Archaeological applications of laser-induced breakdown spectroscopy: an example from the Coso Volcanic Field, California, using advanced statistical signal processing analysis

摘要

Over the past quarter century, multielement chemical analysis has become a common means for attributing the provenance of archaeological materials. The Coso Volcanic Field (CVF) in California, USA, contains at least 38 high-silica rhyolite domes, many of which contain obsidian glass that has been quarried for tools by the indigenous population for more than 12,000 years. Artifacts made from CVF obsidian are found throughout the southwestern United States and geochemical sourcing of CVF obsidian has been an important tool in understanding prehistoric Native American trading patterns. Laser-induced breakdown spectroscopy (LIBS) is a simple atomic emission spectroscopic technique that has the potential for real-time man-portable chemical analysis in the field. Because LIBS is simultaneously sensitive to all elements, a single laser shot can be used to record the broadband emission spectra, which provides a "chemical fingerprint" of a material. Single-shot broadband LIBS spectra were collected using a commercial benchtop LIBS system for 27 obsidian samples from major sites across the CVF and four additional sites in California and western Nevada outside of CVF. Classification of the samples was performed using partial least-squares discriminant analysis (PLSDA), a common chemometric technique suitable for performing regression on high-dimensional data. Provenance identification for the obsidian samples was evaluated for three separate labeling frameworks. The first framework consisted of a binary classification problem to distinguish CVF samples from non-CVF samples. The second approach focused on the CVF samples with labels that corresponded to the eight separate Coso sites encompassed by the 27 samples. In the third analysis, non-CVF samples were excluded, and the remaining 27 CVF samples were labeled based on groupings defined from previous major and trace element chemical studies, which reduces the number of possible classes from eight to four. Different aspects of the classifier setup considered in this study include the training/testing routine (a 27-fold leave-one-sample-out setup versus a simple split of the data into separate sets for training and evaluation), the number of latent variables used in the regression model, and whether PLSDA operating on the entire broadband LIBS spectrum is superior to that using only a selected subset of LIBS emission lines. The results point to the robustness of the PLSDA technique and suggest that LIBS analysis combined with the appropriate statistical signal processing has the potential to be a useful tool for chemical analysis of archaeological artifacts and geological specimens.