Step 1: Understanding Bowen’s reaction series.
Bowen’s reaction series describes the sequence of crystallization of minerals from a cooling magma. It is divided into two branches: the discontinuous series and the continuous series.
Step 2: Continuous series.
The continuous series of Bowen's reaction series is represented by the anorthite - albite system. This system describes the solid-solution behavior of the plagioclase feldspar group, where anorthite (Ca-rich) and albite (Na-rich) are the two endmembers. As magma cools, plagioclase feldspar crystallizes in a continuous fashion, with the mineral composition shifting from anorthite to albite.
Step 3: Comparing the other options.
The orthoclase - albite feldspar system represents alkali feldspar but is not part of the continuous series.
The forsterite - fayalite system represents the olivine group, which is part of the discontinuous series.
The diopside - anorthite system represents pyroxenes and feldspars, but it is not related to the continuous series.
The following table provides the mineral chemistry of a garnet. All oxides are in weight percentage and cations in atoms per formula unit. Total oxygen is taken as 12 based on the ideal garnet formula. Consider Fe as Fetotal and Fe\(^{3+}\) = 0. The Xpyrope of this garnet is _.
Choose the correct combination of minerals (listed in Group A) with the corresponding locations of their deposits (listed in Group B).
The combinations listed below represent major minerals observed in four igneous rocks:
(i) Olivine and Anorthite, (ii) K-feldspar and Quartz, (iii) Mg-Ca-pyroxene and Ca-Na-plagioclase, (iv) Amphibole and Na-Ca-plagioclase
Arrange these mineral combinations based on decreasing temperature of magma crystallization.
A color model is shown in the figure with color codes: Yellow (Y), Magenta (M), Cyan (Cy), Red (R), Blue (Bl), Green (G), and Black (K). Which one of the following options displays the color codes that are consistent with the color model?
While doing Bayesian inference, consider estimating the posterior distribution of the model parameter (m), given data (d). Assume that Prior and Likelihood are proportional to Gaussian functions given by \[ {Prior} \propto \exp(-0.5(m - 1)^2) \] \[ {Likelihood} \propto \exp(-0.5(m - 3)^2) \]
The mean of the posterior distribution is (Answer in integer)