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- W2573015339 abstract "Markov chain Monte Carlo (MCMC) simulation is a powerful statistical method in solving inverse problems that arise from a wide range of applications. In Earth sciences applications of MCMC simulations are primarily in the field of geophysics. The purpose of this study is to introduce MCMC methods to geochemical inverse problems related to trace element fractionation during mantle melting. MCMC methods have several advantages over least squares methods in deciphering melting processes from trace element abundances in basalts and mantle rocks. Here we use an MCMC method to invert for extent of melting, fraction of melt present during melting, and extent of chemical disequilibrium between the melt and residual solid from REE abundances in clinopyroxene in abyssal peridotites from Mid-Atlantic Ridge, Central Indian Ridge, Southwest Indian Ridge, Lena Trough, and American-Antarctic Ridge. We consider two melting models: one with exact analytical solution and the other without. We solve the latter numerically in a chain of melting models according to the Metropolis–Hastings algorithm. The probability distribution of inverted melting parameters depends on assumptions of the physical model, knowledge of mantle source composition, and constraints from the REE data. Results from MCMC inversion are consistent with and provide more reliable uncertainty estimates than results based on nonlinear least squares inversion. We show that chemical disequilibrium is likely to play an important role in fractionating LREE in residual peridotites during partial melting beneath mid-ocean ridge spreading centers. MCMC simulation is well suited for more complicated but physically more realistic melting problems that do not have analytical solutions." @default.
- W2573015339 created "2017-01-26" @default.
- W2573015339 creator A5003521519 @default.
- W2573015339 creator A5068745618 @default.
- W2573015339 date "2017-04-01" @default.
- W2573015339 modified "2023-10-16" @default.
- W2573015339 title "An introduction of Markov chain Monte Carlo method to geochemical inverse problems: Reading melting parameters from REE abundances in abyssal peridotites" @default.
- W2573015339 cites W1483550092 @default.
- W2573015339 cites W1498216505 @default.
- W2573015339 cites W1573196231 @default.
- W2573015339 cites W1782431849 @default.
- W2573015339 cites W1786672761 @default.
- W2573015339 cites W1966133457 @default.
- W2573015339 cites W1967096406 @default.
- W2573015339 cites W1969303984 @default.
- W2573015339 cites W1970768689 @default.
- W2573015339 cites W1976788350 @default.
- W2573015339 cites W1977457396 @default.
- W2573015339 cites W1983428771 @default.
- W2573015339 cites W1987243508 @default.
- W2573015339 cites W1992891991 @default.
- W2573015339 cites W1995981686 @default.
- W2573015339 cites W1999578482 @default.
- W2573015339 cites W2001173398 @default.
- W2573015339 cites W2001973404 @default.
- W2573015339 cites W2007433465 @default.
- W2573015339 cites W2011607179 @default.
- W2573015339 cites W2016159174 @default.
- W2573015339 cites W2016701904 @default.
- W2573015339 cites W2019426353 @default.
- W2573015339 cites W2021620030 @default.
- W2573015339 cites W2022104527 @default.
- W2573015339 cites W2023509153 @default.
- W2573015339 cites W2034884518 @default.
- W2573015339 cites W2035743760 @default.
- W2573015339 cites W2037893193 @default.
- W2573015339 cites W2039535921 @default.
- W2573015339 cites W2041529465 @default.
- W2573015339 cites W2042149675 @default.
- W2573015339 cites W2052997567 @default.
- W2573015339 cites W2054757994 @default.
- W2573015339 cites W2056760934 @default.
- W2573015339 cites W2058000599 @default.
- W2573015339 cites W2059982963 @default.
- W2573015339 cites W2060921520 @default.
- W2573015339 cites W2062218969 @default.
- W2573015339 cites W2062367490 @default.
- W2573015339 cites W2064822299 @default.
- W2573015339 cites W2066236108 @default.
- W2573015339 cites W2066968098 @default.
- W2573015339 cites W2069157151 @default.
- W2573015339 cites W2076240168 @default.
- W2573015339 cites W2078840355 @default.
- W2573015339 cites W2080519657 @default.
- W2573015339 cites W2084042374 @default.
- W2573015339 cites W2086285917 @default.
- W2573015339 cites W2088908478 @default.
- W2573015339 cites W2093570940 @default.
- W2573015339 cites W2095017942 @default.
- W2573015339 cites W2098839042 @default.
- W2573015339 cites W2099914884 @default.
- W2573015339 cites W2104295992 @default.
- W2573015339 cites W2113369720 @default.
- W2573015339 cites W2114660893 @default.
- W2573015339 cites W2115460401 @default.
- W2573015339 cites W2120027408 @default.
- W2573015339 cites W2121703172 @default.
- W2573015339 cites W2126883357 @default.
- W2573015339 cites W2133264142 @default.
- W2573015339 cites W2134226415 @default.
- W2573015339 cites W2134309362 @default.
- W2573015339 cites W2138309709 @default.
- W2573015339 cites W2139696801 @default.
- W2573015339 cites W2140036873 @default.
- W2573015339 cites W2143909904 @default.
- W2573015339 cites W2145237455 @default.
- W2573015339 cites W2164221510 @default.
- W2573015339 cites W2195087649 @default.
- W2573015339 cites W2225045766 @default.
- W2573015339 cites W2314681610 @default.
- W2573015339 cites W2316110691 @default.
- W2573015339 cites W2324661783 @default.
- W2573015339 cites W3010292040 @default.
- W2573015339 cites W3036024830 @default.
- W2573015339 cites W3162624508 @default.
- W2573015339 doi "https://doi.org/10.1016/j.gca.2016.12.040" @default.
- W2573015339 hasPublicationYear "2017" @default.
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