 |
Center for Nonlinear Studies |
The optical nonlinear response of physical and chemical systems provides a unique and powerful window into their fundamental properties. However, the wealth of information contained in this light-matter interaction can also create complications in understanding as well as simulating the response. As a solution to the first problem, machine learning is presented as a viable solution. Its utility is demonstrated for the case of sum-frequency response. The new approach provides chemical information discovery under extremely poor signal to noise situations. For the second issue, a computational package is developed with the ability to handle open quantum systems and produce the spectroscopic response for arbitrary nonlinear light-matter interaction. This program utilizes the powerful quantum-modeling tool, QuTip, for handling the system evolution. As a result, it has the ability to simulate a wide variety of open quantum systems.
Host: Andrei Piryatinski (T-4)