Radiocarbon AMS Data Analysis: From Measured Isotopic Ratios to 14C Concentrations

Abstract

Radiocarbon accelerator mass spectrometry (AMS) measurements are always carried out relative to internationally accepted standards with known 14C activities. The determination of accurate 14C concentrations relies on the fact that standards and unknown samples must be measured under the same conditions. When this is not the case, data reduction is either performed by splitting the collected data set into subsets with consistent measurement conditions or by applying correction factors. This paper introduces a mathematical framework that exploits the intrinsic variability of an AMS system by combining arbitrary measurement parameters into a normalization function. This novel approach allows the en-masse reduction of large data sets by providing individual normalization factors for each data point. Both general features and practicalities necessary for its efficient application are discussed.