MehrteilchenPotenziale

MehrteilchenPotenziale, often translated as many-body potentials or multiparticle potentials, are mathematical functions used in physics and chemistry to describe the interactions between multiple particles. Unlike simple pairwise potentials that only consider the interaction between two particles at a time, many-body potentials account for the influence of the environment, meaning the interaction between two particles can depend on the presence and positions of other particles.

These potentials are crucial for accurately modeling systems where collective effects are significant, such as in condensed matter physics, quantum chemistry, and molecular dynamics simulations. For example, the potential energy of a water molecule might not just depend on the interactions between hydrogen and oxygen atoms within that molecule, but also on the surrounding water molecules through hydrogen bonding networks.

Developing and implementing accurate many-body potentials is computationally challenging. Simple pairwise potentials, like the Lennard-Jones potential, are computationally inexpensive but often fail to capture complex phenomena. Many-body potentials can be built upon pairwise interactions by adding specific terms that capture three-body, four-body, and higher-order interactions. Alternatively, machine learning techniques are increasingly used to develop data-driven many-body potentials that can learn complex interaction patterns from quantum mechanical calculations or experimental data. The inclusion of these potentials is essential for achieving high fidelity in simulations of materials, chemical reactions, and biological systems.