Abstract: The present disclosure relates to a data processing method and apparatus for a quantum chemistry system. The data processing method for a quantum chemistry system comprises the following steps: acquiring a specific wave function which is constructed on the basis of a neural network and is suitable for a quantum chemistry system; performing walker processing on the basis of the specific wave function, the walker processing comprising diffusion processing of walkers; and determining related information about chemical properties of the quantum chemistry system on the basis of the specific wave function and the processed walkers.

Abstract: A method is proposed for a deep learning simulation of a topological insulator. The method includes determining, by using a neural network, a wavefunction of a moiré system based on positions and spins of electrons of the moiré system; and determining, based on the wavefunction, whether the moiré system is a topological insulator.

Abstract: The present disclosure relates to a data processing method and apparatus for a quantum chemistry system. The data processing method for a quantum chemistry system comprises the following steps: acquiring a specific wave function which is constructed on the basis of a neural network and is suitable for a quantum chemistry system; performing walker processing on the basis of the specific wave function, the walker processing comprising diffusion processing of walkers; and determining related information about chemical properties of the quantum chemistry system on the basis of the specific wave function and the processed walkers.

Abstract: The present disclosure relates to a method and apparatus for determining a relative energy between systems, an electronic device, a computer-readable storage medium, and a computer program product. The method includes: for a chemical system, performing a plurality of iteration rounds using a neural network variational Monte Carlo method; acquiring a linear relationship between energy errors and energy variances, which are obtained in the plurality of iteration rounds; determining a first energy error at a position where the energy variance is zero based on the linear relationship; and determining the relative energy between the chemical system and a further system based on the first energy error.

Abstract: The present disclosure relates to a method and apparatus for determining a relative energy between systems, an electronic device, a computer-readable storage medium, and a computer program product. The method includes: for a chemical system, performing a plurality of iteration rounds using a neural network variational Monte Carlo method; acquiring a linear relationship between energy errors and energy variances, which are obtained in the plurality of iteration rounds; determining a first energy error at a position where the energy variance is zero based on the linear relationship; and determining the relative energy between the chemical system and a further system based on the first energy error.