Hybrid Quantum-Classical Neural Network for Calculating Ground State Energies of Molecules

We present a hybrid quantum-classical neural network that can be trained to perform electronic structure calculation and generate potential energy curves of simple molecules. The method is based on the combination of parameterized quantum circuits and measurements. With unsupervised training, the neural network can generate electronic potential energy curves based on training at certain bond lengths. To demonstrate the power of the proposed new method, we present the results of using the quantum-classical hybrid neural network to calculate ground state potential energy curves of simple molecules such as H2, LiH, and BeH2. The results are very accurate and the approach could potentially be used to generate complex molecular potential energy surfaces.

Bridging the gap between laboratory astrophysics and quantum chemistry: The concept of potential energy surfaces

An exotic molecular inventory exists in space. While some species have well-known terrestrial analogs, others are very reactive and can hardly survive in the laboratory timely to allow for their characterization. With an eye toward these latter, we highlight in this contribution the role of quantum chemistry in providing astrochemically relevant data where experiment struggles. Special attention is given to the concept of molecular potential energy surfaces (PESs), a key aspect in theoretical chemical physics, and the possible dynamical attributes taken therefrom. As case studies, we outline our current efforts in obtaining global PESs of carbon clusters. It is thus hoped that, with such an active synergy between theoretical chemistry and state-of-the-art experimental/observational techniques (the pillars to the modern laboratory astrophysics), scientists may gather the required knowledge to explain the origins, abundances and the driving force toward molecular complexity in the Universe.

Two-level stochastic search of low-energy conformers for molecular spectroscopy: implementation and validation of MM and QM models

The search for stationary points in the molecular potential energy surfaces (PES) is a problem of increasing relevance in molecular sciences especially for large, flexible systems featuring several large-amplitude internal motions.

The Cavitation Nuclei Transient Characteristics of Lennard-Jones Fluid in Cavitation Inception

In the field of ocean engineering, cavitation is widespread, for the study of cavitation nuclei transient characteristics in cavitation inception, we applied theoretical analysis and molecular dynamics (MD) simulation to study Lennard-Jones (L-J) fluid with different initial cavitation nuclei under the NVT-constant ensemble in this manuscript. The results showed that in cavitation inception, due to the decrease of liquid local pressure, the liquid molecules would enter the cavitation nuclei, which contributed to the growth of cavitation nuclei. By using molecular potential energy, it was found that the molecular potential energy was higher in cavitation nuclei part, while the liquid molecular potential energy changes greatly at the beginning of the cavitation nuclei growth. The density of the liquid and the surface layer changes more obvious, but density of vapor in the bubble changes inconspicuously. With the growth of cavitation nuclei, the RDF peak intensity increased, the peak width narrowed and the first valley moved inner. When cavitation nuclei initial size reduced, the peak intensity reduced, the corresponding rbin increased. With the decrease of the initial cavitation nuclei, the system pressure and total energy achieved a balance longer, and correspondingly, they were smaller. In addition, at the beginning of the cavitation nuclei growth, the total energy and system pressure changed greatly.