Stability of ultracold polyatomic molecules
Abstract
This proposal aims to elucidate the primary loss mechanism of one of the most prospective systems for novel quantum technologies- ultracold polyatomic molecules. Thus, this project will contribute to one of the main focuses of the atomic, molecular and optical physics research program of the AFOSR, namely ultracold quantum gases. Furthermore, this proposal s results will naturally help establish a bridge between ultracold quantum gases and the development of novel quantum technologies, another essential focus of the AMO research program of the AFOSR. We propose a new theoretical approach for calculating the lifetime of intermediate complexes of ultracold polyatomic molecules based on a new method for computing accurate multi-atomic potential energy surfaces. First, we will develop a hybrid ab initio-machine learning method to compute the underlying potential energy surface. Next, we will employ on-the-fly ab initio molecular dynamics simulations to calculate the lifetime of intermediate complexes. In particular, our approach requires a few thousand geometries at a high level of theory, whereas the rest of the points will be estimated through a machine learning algorithm. Thus, gaining computational efficiency without compromising accuracy. Furthermore, our proposed methodology is generalizable to any multi-atomic system going beyond state-of-the-art for ultracold molecules based on diatomic-diatomic processes and impacting chemical physics. Finally, it is worth emphasizing that this project relies on synergetic efforts across disciplines to find solutions to challenging scenarios. In particular, we will show how data science, when properly combined with quantum chemistry, will lead to a new set of tools that can bring us to a profound understanding of molecular processes. In this line, we plan to release an open source software to approach our ideas and methodology to the community.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 29, 2024
- Source ID
- FA95502310202
Entities
People
- Jesus Perez Rios
Organizations
- Air Force Office of Scientific Research
- Research Foundation for the State University of New York
- United States Air Force