Solving nonlinear ambiguous multivariate input-output (causal-effect) problems in space and solar physics with information theory
John Hopkins University
Many physical systems are nonlinear. These systems can be characterized as input-output or causal-effect problems in which multiple input variables can be linearly and nonlinearly causally related to multiple output variables. Moreover, the input variables can be linearly and nonlinearly correlated with one another, which may lead to ambiguities as to which variables are really the main drivers of the system. Isolating the effect of an individual input variable or driver can be challenging. Likewise, identifying the response to a particular input variable can be nontrivial in such system. Information theory can help untangle the drivers, describe the underlying dynamics and response, and offer constraints to modelers and theorists, leading to better understanding of the system. To illustrate the methodology, a few examples from are presented: (1) identifying causalities in the solar cycle; (2) untangling the drivers of the solar windâradiation belt system; and (3) identifying the source of the periodic radio wave emissions at Saturn. Implications to brown dwarfs and exoplanets are discussed.
|Date: ||Jeudi, le 2 avril 2020|
|Lieu: ||Université de Montréal|
| ||A-2553 - Campus MIL|
|Contact: ||Paul Charbonneau|