Computational Aspects of the One Body Reduced Density Matrix Functional Theory
Researchers are increasingly using computer simulations to develop new drugs and materials. This saves time and costs, because promising molecules can first be tested digitally before laboratory studies are required. Still, some chemical processes remain difficult to simulate accurately, especially so-called "highly correlated systems," which arise, for example, when chemical bonds are stretched.
Quantum chemist Nicolas Cartier developed a new algorithm that significantly speeds up these complex calculations. His research focuses on a relatively little-explored method within quantum chemistry: reduced density matrix functional theory (RDMFT). Using his approach, calculations can often be performed up to 10 times faster than before.
Moreover, according to Cartier, there is potential to make the method even much more efficient via a completely new computational approach, although further research is needed to do so. Thanks to the acceleration, RDMFT calculations not only become more practical, but also usable for larger and more realistic molecules.
Faster and more accurate simulations can accelerate the development of new drugs, contribute to sustainable alternatives to petrochemicals and help develop innovative agrochemical applications for food production. Problems hitherto too complex to reliably simulate may thus come within reach of researchers and companies.
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