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Paleomagnetic and environmental magnetic studies are commonly conducted on samples containing mixtures of magnetic minerals and/or grain sizes. Major hysteresis loops are routinely used to provide information about variations in magnetic mineralogy and grain size. Standard hysteresis parameters, however, provide a measure of the bulk magnetic properties, rather than enabling discrimination between the magnetic components that contribute to the magnetization of a sample. By contrast, first‐order reversal curve (FORC) diagrams, which we describe here, can be used to identify and discriminate between the different components in a mixed magnetic mineral assemblage. We use magnetization data from a class of partial hysteresis curves known as first‐order reversal curves (FORCs) and transform the data into contour plots (FORC diagrams) of a two‐dimensional distribution function. The FORC distribution provides information about particle switching fields and local interaction fields for the assemblage of magnetic particles within a sample. Superparamagnetic, single‐domain, and multidomain grains, as well as magnetostatic interactions, all produce characteristic and distinct manifestations on a FORC diagram. Our results indicate that FORC diagrams can be used to characterize a wide range of natural samples and that they provide more detailed information about the magnetic particles in a sample than standard interpretational schemes which employ hysteresis data. It will be necessary to further develop the technique to enable a more quantitative interpretation of magnetic assemblages; however, even qualitative interpretation of FORC diagrams removes many of the ambiguities that are inherent to hysteresis data.
Roberts et al. (Sun,) studied this question.