{"title":"An algorithm for U–Pb geochronology by secondary ion mass spectrometry","authors":"P. Vermeesch","doi":"10.5194/gchron-4-561-2022","DOIUrl":null,"url":null,"abstract":"Abstract. Secondary ion mass spectrometry (SIMS) is a widely used technique for in situ U–Pb geochronology of accessory minerals. Existing algorithms for SIMS data reduction and error propagation make a number of simplifying assumptions that degrade the precision and accuracy of the resulting U–Pb dates. This paper uses an entirely new approach to SIMS data processing that introduces the following improvements over previous algorithms. First, it treats SIMS measurements as compositional data using log-ratio statistics. This means that, unlike existing algorithms, (a) its isotopic ratio estimates are guaranteed to be strictly positive numbers, (b) identical results are obtained regardless of whether data are processed as normal ratios (e.g. 206Pb / 238U) or reciprocal\nratios (e.g. 238U / 206Pb), and\n(c) its uncertainty estimates account for the positive skewness of\nmeasured isotopic ratio distributions. Second, the new algorithm\naccounts for the Poisson noise that characterises secondary electron\nmultiplier (SEM) detectors. By fitting the SEM signals using the\nmethod of maximum likelihood, it naturally handles low-intensity ion\nbeams, in which zero-count signals are common. Third, the new\nalgorithm casts the data reduction process in a matrix format and\nthereby captures all sources of systematic uncertainty. These\ninclude significant inter-spot error correlations that arise from\nthe Pb / U–UO(2) / U calibration curve. The new\nalgorithm has been implemented in a new software package called\nsimplex. The simplex package was written in R and can\nbe used either online, offline, or from the command line. The programme\ncan handle SIMS data from both Cameca and SHRIMP instruments.\n","PeriodicalId":12723,"journal":{"name":"Geochronology","volume":"16 1","pages":""},"PeriodicalIF":2.7000,"publicationDate":"2022-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Geochronology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5194/gchron-4-561-2022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
引用次数: 3
Abstract
Abstract. Secondary ion mass spectrometry (SIMS) is a widely used technique for in situ U–Pb geochronology of accessory minerals. Existing algorithms for SIMS data reduction and error propagation make a number of simplifying assumptions that degrade the precision and accuracy of the resulting U–Pb dates. This paper uses an entirely new approach to SIMS data processing that introduces the following improvements over previous algorithms. First, it treats SIMS measurements as compositional data using log-ratio statistics. This means that, unlike existing algorithms, (a) its isotopic ratio estimates are guaranteed to be strictly positive numbers, (b) identical results are obtained regardless of whether data are processed as normal ratios (e.g. 206Pb / 238U) or reciprocal
ratios (e.g. 238U / 206Pb), and
(c) its uncertainty estimates account for the positive skewness of
measured isotopic ratio distributions. Second, the new algorithm
accounts for the Poisson noise that characterises secondary electron
multiplier (SEM) detectors. By fitting the SEM signals using the
method of maximum likelihood, it naturally handles low-intensity ion
beams, in which zero-count signals are common. Third, the new
algorithm casts the data reduction process in a matrix format and
thereby captures all sources of systematic uncertainty. These
include significant inter-spot error correlations that arise from
the Pb / U–UO(2) / U calibration curve. The new
algorithm has been implemented in a new software package called
simplex. The simplex package was written in R and can
be used either online, offline, or from the command line. The programme
can handle SIMS data from both Cameca and SHRIMP instruments.