Next Generation Software for Quantum Molecular Modeling with Application in Resonance Raman Spectroscopy
Abstract
Light-matter interactions play a crucial role in areas of physics, chemistry, biology, and materials science. Experimental spectra usually yield indirect information about structure and dynamics, but theoretical computations have become indispensable in modern molecular research to fully understand and explain these findings. In these areas of computer-aided natural sciences, a paradigm shift is on its way, both in academia and industry. Billions of Euros and dollars are invested in building a world-class high-performance computing (HPC) ecosystem in order to raise the competitiveness of academia and industry alike. The lead is represented by the Frontier supercomputer at Oak Ridge National Laboratory in the U.S. that has surpassed the dream limit of one exaFlop-s of LinPack performance, for long a holy grail in HPC. 1. In order to leverage these vast hardware resources, the invention of new methods and software in quantum chemistry is required, because with a full exploitation of these GPU-accelerated heterogenous architectures, enormous capacities are made available that will enable the field of computational material design to address model systems of so far unimaginable complexity and size.The present project will explore the opportunity to combine the analytical Lagrangian derivative technique that is used for derivations of molecular gradients and Hessians with CPP theory that offers a physically sound description of optical responses in resonance regions of the spectrum. Born out of this fusion, we will create a method able to efficiently and accurately simulate resonance Raman spectroscopy (RRS) and with the choice of Kohn–Sham density functional theory as the underlying electronic structure theory method, it will enable simulations of large-scale systems that reach far beyond the current scope of applications.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 22, 2024
- Source ID
- FA86552317015
Entities
People
- Patrick Norman
Organizations
- Air Force Office of Scientific Research
- Royal Institute of Technology
- United States Air Force