Groundbreaking research from the University of Michigan has paved the way for the accurate modeling of large-scale material systems using quantum mechanics. Overcoming the long-standing challenge of accurately calculating interactions among electrons, an international team led by Professor Vikram Gavini developed a code that brings quantum mechanical accuracy within reach of today’s supercomputers. This achievement has been recognized by the Association for Computing Machinery (ACM) through the prestigious Gordon Bell Prize.
The ability to simulate and understand the properties and behavior of materials has been greatly expanded through quantum mechanical calculations. However, the complexity of modeling quantum wavefunctions for multiple connected electrons has limited their application to relatively small systems. This has hindered reliable material exploration and design through computer modeling, particularly for systems with thousands of electrons.
To address this limitation, Professor Gavini’s team bridged the gap between Quantum Many-Body (QMB) methodologies and Density Functional Theory (DFT). While QMB methods offer high accuracy, they are computationally intensive and restrict system sizes. On the other hand, DFT simplifies analysis by considering electron density but relies on approximate exchange-correlation (XC) functionals.
By solving the inverse DFT problem, Gavini and his team developed a machine-learned XC functional that matches the accuracy of QMB methods in ground-state energies. This breakthrough overcomes the accuracy limitation of DFT and enables large-scale predictive modeling of material physics. In fact, their calculations for a system involving approximately 620,000 electrons achieved unprecedented sustained performance on the Frontier Exascale supercomputer, reaching 660 petaflops.
This recognition from ACM highlights the exceptional work of Gavini’s group and their contributions to advancing materials modeling. By combining innovation and expertise, they have laid the foundation for accelerating our understanding of material properties, designing better alloys, catalysts, and even aiding in drug discovery.
The impact of this breakthrough extends beyond the realm of materials science, ushering in the Exascale computing era at the University of Michigan. Through their dedication and collaboration, Gavini’s team has opened doors to new possibilities in computational research.
Frequently Asked Questions (FAQ)
What is the Gordon Bell Prize?
The Gordon Bell Prize is an award presented by the Association for Computing Machinery (ACM) for outstanding achievements in high-performance computing.
What is Quantum Many-Body (QMB) methodology?
Quantum Many-Body (QMB) methodology is a class of quantum mechanics that deals with multiple interacting particles or electrons.
What is Density Functional Theory (DFT)?
Density Functional Theory (DFT) is a computational approach that simplifies the analysis of complex materials by considering the density of electrons rather than the wavefunctions of individual electrons.
What is the Frontier Exascale supercomputer?
The Frontier Exascale supercomputer is currently recognized as the most powerful supercomputer globally and is housed at the Oak Ridge National Laboratory.
How does this breakthrough impact materials science?
The breakthrough in quantum modeling opens doors for large-scale simulations of materials with unprecedented accuracy. It enables faster exploration of material properties, aids in computational design, and has potential applications in developing better alloys, catalysts, and drug discovery, among other areas.
Sources:
- University of Michigan: https://news.umich.edu/
- Association for Computing Machinery (ACM): https://www.acm.org/