|Title||pySCu: a new python code for analyzing remagnetizations directions by means of Small Circle utilities|
|Publication Type||Journal Article|
|Year of Publication||2017|
|Authors||Calvín P, Villalaín JJ, Casas-Sainz AM, Tauxe L, Torres-López S|
|Journal||Computers & Geosciences|
|Keywords||fold-test; remagnetization; SCI method; Small Circle; synfolding, pySCu|
The Small Circle (SC) methods are founded upon two main starting hypotheses: (i) the analyzed sites were remagnetized contemporarily, acquiring the same paleomagnetic direction. (ii) The deviation of the acquired paleomagnetic signal from its original direction is only due to tilting around the bedding strike and therefore the remagnetization direction must be located on a small circle (SC) whose axis is the strike of bedding and contains the in situ paleomagnetic direction. Therefore, if we analyze several sites (with different bedding strikes) their SCs will intersect in the remagnetization direction. The SC methods have two applications: (1) the Small Circle Intersection (SCI) method is capable of providing adequate approximations to the expected paleomagnetic direction when dealing with synfolding remagnetizations. By comparing the SCI direction with that predicted from an apparent polar wander path, the (re)magnetization can be dated. (2) Once the remagnetization direction is known, the attitude of the beds (at each site) can be restored to the moment of the acquisition of the remagnetization, showing a unique picture of the structure in the past (palinspastic reconstruction). Some caveats are necessary under more complex tectonic scenarios, in which SC-based methods can lead to erroneous interpretations. However, the graphical output of the methods tries to avoid ‘black-box’ effects and can minimize misleading interpretations or even help, for example, to identify local or regional vertical axis rotations. In any case, the methods must be used with caution and always considering the knowledge of the tectonic frame in which it is applied. In this paper, some utilities for SCs analysis are automatized by means of a new Python code. With pySCu the SCs methods can be easily and quickly applied, obtaining firstly a set of text files containing all calculated information and subsequently generating a graphical output on the fly.
|Short Title||Comput. Geosci.|