC007511
Depositing User:	Sarah Humbert
Date Deposited:	22 Oct 2018 10:08
Last Modified:	12 Sep 2019 09:41
URI:	http://eprints.esc.cam.ac.uk/id/eprint/4347

Actions (login required)

View Item