Singularity analysis of magmatic flare-ups caused by India – Asia collisions

Abstract

Frequency distribution (histogram) calculated on the basis of igneous and detrital zircon U-Pb ages has been commonly utilized to interpret the age (range) of magmatic events. The temporal properties revealed by these types of data have also been integrated with other types of isotope data (e.g., neodymium, hafnium, and oxygen) to describe the high magmatic addition rate (MAR) and its association with the growth or reworking of the continental crust. Major peaks are picked to associate with pulses of high-volume magmatic flare-ups related to episodic evolution of continental crust. With the development of modern isotope identification technology which results both in reduction of analytical error of isotope data and rapid accumulation of massive high-quality data, the temporal and frequency variances of these types of data ought to be quantitatively analyzed to study magmatic evolution with respect to tectonic background. A new fractal density concept and a local singularity analysis (LSA) method have been recently and successfully applied to analyze the geometric property of the age peaks in global zircon U-Pb age database by power law models. The anomalies of age peaks identified are linked to deeply rooted avalanches associated with short spurts of convection during formation of supercontinents and continent crust growth. In this paper, the method is further used to analyze a small dataset of U-Pb ages from Gangdese arc to characterize the causational relationship of age peak and India-Asia collision. The results show that the age density around peak at 51Ma can be fitted by power law functions. Both the scaling range of the age distribution and the exponents of the power law functions observed from the data suggest that the age peak may reflect magmatic flare-ups which would have been caused by superimposing of subduction, exhumation and slab breakoffs. It has been demonstrated that the LSA can be used as a new way to quantitatively characterize magmatic flare-ups based on U-Pb age data from a fractal density point of view.