Molecular mechanics (MM) is a powerful tool to study the properties of molecular systems in the fields of biology and materials science. With the development of ab initio force field and the application of ab initio potential energy surface, the nuclear quantum effect (NQE) is becoming increasingly important for the robustness of the simulation. However, the state-of-the-art path-integral molecular dynamics simulation, which incorporates NQE in MM, is still too expensive to conduct for most biological and material systems. In this work, we analyze the locality of NQE, using both analytical and numerical approaches, and conclude that NQE is an extremely localized phenomenon in nonreactive molecular systems. Therefore, we can use localized machine learning (ML) models to predict quantum force corrections both accurately and efficiently. Using liquid water as example, we show that the ML facilitated centroid MD can reproduce the NQEs in both the thermodynamical and the dynamical properties, with a minimal increase in computational time compared to classical molecular dynamics. This simple approach thus largely decreases the computational cost of quantum simulations, making it really accessible to the studies of large-scale molecular systems.
We apply the stabilizer method to the study of some complicated molecules, such as water and benzene.In the minimal STO-3G basis, the former requires 14 qubits, and the latter 72 qubits, which is very challenging. Quite remarkably, We are still able to find the best stabilizer states at all the bond lengths. Just as the previously studied H 2 , LiH and BeH 2 molecules, here the stabilizer states also approximate the true ground states very well, especially when the molecules are strongly distorted. These results suggest stabilizer states could serve as natural reference states when the system involves strong static correlation. And in the language of quantum computing, one would expect stabilizer states to be natural initial states for chemical simulation.
The thermal conductivity test is mainly carried out under normal temperature conditions, and there are few reports on the thermal conductivity test at low temperature and high temperature. In this paper, the fabric heat transfer simulation based on non-steady state conditions is analyzed.
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