Power functional theory (PFT) vs traditional Dynamic DFT

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Dynamic density functional theory "has weaknesses, as physicists from the University of Bayreuth have now shown in an article published in the Journal of Physics: Condensed Matter. Power functional theory proves to perform substantially better—in combination with artificial intelligence methods, it enables more reliable descriptions and predictions of the dynamics of non-equilibrium systems over time."

https://phys.org/news/2023-06-physi...hQVplcl7zlAoab8Qev-9Yq-Bhcz9UYrocQPXrouyg4mFI
Many-particle systems are all kind of systems composed of atoms, electrons, molecules, and other particles invisible to the eye. They are in thermal equilibrium when the temperature is balanced and no heat flow occurs. A system in thermal equilibrium changes its state only when external conditions change. Density functional theory is tailor-made for the study of such systems.

For more than half a century, it has proven its unrestricted value in chemistry and materials science. Based on a powerful classical variant of this theory, states of equilibrium systems can be described and predicted with high accuracy. Dynamic density functional theory (DDFT) extends the scope of this theory to non-equilibrium systems. This involves the physical understanding of systems whose states are not fixed by their external boundary conditions.

For ten years, the research team around Prof. Dr. Matthias Schmidt has been making significant contributions to the development of a still young physical theory, which has so far proven to be very successful in the physical study of many-particle systems: power functional theory (PFT). The physicists from Bayreuth are pursuing the goal of being able to describe the dynamics of non-equilibrium systems with the same precision and elegance with which classical density functional theory enables the analysis of equilibrium systems.

Perspective: How to overcome dynamical density functional theory​

https://iopscience.iop.org/article/10.1088/1361-648X/accb33
 
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